ThomHartleTradingStrategiesAnalysisCollection Vol 1

Thom Hartle Trading Strategy and Analysis collection Vol. 1: 2001-2004

2

On-target trading (Active Trader, July 2001)

7

Finding value opportunities (Active Trader, Aug. 2001)

13

Know thy market: Gauging typical price behavior (Active Trader, Oct. 2001)

18

Fundamentally technical trading (Active Trader, July 2002)

22

Familiarity breeds profitability (Active Trader, Sept. 2002)

30

Bull vs. Bear The details matter (Active Trader, Nov. 2002)

36

Equity curve drawdown management (Active Trader, Feb. 2003)

40

Opening shots (Active Trader, April 2003)

43

What goes up must come down (Active Trader, May 2003)

49

What's the time? (Active Trader, Aug. 2003)

54

Trend, consolidations and unchanged volume (Active Trader, Oct. 2003)

57

The telltale spread (Active Traderr, Nov. 2003)

61

Choosing the proper time frame (Active Trader, Dec. 2003)

65

The method trader (Active Traderr, April 2004)

71

Nasdaq 100 volume and the QQQ (Active Trader, July 2004)

TRADING Strategies

ON-TARGET trading Taking profits is a balancing act: Hold on too long and you risk giving back your gains. Get out too soon and your gains might not be worth holding on to. By using a scientific approach to solve this puzzle you can establish intelligent profit targets that BY THOM HARTLE

T

rading, like any other profession, is an acquired set of skills. Granted, certain individuals naturally possess the prerequisite abilities for successful trading: a superior memory for pattern recognition, supreme confidence and plenty of capital. As a result, they hit the ground running. However, there’s a learning curve for the rest of us — a step-by-step process of obtaining skills in areas such as trade entry, trade exit and money management (taking profits and controlling risk). How to set a target for taking profits is an essential part of this process.

Before explaining the method of setting targets, we’ll review the basic guidelines of the trading process we’ll be working with. First, technical analysis lends itself to a scientific approach of defining your trading procedure. The word lends is important here, because not all technical analysis methods can be used in a scientific way. For example, the relationship between today’s closing price and a 102

enhance your performance.

day moving average of the closing price is an observable condition with only one of three possible outcomes: Today’s close is either greater than, less than or equal to the moving average. The advantage of using technical approaches with such precise definitions is that you can convert the definitions into trading rules or procedures and then test them on historical data to determine the outcome. For example, let’s compare two technical analysis concepts that point to an expected outcome. The first is the close vs. the moving average, as described above. The second is the break of the trendline referred to as the “neckline” of the head-and-shoulders top pattern. The first is very specific, while the latter is difficult to precisely define. Can you precisely define the head-and-shoulders chart pattern in combination with the break of the neckline in such a way that you can create a rule and test its outcome? If you can, great. If not, you might want to avoid this kind of analysis. What is the problem with not having precise definitions? Imagine you are reviewing charts, trying to measure the

outcome of a particular chart reversal pattern. Seeing the outcome together with the pattern may bias your review process. For example, it’s possible you’ll see the pattern at market tops but fail to recognize it (or a similar pattern) in the middle of a trend when no reversal occurs. Or you may convince yourself that you’d know when to trade the pattern when it was accurate, and know to avoid it in the situations it failed. Hindsight is one thing, but in real-time trading you don’t know the outcome — you can’t see the pattern and the result, together, in advance — and your judgment may fail to provide the same advantage you assumed existed when you did know the outcome. Such circumstances can reduce your confidence and raise your anxiety level — both major obstacles in the path of effective trading. However, once you have precise definitions, a whole new world of developing trading procedures opens to you.

This idea of using precise definitions is really the foundation of the scientific continued on p. 3

www.activetradermag.com • July 2001 • ACTIVE TRADER

FIGURE 1 MAXIMUM FAVORABLE EXCURSION (MFE) At point A, the MACD histogram went positive (on the close) at a price of 1,656.54, triggering a buy. The MACD histogram switched to a short position on the close at point B at 1,673.62, for a 17.07-point profit. The peak price while in the trade was 1,749.29, for an MFE of 92.75 points.

MACD system -1

1,800

Nasdaq 100 Index (NDX), 30-minute Trading range

1,760

MFE

1,720 1,680

B

1,640 1,600

A

1,560

-.04 -8.6 -17.15 3/16/013/19/01 3/20/01 3/21/01 3/22/01 3/23/01 3/26/01 3/27/01 3/28/01 Source: Fibonacci Trader

FIGURE 2 TRENDING PERIOD In addition to the trading range period shown in Figure 1, the test period also included trend periods. During this downtrend, the MACD histogram signaled two good short trades. MACD system 1

1,800

Nasdaq 100 Index (NDX), 30-minute Downtrend

1,750 1,700 1,650 1,600 1,550 1,500 1,450 1,400 1,350 1,300 8.81 1.24 -6.33

3/27/01 3/28/013/29/01 3/30/01 4/2/01 4/3/01 4/4/01 4/5/01 4/6/01

-13.9

Source: Fibonacci Trader

method credited to Sir Francis Bacon. The scientific method requires you to follow certain steps toward understanding and finding a solution to a problem. 3

One reason to follow the steps outlined in the scientific method is to remove any bias the researcher may bring to the situation. We’ll approach the problem of set-

ting profit targets using the steps of the scientific method.

Step 1: State the problem. You can’t solve a problem unless you know what the problem is. Our problem is to determine where to take profits after a trading signal is triggered. Consequently, the solution is twofold: We have to define, first, an entry signal and, second, the targeting technique.

Step 2: Research the problem. Look to other people’s work in the area of entry signals and taking profits. There are many sources for trading signals (which we will mention shortly), but regarding profit-taking, we’ll use John Sweeny’s book, Campaign Trading: Tactics and Strategies to Exploit the Markets and a research technique he calls measuring maximum favorable excursion. Maximum favorable excursion (MFE) is the positive price movement of a trade from beginning to end. After we enter into a trade there will be a range of possible price movement. Some trades may have little, or possibly zero, positive price movement. For example, a long entry executed at the high of the day would have no positive price movement. On the other hand, if the entry occurred at what turns out to be the start of a substantial trend, the positive price movement for this trade will be the best under review. In between these two extremes of maximum favorable excursions lie the outcomes of all of the other trades. For example, if you bought a stock at 20 and it rallied to 30, but your exit technique didn’t trigger an exit until it subsequently dropped to 27, your profit would be seven points but the MFE would be 10 points. Let’s define our entry signals. We will use the difference between the MACD line and its signal line (referred to as the MACD histogram) to indicate trend and trigger long and short positions. (For more on the MACD, see Indicator Insight, p. 88.) The entry signal will be to buy when the MACD histogram turns positive, staying long until the MACD histogram turns negative. The sell-short rule is the opposite: Sell short when the MACD histogram turns negative and stay short until the MACD histogram turns positive. This system is always in the market. Now, on to Step 3.

www.activetradermag.com • July 2001 • ACTIVE TRADER

Step 3: Form a hypothesis or solution to the problem. We will assume there will be positive outcomes from the trading signals and we will measure the MFE for each signal. It may turn out the entry signal concept is flawed, which is valuable information. Most likely, with such a simple approach, the entry rules are a starting point, and by using MFE analysis, you can review the results and repeat the process with the new information. (The importance of testing any trading idea cannot be stressed enough. This research ultimately saves you a considerable amount of money.)

Step 4: Test the hypothesis. To perform this test we will review 30-minute bars of the Nasdaq 100 from Dec. 22, 2000, to April 4, 2001. (This is too short a time period for confidence in the system itself, but more than adequate to demonstrate the analytical concept.) The Nasdaq 100 can be traded using the Nasdaq 100 tracking stock (QQQ) or the Nasdaq 100 futures contact. Figure 1 (opposite page, top) shows a series of trades during March when the Nasdaq 100 was in a trading range; Figure 2 (opposite page, bottom) shows trades during a trending period. At the close of a bar when the MACD histogram crosses into positive territory (a buy signal), the price bars turn green and an up arrow is displayed. (The entire bar is colored green even though this action takes place at the close of the bar.) When the MACD histogram drops into negative territory (a sell signal), the bars are colored red and a down arrow is displayed. For each trade we will measure the profit or loss as well as the MFE. For example, at point A in Figure 1, the MACD histogram went positive on the close at a price of 1,656.54. At point B the MACD histogram signaled a short position on the close at a price of 1,673.62, for a 17.07-point profit. The peak price while in the trade was 1,749.29, for a MFE of 92.75 points. Ideally, we would like to have our initial test period include a trend and some sideways price movement so we see how the strategy performs in different market environments. Figure 3 (top right) is a daily chart showing the period of the historical data base on a daily bar basis. We can see January was a rising trend while

FIGURE 3 DAILY PERSPECTIVE The Nasdaq 100 rallied into late January and then entered a persistent downtrend during February and March. Nasdaq 100 Index (NDX), daily 2,600 Uptrend 2,400

2,200 Downtrend 2,000

1,800

1,600

January 2001 26 2

8

16

February 22

29 1 5

12

March 20 26 1 5

April 12

19

26

1,448.24 140,000

2

Source: Fibonacci Trader

there was a persistent downtrend during February and March.

Figure 4 (bottom right) lists the performance statistics of this trading system over the test period. Figure 5 (p. 48) shows the trade-by-trade summary. This system appears to be quite successful but, again, the test period is too short to draw any reasonable conclusions. However, for our purposes, the first part of our proposed solution (there are positive trade outcomes) has been met. Let’s now add in the MFE analysis for each trade. One way to approach this analysis is to step through each trade on the screen one bar at a time and continued on p. 5

ACTIVE TRADER • July 2001 • www.activetradermag.com

FIGURE 4 PERFORMANCE SUMMARY The system posted a profitable return of 1,897.28 points (not including slippage or commissions). Performance Results for Nasdaq 100 Index 30- D- W System MACD System

From 12/22/2000 14:00 to 4/5/2001 14:30

Gross Profit Gross Loss Net Total Trades Total Winning Trades Total Losing Trades Percent Profitable Largest Winning Trade Largest Losing Trade Average Winning Trade Average Losing Trade Ratio Average Win/Average Loss Average Trade Max. Consecutive Winners Max. Consecutive Profit Max. Consecutive Losers Max. Consecutive Draw Down

2,730.22 -832.94 1,897.28 47.00 24.00 23.00 51.06 266.83 -89.81 113.76 -36.21 3.14 75.81 4.00 909.41 5.00 -253.96

Source: MetaStock Professional

4

FIGURE 5 TRADE-BY-TRADE SUMMARY After four consecutive winners at the beginning of the test period, the system suffered six losing trades in a row. MACD System Date Time Position Price P&L P&L Accum. 12/28/2000 12:00 short 2435.17 0.00 1/3/2001 9:30 long 2,187.07 248.09 248.09 1/4/2001 13:30 short 2,453.9 266.82 514.92 1/8/2001 14:30 long 2,281.54 172.35 687.28 1/12/2001 9:00 short 2,503.66 222.11 909.40 1/12/2001 9:30 long 2,548.94 - 45.28 864.12 1/12/2001 11:00 short 2,513.52 - 35.41 828.70 1/17/2001 8:30 long 2,599.27 - 85.75 742.95 1/17/2001 14:00 short 2,566.45 - 32.82 710.13 1/18/2001 11:30 long 2,621.14 - 54.68 655.44 1/19/2001 11:00 short 2,657.67 36.53 691.97 1/23/2001 10:00 long 2,659.16 - 1.49 690.48 1/24/2001 12:00 short 2,716.47 57.31 747.79 1/26/2001 12:00 long 2,618.14 98.33 846.12 1/30/2001 13:00 short 2,669.74 51.60 897.72 1/31/2001 9:00 long 2,713.19 - 43.44 854.27 1/31/2001 10:30 short 2,685.15 - 28.04 826.23 2/1/2001 14:30 long 2,607.17 77.98 904.21 2/2/2001 9:00 short 2,564.07 - 43.09 861.11 2/5/2001 13:30 long 2,451.03 113.04 974.15 2/7/2001 8:30 short 2,434.82 - 16.20 957.95 2/7/2001 14:30 long 2,409.66 25.16 983.11 2/8/2001 14:00 short 2,364.79 - 44.86 938.24 2/12/2001 9:00 long 2,293.92 70.87 1,009.11 2/13/2001 13:30 short 2,263.73 - 30.18 978.92 2/14/2001 13:00 long 2,284.74 - 21.01 957.91 2/15/2001 14:30 short 2,367.09 82.35 1,040.26 2/21/2001 10:00 long 2,108.95 258.14 1,298.40 2/21/2001 14:30 short 2,058.54 - 50.40 1,247.99 2/22/2001 12:00 long 2,068.31 - 9.77 1,238.22 2/23/2001 9:00 short 1,979.44 - 88.87 1,149.35 2/23/2001 13:30 long 1,986.52 - 7.08 1,142.27 2/27/2001 9:30 short 2,021.37 34.85 1,177.12 3/1/2001 13:30 long 1,877.52 143.85 1,320.97 3/5/2001 8:30 short 1,905.67 28.15 1,349.12 3/6/2001 8:30 long 1995.48 - 89.80 1,259.31 3/6/2001 14:30 short 1,976.31 - 19.16 1,240.14 3/12/2001 13:00 long 1,748.33 227.98 1,468.12 3/15/2001 13:00 short 1,736.44 - 11.89 1,456.23 3/19/2001 9:00 long 1,656.54 79.89 1,536.13 3/20/2001 13:30 short 1,673.62 17.07 1,553.21 3/22/2001 10:30 long 1,616.02 57.60 1,610.81 3/26/2001 11:30 short 1,708.56 92.54 1,703.35 3/27/2001 10:00 long 1,734.15 - 25.59 1,677.76 3/27/2001 13:30 short 1,715.33 - 18.82 1,658.94 3/30/2001 10:30 long 1,554.82 160.51 1,819.45 4/2/2001 12:00 short 1,525.61 - 29.20 1,790.24 4/4/2001 10:00 long 1,418.57 107.04 1,897.28 Last Pos. Value 1,519.09 1,997.80 Source: MetaStock Professional 5

log the information into Excel for further analysis. This may seem like a lot of work — it is — but the returns from your investment of time and energy are significant. You gain a number of insights compared to asking the computer to do the work for you. First, you will feel more comfortable with the trading approach and have more confidence, because in a sense, you experience each trade. You will see the good times and the bad, so you will not feel uneasy when your strategy experiences a predictable drawdown. Second, you will quickly realize if you have a rule that does not make sense, or a market situation for which you don’t know the appropriate action. Finally, you will bring to bear your own intuitive skills for refining your technique. None of this happens when you ask the computer to do the work. However, once we have the data we will use Excel to analyze the results. Figure 6 (opposite page, top) displays the MFE results as a histogram, arranging each trade by order of the size of its MFE. The minimum value was zero, and the maximum was 359.86 points, which happened to be the second trade in the test period. Figure 7 (opposite page, middle) sorts the MFEs of long and short positions. The majority of long signals cluster from 100 and below (with the exception of two large values, which are trades from early January). The MFEs of the short positions tend to steadily increase. Both of these observations make sense, considering the market was in a downtrend more than two thirds of the test period. It appears that these trading signals are a valid approach because of the overall profitability. In addition, the MFE outcomes indicate we can identify a profitable target level for most trades. Now, how should we establish a target? Let’s return to Figure 6, which shows the MFE of all of the trades ordered by size. We can use a target based on whatever we choose from this graph, increasing or decreasing the size of the target based on the likelihood of hitting the target. For example, let’s say we choose 50 points as our target price. This value was exceeded more than 33 times, or 68 percent of the time. Let’s see how we can alter our previous rules using this target.

www.activetradermag.com • July 2001 • ACTIVE TRADER

FIGURE 6 MFE RANKED BY SIZE We will use both target and trend-following exits for each trade. We will take half our profit at a target of 50 points and hold the remainder of the trade until the MACD histogram reverses again. Figure 8 (bottom, right) shows the equity line for the original trend-following positions, along with the equity line using the additional target exit. (We are only interested in the performance of adding the targeting scheme; the additional necessary capital is not an issue here.) Of course, this additional step added more money, but more importantly, notice how the original equity line system peaked at trade 4 and did not surpass this level until trade 19. By comparison, the targeting scheme version passed the previous high at trade 13. Also, the original equity line from trade 19 to 26 was flat, while the targeting scheme version continued to add profits. Most trend-following methods tend to have lengthy periods of flat or negative equity growth, and the target scheme counters this drawback.

Step 5: Drawing conclusions from the testing. Based on this testing we can conclude that the MFE approach is an appropriate method for determining profit targets. You can use the MFE to create targets that suit your risk tolerance by using larger or smaller values depending on how active you want to be. Other MFE measurements may be used for targets, such as percentage price movement or a ratio based on the current average true range. Also remember that other issues must be addressed when designing a system or strategy, such as slippage and commissions, risk and required capital.

This chart shows that the MFEs for the trades in the test ranged from zero to 350-plus points. 400 MFE histogram

350 300 250 200 150 100 50 0

1

4

7

10

13

16

19

22 25 Trades

28

31

34

37

40

43

46

FIGURE 7 MFE SORTED BY SIZE AND POSITION The upper curve represents the short sale positions. The lower curve repre sents the long positions. On average, the long positions are smaller because the market was in a downtrend for the majority of the test period. 400 350 300 250 200 150

Short positions

100

Long positions

50 0

1

3

5

7

9

11

13

15

17

19

21

23

FIGURE 8 EQUITY CURVES The bottom curve shows the performance of the original system. The top curve shows the performance with the addition of a 50-point profit target. The target continues to add profits to the system while the original trend-following technique is in a flat period. 3,400

Granted, this targeting method is based on hindsight. So, the first step would be to test the approach on different (and more) historical data and see if the performance holds up. This is called “out-of-sample” testing, and is a very necessary step if you wish to draw reliable conclusions from your testing. Finally, as with all technical trading methods, past profitable performance does not guarantee future profits, but if you take the time to do this type of work you will gain both experience and develop profitable techniques. Ý

2,900 2,400 Target plus trend-following positions

1,900 1,400

Trend-following positions

900 400 -100

2

ACTIVE TRADER • July 2001 • www.activetradermag.com

4

6

8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48

6

TRADING & Investing

Finding VALUE OPPORTUNITIES Where can you find high-potential stocks in a battered market? Adding technical signals to basic fundamental analysis can allow you to identify value stocks poised to move. BY THOM HARTLE

D

based. Capital flowed to the leaders in the high-tech industry because the growth rates using the aforementioned measurements were so high. The risk, though, was great. If there was any hint of slowdown in the acceleration of a company’s business — not even anything as serious as an actual loss — your position was hammered in a wink of an eye. In the first quarter of 2000, a slowdown engulfed the entire high-tech sector, and these stocks — measured both individually FIGURE 1 S&P BARRA GROWTH INDEX and by the Nasdaq Composite — lost more than 50 percent of their This index represents the stocks within the S&P 500 with price-to-book ratios greater value over the subsequent 12 than the average price-to-book ratio in the S&P 500 index. months. Once seemingly invincible market leaders such as Cisco S&P 500 (Barra Growth), weekly 1000 Systems (CSCO), Sun Micro950 systems (SUNW) and Yahoo (YHOO), among others, plum900 meted. 850 That’s been the headline news. 800 But away from the front page, everything isn’t falling apart. In 750 fact, a new theme appears to be 700 shaping up in the market: under650 valued companies. We’ll explore 600 techniques for identifying undervalued companies and meth550 ods for trading them.

uring the latter part of the 1990s, successful stock traders had one mantra: High tech is the place to be. In reaction to the phenomenal bull market, traders quickly adapted to techniques that measured momentum, be it price, earnings or sales momentum. The goal was to hop on the backs of stocks that showed acceleration of any kind, whether it was price- or fundamental-

500

450 400 350 300 250 1996

1997

1998

1999

Source: MetaStock, Equis International (www.equis.com)

7

2000

2001

Figures 1 through 3 illustrate the changes that have taken place in the market in 2000 and early 2001. Figure 1 (left) is the S&P 500 Barra Growth index and Figure 2 (opposite page) is the S&P 500 Barra Value index.

www.activetradermag.com • August 2001 • ACTIVE TRADER

FIGURE 2 S&P BARRA VALUE INDEX The growth index is a capitalization-weighted index of the common stocks within the S&P 500 index with price-to-book ratios higher than the index average (the book value of a stock is the net worth of the company divided by the number of outstanding shares). The value index is a capitalization-weighted index of the common stocks within the S&P 500 index with price-to-book ratios lower than the index average. Figure 1 shows that growth stocks fell precipitously beginning in the first quarter of 2000, while value stocks, shown in Figure 2, moved to new highs over the same period. Figure 3 (bottom right) provides a clearer picture of the relationships between these two indices. Here we see the growth and value indices using a logarithmic scale, which measures how the indices performed on a percentage basis. You can see that the two tracked in close fashion from 1996 until the middle of 1998, at which point growth stocks took off (A). Then, in 2000, the relative strength comparison traced out a double top and growth stocks fell relative to the value stocks. Whether or not this current trend will continue is difficult to know. However, because it is in place it warrants bringing a value-oriented approach to your trading and investing. The following approach shows how to identify value stocks and how to determine when to commit capital to them.

Traditionally, value is defined by comparing various “fundamentals” to the price of a stock — for example, price earnings (P/E) ratio, book value, sales ratio and so on. A value-oriented technique dictates that investments should only be made in companies whose ratios are at historical low values. The logic is that such a company has fallen out of favor with Wall Street, (as reflected by the low value continued on p. 9

This index represents the stocks within the S&P 500 with price-to-book ratios lower than the average price-to-book ratio in the S&P 500 index. 690 680 670 660 650 640 630 620 610 600 590 580 570 560 550 540 530 520 510 500 490 480 470 460 450 440 430 420 410 400 390 380 370 360 350 340 330 320

S&P 500 (Barra Value), weekly

1996

1997

1998

1999

2000

2001

Source: MetaStock, Equis International (www.equis.com)

FIGURE 3 S&P 500 BARRA GROWTH VS. VALUE INDEX The relative performance of growth and value stocks. The top chart shows a double top formed on a relative strength basis, a bearish sign for growth stocks. Double top

1.60 1.55 1.50 1.45 1.40 1.35 1.30 1.25 1.20 1.15 1.10 1.05 1.00 0.95 0.90

A Growth stocks accelerate

900 800

Growth

700 600 500

Value 400

300

1996

1997

1998

1999

2000

2001

Source: MetaStock, Equis International (www.equis.com)

ACTIVE TRADER • August 2001 • www.activetradermag.com

8

Market timing: ECO

T

he Ergodic Candlestick Oscillator (ECO) is detailed in CSI) and a short-term EMA (generally five days for the CSI). William Blau’s book, Momentum, Direction, and The next step is the calculation of the Candlestick Divergence (1995, John Wiley & Sons). To calculate it, Indicator. The CSI is a ratio of the double-smoothed differtwo other concepts must first be explained: “double smoothing” and CHART 1 GAP-DOWN OPENING the Candlestick Indicator (CSI). Even though RNWK opened on a gap-down, the CSI continued to rise and the Blau uses exponential moving MACD remained flat. averages (EMAs) extensively in his calculations. In an effort to create smooth signals while minimizing Real Networks (RNWK), daily 8.16 price lag, Blau used a double8.00 smoothing technique — that is, he applied an EMA to the raw price 7.48 data, and then performed a second 7.32 smoothing of the first EMA using an A 7.16 additional EMA. Blau uses the standard formula for an EMA, which takes CSI rises 7.00 Ergodic Candlestick Oscillator a price observation, such as the 18.36 close, and multiplies it by a constant, called the alpha (a), which, in 5.7 the following formula, represents 6.96 the lookback period used for a simple -19.61 moving average: a = 2/(n+1) where n = the lookback period for a simple moving average

MACD is flat

MACD

-.11 2/22/2001

In other words, the exponential smoothing constant (a) to approximate a 20-day simple moving average would be .095 (2/[n+1]). The adjusted closing price using 1alpha is added to yesterday’s EMA value, which has been multiplied by alpha. Here is the formula for the EMA:

.05 -.03

2/23/2001

2/26/2001

-.18

Source: Fibonacci Trader (www.fibonaccitrader.com)

CHART 2 PENETRATING THE SIGNAL LINE The ECO crossing above and below the signal line generates buy and sell signals, respectively. In this case, the ECO signal occurred eight bars before the MACD signal. Real Networks (RNWK), daily

8.16 8.00

EMA = (1-a)P + a(EMA (t-1)) where p = price EMA (t-1) = yesterday’s EMA The double-smoothed closing price series (EMA Double) uses the EMA of the closing price: EMA Double = (1-a) EMA + a(EMA Double(t-1)) where EMA Double(t-1) = yesterday’s EMA value

7.48 7.32 7.16 7.-00

Ergodic Candlestick Oscillator

18.36 5.7 6.96

A

ECO crosses above the signal line

-19.61

MACD

.05 -.03 -.11

Blau uses the notation EMA(EMA(P,r),s) to indicate a longterm EMA (generally 26 days for the 9

B 2/22/2001

MACD crosses above the signal line 2/23/2001

2/26/2001

-.18

Source: Fibonacci Trader (www.fibonaccitrader.com)

www.activetradermag.com • August 2001 • ACTIVE TRADER

ratios), but that its management team will respond to pressure from shareholders and take steps to improve earnings. The price of the stock will ultimately rise as management improves its business practices. There are a number of value-oriented techniques; the one we will look at uses historical dividend yields as a basis for value. Value Trend Analysis is a company that publishes Investment Quality Trends (IQ Trends), a value-oriented appraisal of stocks. It uses individual historical dividend yield analysis of each stock from the company’s approved list of 350 “Blue Chips” to determine when a stock is undervalued (i.e., has a historical high dividend yield), in a rising trend, overvalued or in a declining trend. IQ Trends uses the following requirements to qualify stocks as blue chips: • The dividend has been raised five times in the last 12 years. • The company carries a Standard and Poor’s Quality ranking of “A.” • The company has at least 5 million shares outstanding. • At least 80 institutional investors hold the stock. • There have been at least 25 years of uninterrupted dividends.

ence between the open and close of each price bar and a double-smoothed difference between each bar’s high and low: CSI = 100(Ema(Ema (close-open,r),s)/ (Ema(Ema (high-low,r),s)

The CSI measures momentum based on how each bar closes relative to the range for the bar. Closes at the upper end of each bar’s range and above the opening price indicate strength and positive CSI raw values. Closes at the lower end of each bar and below the opening price indicate weakness. A trend in either direction will have persistent readings. The double-smoothing technique will create a smooth indicator line that rises if the market is in an uptrend and falls if prices are in a downtrend. Intraday traders will value this indicator because the continued on p. 11 calculation does not reference the previous bars’ closes. Consequently, any FIGURE 4 IQ TRENDS CHART large price gap — such as a gap open or gap close — will not cause this indicator IQ Trends measures an individual company’s undervalued and overvalued to fluctuate dramatically. levels based on historical yields. For example, Chart 1 is a 15-minute chart of Real Networks (RNWK). The upper histogram chart is a 26-period CSI and the lower histogram chart is the 1226-period moving average convergencedivergence (MACD) indicator (see Indicator Insight, Active Trader, July 2001, p. 88). Notice that at point A, there is a gap-down opening, but the MACD, which looks at the market on a close-to-close basis, remains virtually flat. On the other hand, the CSI continues to rise from the previous day’s reading because the majority of the 15minute bars are closing near their respective highs, indicating strength. The ECO is a plot of two lines. The primary is the ECO, which uses the CSI with an additional smoothing by a fiveperiod EMA, and the addition of a “signal line,” which is a five-period moving average of the ECO (similar to the default nine-period moving average signal line of the MACD). Basic buy and sell signals occur when the ECO crosses above and below its signal line, respectively. Chart 2 compares the ECO (upper histogram) and the MACD (lower histogram). As a shortterm bottom was forming, the ECO crossed above its signal line eight bars before the MACD.

Mid January 2001

Wachovia Banc Corp. (WB) Regional bank throughout N & S Carolina and Georgia

Dividend

Price

6.5

95

6.0

85

5.5 5.0

75 70

Overvalued yield line

4.5

65 60

4.0

55

Undervalued yield line

3.5

50 46

3.0

42 2.5

38

2.0

30 28 26

34

Earnings trend line

24 1.5

22

Dividend trend line

20 18 16 15 14 13

1.0 .90

12 11

.80 .70

24

24 16

16

8

8

1989

1990

1991

1992

1993

1994

1995

1996

Ern.1.94 2.13 2.14 2.51 2.83 3.13 3.50 3.81 Div. 0.70 0.82 0.92 1.00 1.11 1.23 1.38 1.52 Source: Investment Quality Trends (www.iqtrends.com)

ACTIVE TRADER • August 2001 • www.activetradermag.com

1997

3.96 1.68

1998

4.45 1.86

1999

4.97 2.06

2000

4.60 2.28

10

FIGURE 5 BANK OF AMERICA Bank of America has traded into undervalued territory a number of times, offering trade opportunities at points A, B and D (confirmed by the ECO crossovers). 68.00

Bank of America (BAC), weekly

64.00 60.00 56.00

B1

A1

52.00 48.00

D1

44.00

Undervalued price=45

40.00

C

36.00 32.00

Ergodic candlestick oscillator

3

B

-4.68

D

A 7/5/99

10/4/99

1/3/00

4/3/00

7/3/00

10/2/00

-12.35 1/1/01

-20.03

Source: Fibonacci Trader (www.fibonaccitrader.com)

S&P 500/Barra Growth and S&P 500/Barra Value Indices

I

is an excerpt from the newsletter that illustrates the price chart, dividend yield bands and other attributes of the company, including earnings trend. These companies are certainly less volatile than the typical Nasdaq stock. While the list of blue chip stocks may not be the most exciting, they do offer opportunities for traders and investors alike. The technique to be discussed may be primarily of interest to investors or longer-term traders, but since shorter-term traders also improve their chances of success by identifying stocks and sectors most likely to move, it will also provide valuable information for them. Consider this technique as one of a number of trading strategies you could employ. In other words, diversify not only into different markets, but among different techniques as well.

As our first criterion, we will begin with a list of undervalued stocks — those that have fallen in price and reached their high historical dividend yield. However, we are faced with one problem: By putting capital into undervalued companies, we risk the possibility that the stock price may languish, trading sideways for a considerable amount of time. However, use of technical analysis allows you to spot situations that indicate price action is beginning to move into an uptrend. A good tool for this is called the Ergodic Candlestick Oscillator (ECO), developed by William Blau. In the charts that follow, we will plot the ECO as a histogram and the signal line as a dot. For more information, see “Market timing: ECO,” p. 9. Our plan is to look for stocks from IQ Trends’ undervalued list and then use the ECO to determine which ones are in an uptrend. The trend turns up when the ECO histogram is in negative territory and rises to the point that the signal line is not within the histogram. Our work will be with weekly charts.

n 1992, Standard and Poor’s (S&P) and Barra worked in partnership to produce growth and value subsets of S&P’s equity indices. The S&P 500/Barra Growth and S&P500/Barra Value Indices separate fast-growing companies from slower growing, or undervalued, companies, based upon a price-to-book value calculation (the price of the stock divided by the “book value,” or net worth of the company). The price-to-book ratio captures one of the fundamental differences between companies classified as value companies or growth companies: Growth companies tend to have higher price-to-book ratios than value companies. Also, price-to-book ratios tend to be more stable over time compared to alternative measures such as the price-toearnings ratio, historical earnings growth rates or return on equity. Consequently, the growth and value indices experience relatively low turnover. Companies in the growth index have higher market caps, on average, than those in the value index. As a result, there are many more companies in the value index than the growth index. As of this writing, the Growth Index had 125 companies while the Value Index listed 375 companies. More information can be found at the Standard & Poor’s Web site (www.spglobal.com or www.spglobal.com/indexmain500style_data.html) and Barra’s Web site (www.barra.com). • The earnings have improved in at least seven of the last 12 years. In mid-January 2001, IQ Trends listed 30 companies as undervalued, 89 in rising trends, 116 overvalued and 114 in declining trends. Many of the companies listed have been around most of the past century and are household names, such as JP Morgan Chase and Eastman Kodak. Figure 4 (p. 97) 11

www.activetradermag.com • August 2001 • ACTIVE TRADER

FIGURE 6 DILLARDS INC. This company reached undervalued territory for a three-month period before an uptrend began, as signaled by the ECO (point A). Dillards Inc. (DDS), weekly

20.00 18.00 16.00 14.00

A1

Undervalued price=11

12.00 10.00 8.00

Ergodic Candlestick Oscillator

-5.89 -15.71

A 1/3/00

2/7/00 3/6/00 4/3/00 5/1/00

6/5/00 7/3/00

8/7/00 9/4/00 10/2/00 11/6/00 12/4/00 1/1/01 2/5/01

-25.54

Source: Fibonacci Trader (www.fibonaccitrader.com)

FIGURE 7 HJ HEINZ Heinz traded into undervalued territory twice last year. Each buy signal was followed by a greater than 10-point gain. H.J. Heinz (HNZ), weekly 52.00 48.00 44.00 40.00

B1 Undervalued price=35

A1

36.00 32.00 28.00

Ergodic Candlestick Oscillator

4.74 -5.82

B

first quarter of 2000, BAC traded below 45. At point A, the ECO histogram rose above the signal line. On this bar, BAC closed at 50. BAC then moved above 60, a gain of more than 20 percent. In late June 2000, BAC again dropped into undervalued territory, and the ECO flashed a buy signal (point B) with a closing price of 52.50. The stock then advanced to 57.63 for a 5-point gain. At point C, BAC again dropped to below the undervalued level. However, notice that during the short two-week rally, the ECO never gave a buy signal. BAC again fell back into undervalued territory at point D, and the ECO gave a buy signal at a price of 46.13. The stock rallied nearly 10 points after that. In regard to taking profits, you can use a trailing stop or a hard money target, or take partial profits at a combination of the two. Figure 6 (top left) is Dillards Inc. (DDS). The undervalued price for DDS is 11, or a yield of 1.5 percent. DDS reached this price in October 2000, and the ECO gave a buy signal that same month (point A) at a price of 10.88. In mid-May 2001, the stock traded above 18. Our final example, Figure 7 (bottom left), is HJ Heinz (HNZ). The undervalued price is 35, or a yield of 4.5 percent. HNZ reached 35 twice in 2000. The first time, (point A) was in the first quarter. The ECO gave a buy signal at 33.59, and the stock advanced to 45.94. The second signal came in September 2000. The ECO flashed a new uptrend at a price of 38.94. In May 2001, the stock traded as high as 48.

-16.37

A 1/4/99

4/5/99

7/5/99

10/4/99

1/3/00

4/3/00

7/3/00

Source: Fibonacci Trader (www.fibonaccitrader.com)

Figure 5 (opposite page) shows Bank of America (BAC). According to the January IQ Trend, BAC was undervalued at a price of 45 (giving it a dividend yield of 5 percent). During the ACTIVE TRADER • August 2001 • www.activetradermag.com

Will the price/earnings ratio compression continue in the Nasdaq stocks? Will value stocks be the market for this decade? No one knows, but broadening your methods to position yourself for whatever happens is a good step to take. That way, you can take advantage of the current theme driving the market.Ý

10/2/00

1/1/01

-26.93

12

KNOW THY MARKET :

Gauging typical price behavior Regardless of what kind of trader you are or what approach you use, knowing the typical price behavior for the markets you trade is essential. Here’s how to do it.

BY THOM HARTLE

W

a spreadsheet such as Excel, can be applied to any market or hen it comes to the price behavior of a parindividual stock you trade. ticular stock or market, many traders think of broad concepts like a tendenFIGURE 1 GAUGING PRICE ACTION cy to trend, or relatively high or low volatility compared to other markets. From March 30 to mid-June, the QQQs displayed a wide range of price behav While such characteristics are useful ior: an extended uptrend, short-term uptrends, a sideways trading range and for generalizing market behavior, more short-term downtrends. specific, statistical measures of price Nasdaq 100 Tracking Stock (QQQ), daily action are better for actual trading, especially for short-term traders who are 50.00 more dependent on the quality of their entries and exits than long-term traders. 47.50 The simplest statistics can provide a great deal of insight into a stock’s behavior. For instance, knowing the average 45.00 difference between the open and low for days the market closes up would be use42.50 ful for improving your trade entries and stop placement. This is just one example of the kind of information that can be 40.00 gleaned from analyzing price action barby-bar. 37.50 We will look at some unique ways to observe market behavior and then show how to use this information in your trad35.00 ing. First, we’ll walk through some simApril May June ple observations of market behavior 2 9 16 23 1 7 14 21 29 1 11 using the QQQs, the exchange-traded fund that tracks the Nasdaq 100 index. Source: CQGNet The same analysis, which can be done in 13

www.activetradermag.com • October 2001 • ACTIVE TRADER

TRADING Strategies

FIGURE 2 DAILY RANGE

The principle price behavior characteristics we’ll look at are the daily range, the close-to-close range and the differences between days that close up vs. those that close down. For clarity, we will start by analyzing small amounts of data and then expand our analysis.

A histogram of the daily ranges of the QQQs for the period in Figure 1 shows the typical daily range is approximately $2. The blue line is a three-period moving average of the daily ranges and the red line is a 10-period moving average. Points 9 8 7

The first price behavior characteristic to analyze is the typical daily range. Figure 1 (opposite page) shows a daily chart of the QQQs from March 30 to the middle of June, a period that encompassed up, down and sideways price movement. Figure 2 (right, top) shows the daily range (high minus low) for each bar in the period in Figure 1. The blue line is a three-period moving average (MA) of the daily ranges and the red line is a 10-period MAof the ranges. Both MAs reveal the typical daily range is approximately $2, the jump at bar 13 notwithstanding.

The second characteristic is the difference between closing prices on a day-to-day basis. Figure 3 (right, bottom) shows the absolute values of close-to-close price changes over the

The simplest of statistics can provide a great deal of insight into a stock’s behavior.

6 5 4 3 2 1 0 Price bars Source: Excel

FIGURE 3 CLOSE-TO-CLOSE CHANGES The absolute value between closing prices indicates the closing differences tend to be between $1 and $1.50, except for the earlier observations. The blue line is the three-period moving average of the bar-to-bar closing price differences and the red line is the 10-period moving average. Points 5.0 4.5 4.0 3.5 3.0 2.5

same period. As would normally be the case, the differences in closing prices are, on average, less than the daily ranges (and the same volatility spike occurs at bar 13). As in Figure 2, the blue line is a three-period MA and the red line is the 10-period MA. Here, the averages tend to be between $1 and $1.50, except for the early observations in the example. To delve further into this aspect of the QQQs’ price continued on p. 15 ACTIVE TRADER • October 2001 • www.activetradermag.com

2.0 1.5 1.0 .5 0 Price bars Source: Excel

14

FIGURE 4 DAILY BARS IN TERMS OF OPENING PRICE behavior, we’ll display this data in a forIn this chart the daily bars are adjusted so the opening price is zero. The high of mat that makes it easier to see how the each bar represents the difference between the high and the open; the low of the high, low and close relate to the each bar represents the difference between the open and the low; and the hash open. Figure 4 (right) shows each of the mark on each bar represents the difference between the close and the open. daily open-high-low-close bars adjusted Points so the opening price is zero. The high of 8.0 each bar represents the difference 7.5 between the high and the open; the low 7.0 6.5 of each bar is the difference between the 6.0 open and the low, and the dash on each 5.5 5.0 bar is the difference between the close 4.5 4.0 and the open. 3.5 The next step is to create two versions 3.0 2.5 of this chart to analyze the difference 2.0 between bars that closed up from the 1.5 1.0 previous close and those that closed .5 down from the previous close. Figure 5 0 -.5 (below) shows only bars that closed up -1.0 from the previous day’s close. Figure 6 -1.5 -2.0 (p. 62) shows those bars that closed -2.5 down from the previous day’s close. -3.0 -3.5 Figure 5 reveals that, of days that closed higher than the previous day, Price bars approximately one-third of the bars’ Source: Excel lows were less than 50 cents below the open, one-third were between 50 cents closed down for the day, but above the opening price — a price and $1 below the open, and one-third were between $1 and $1.50 below the open. Interestingly, a number of the bars from pattern often referred to as a reversal day. These charts reflect a bias for the low or the high depending the final third closed below the open but made highs that were on if the market closes up or down for the day. On up-closing approximately 50 cents above the open for the day. Figure 6 shows when the market closed down, the highs days, the majority of the daily ranges are above the opening tended to range between 50 cents and $1 above the open. The price (with the highs often reaching $2 or more above the openbar with the highest high (nearly $2 above the opening price) ing), while the lows are often between 50 cents and $1 below the open. The opposite is true for downclosing days. FIGURE 5 CHARACTERISTICS OF UP-CLOSING DAYS Only the bars from Figure 4 that closed up from the previous day’s close are shown here. Approximately a third of the bars had lows near 50 cents below the open, a third were between 50 cents and $1 below the open, and a third were between $1 and $1.50 below the open. Points 3.5 3.0 2.5 2.0 1.5 1.0 .5 0 -.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5

$7.28

Price bars Source: Excel

15

Now we’ll expand this kind of simple statistical analysis to cover the period from June 22, 1999, to June 13, 2001 (500 days). During this period, the market closed up 254 days, closed down 238 days and closed unchanged eight days. Figure 7 (p. 62) sorts the daily ranges in 50-cent increments. (The 50-cent column shows the number of days with ranges up to and including 50 cents and so on.) There were zero days with a daily range of 50 cents or less; 13 days with ranges of 51 cents to $1; 63 days with ranges of $1.01 to $1.50; and 72 days with ranges of $1.51 to $2. The daily range was greater than $10 just seven days. The typical daily range was around $2, similar to the results for the shorter period examined in Figure 2. Approaching the data from the opposite direction provides another perspeccontinued on p. 16

www.activetradermag.com • October 2001 • ACTIVE TRADER

FIGURE 6 CHARACTERISTICS OF DOWN-CLOSING DAYS with a difference of up to +/-50 cents; 92 days closed with a difference between +/-51 cents and +/-$1; 66 closed with a difference between +/-$1.01 and +/$1.50; and 54 closed with a difference between +/-$1.51 and +/-$2. Only 182, or 36.4 percent, of the 500 days the QQQs closed by more than +/$2 from the previous close. The data indicates that although 70 percent of the time the QQQs have a daily range greater than $2, only 36 percent of the time will they close more than $2 (higher or lower) from the previous day’s close.

On days the market closed lower than the previous close, the highs tended to range between 50 cents and $1 above the open. The bar with the highest high (nearly $2 above the opening price) closed above the opening price despite closing lower than the previous close. Points 3.5 3.0 2.5 2.0 1.5 1.0 .5 0 -.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5 Price bars Source: Excel

tive. For example, out of the 500 days, how many days did the QQQs have a range greater than $2? It turns out that there were 352, or 70.4 percent of the total days. Figure 8 (below, right) is a similar breakdown of the typical difference in closing prices, expressed as absolute values. Eight days were unchanged from the previous close; 98 days closed

As noted, 254 of the 500 days closed higher than the previous day. Figure 9 (p. 64) shows that for these days (using absolute values for the difference between the open and the low) the opening price was equal to the low of the day five times; the difference between the open and the low was 50 cents or less 77 times; and the difference between the open and the low was 51 cents to $1 73 times, which means the market was down as much as 51 cents to $1 before reversing to close up on the day. On only 32 days, or 12.5 percent of the time, did the market fall by more than $2 and still close up for the day. Of the 238 days the market closed down, the open and the continued on p. 17

FIGURE 7 SORTING THE DAILY RANGES There were zero days with a daily range of 50 cents or less; 13 days with ranges greater than 50 cents up to and includ ing $1; 63 occurrences with ranges greater than $1 up to and including $1.50; and 72 days where the daily range was greater than $1.50 up to and including $2. The daily range was greater than $2 approximately 70 percent of the time. Price bars 80

72

70

69

98

100

55 57

92

80

50

36 38

40 30

66 54 52

60 22 20 19

20 10

There were eight unchanged closing prices; 98 that closed between unchanged and +/-50 cents; 92 that closed greater than 50 cents and up to $1; 66 that closed greater than $1 and up to $1.50, and 54 that closed greater than $1.50 and up to $2. Price bars 120

63

60

FIGURE 8 SORTING THE CLOSE-TO-CLOSE CHANGES

13

8 5 7 3 5

0 0

0

32

40 0 1 0

7

20

8

16

15

10

5 5 7 4 1 2 0 1 1 1

0 Range

Range Source: Excel

24 22

Source: Excel

www.activetradermag.com • October 2001 • ACTIVE TRADER

high were the same only 10 times (see Figure 10, below, right). The market reached a high of between one cent to 50 cents before turning down 84 times, and was up between 51 cents to $1 65 times before reversing. Figures 9 and 10 reveal there were some volatile days in this period, in that five times the QQQs were down more than $4.50 and still closed up, and three times were up more than $4.50 and then closed down.

FIGURE 9 DAYS THE MARKET CLOSED UP Analyzing the absolute values of the differences between the open and the low for days the market closed higher reveals that only five times was the opening price equal to the low, and 77 times the difference between the open and the low was 50 cents or less. The market recovered from being down between 51 cents and $1 before reversing to close up for the day 73 times. Price bars 90

These price behavior characteristics provide practical trading guidelines for systematic and discretionary traders alike — regardless of other analytical approaches they use. For example, if you trade intraday bars and came into the trading day with a trade that was up $2 for the day, you should consider taking some partial profits because although the QQQs exceed a $2 range 70 percent of the time, they close +/-$2 from the previous close only 36 percent of the time. As a result, the statistics suggest the market is likely to turn against this position by the close. Or, perhaps your analysis indicates the QQQs have a good chance to rally, but the market starts the day with an early sell-off, trading down from the opening price. The statistics from Figure 9 (which showed the QQQs were down as much as 51 cents to $1 before reversing to close up on the day 73 times) suggest opportunity is there when the market

80

77

73

70 60

50

50 40 30 20 10

17

13

5

10 2

3

2

0

0

1

1

0 Range Source: Excel

FIGURE 10 DAYS THE MARKET CLOSED DOWN

To understand any market, you must measure and classify its behavior in terms of probabilities.

On days the market closed down, the open was equal to the high only 10 times. The market turned down after reaching a high between one cent to 50 cents 84 times. The market was up between 51 cents and $1 65 times before reversing. Price bars 100 90

84

80

65

70 60

is down $1. If you are developing a short-term systematic approach based upon indicators, you can substitute a hard-money stop based on typical behavior of the market instead of waiting for an indicator to give a signal at the close. For example, when reviewing your test results you might uncover that if your system was long and the indicator signals a reversal point that causes losses greater than $3 at the close, you could substitute a hard-money exit rule based on the statistics that show the market rarely recovers after it has moved a certain amount intraday. In addition, knowing the market’s typical behavior can help you better decide how much capital to risk on any one trade.

In his book Trading in the Zone: Master the Market with Confidence, Discipline and a Winning Attitude, trader and author Mark Douglas writes, “The best traders treat trading like a numbers game, similar to the way in which casinos and professional gamblers approach gambling.” 17

50

38

40 30

18

20 10

9

10

4

3

1

3

0

1

0

1

0

1

0 Range Source: Excel

To understand any market, you must measure and classify its behavior in terms of probabilities. You can combine these statistics with other analytical techniques and build sound trading methods based on concrete price behavior characteristics. This kind of analysis reveals each market has typical behavior patterns, as well as the potential to — on any given day — trade outside of its typical pattern. That is a fact of life in trading, but by using simple statistics, you’ll be better equipped to trade effectively. Ý www.activetradermag.com • October 2001 • ACTIVE TRADER

TRADING Strategies

Fundamentally TECHNICAL TRADING Technical and fundamental analysis don’t have to be mutually exclusive. This trading approach finds stocks with top fundamentals and buys them in uptrends when they pull back.

BY THOM HARTLE

W

ith more than 10,000 stocks to choose from, traders need to ensure they are in the ones that are moving. No one can afford to sit in markets that are going nowhere. Money goes where opportunities lie, and traders and investors often define opportunity and commit capital based on either technical conditions, such as high price momentum, or fundamental characteristics, such as strong earnings growth. However, there’s no reason fundamentals and technicals cannot complement each other. In fact, you can improve your chances of success by focusing on stocks with both good technical and fundamental characteristics. After all, a company’s ability to deliver persistent positive business performance should translate into a chart with an upward, zigzagging price pattern — perfect for the nimble trader. One easy place to get a list of stocks with strong technical and fundamental 18

characteristics is Investor’s Business Daily (IBD), a newspaper that publishes a weekly list of stocks with top fundamentals. While IBD does not provide the precise criteria of the screening process used to identify these stocks, they rank high in IBD’s SmartSelect Ratings.

Get SmartSelect All IBD screens and ratings are based upon a proprietary stock database. For example, its relative strength ratings compare an individual stock’s price performance to the IBD stock database, not to the S&P 500 or a particular sector, as is the case with other services. Here is a brief explanation of the IBD rankings, known as the SmartSelect Ratings: SmartSelect Composite Rating: Combines all five IBD SmartSelect Ratings.

Of the five, the earnings per share rating and the relative strength rating receive the most weight. Earnings Per Share (EPS) Rating: Compares the last two quarters and the last three to five years of earnings growth and stability to that of all other companies. A 90 rating indicates that a company’s earnings growth outperformed 90 percent of all other companies in the database. Relative Price Strength (RS) Rating: A stock’s relative price change in the last 12 months vs. all other stocks. Industry Group Relative Price Strength Rating: Compares a stock’s industry price performance in the last six months to 196 other industries. Top industries rate A+, the worst rate E. Sales + Profit Margins + ROE Rating:A

www.activetradermag.com • July 2002 • ACTIVE TRADER

Money goes where opportunities lie, and traders and investors often define opportunity and commit capital based on either technical conditions, such as high price momentum, or fundamental characteristics, such as strong earnings growth. company’s recent sales growth, profit margin and return on equity (ROE) are combined and graded from A to E. Accumulation-Distribution Rating: A price and volume formula determines if a stock is under accumulation (buying) or distribution (selling) in the last 13 weeks. A grade of A indicates heavy buying and a grade of E reflects heavy selling. Each week IBD singles out approximately 20 to 30 stocks with top fundamentals. These stocks are highlighted in yellow in the NYSE and Nasdaq Main Tables. They provide a starting point for identifying solid trading opportunities. The next step is to use specific technical criteria to narrow the list further and ultimately signal trades. The strategy that will be outlined in the following sections will focus on stocks with strong fundamentals, and will operate exclusively from the long side of the market.

Blending in the trend: Chaikin Money Flow IBD performs its screening of top fundamental stocks on a weekly basis. This means it is possible for a stock to switch from uptrend to downtrend based on some event that won’t be picked up by this screening process. (Later, we’ll look at an example of a company that stayed on the top fundamental stocks list for two weeks despite losing almost 30 percent of its value.) Accordingly, it is necessary to consult a technical trend indicator to identify those stocks that are in uptrends. Chaikin’s Money Flow (CMF) will be used to determine the trend for the trading approach we will outline. The CMF is a ratio of weighted volume relative to total volume over a 21-day period. The numerator is the 21-day sum of

each day’s volume weighted by the closing price relative to the day’s range. The denominator is the total volume over the 21-day period. The CMF formula (in MetaStock language) is: CMF = sum((((C-L)-(H-L)) / (H-L)) * V, 21) / sum(V, 21) where H = daily high L = daily low C = daily close V = volume (Traders using eSignal 7.0 can find the custom formula for the CMF at www.activetradermag.com/code.htm.) Positive CMF values indicate the stock is closing near the upper end of its daily range on higher volume, a sign of persistent buying. Negative CMF readings reflect the opposite. As long as the CMF is positive, the market is considered to be in an uptrend. The advantage of this indicator is its focus on volume relative to how the market closes each day. A stock could be down on the day because of selling pressure throughout the broader market, but strong stocks should nevertheless tend to close near their highs despite overall market weakness. At this point we have created a list of fundamentally strong stocks and chosen a tool that defines when they are in uptrends. Now we must decide the best way to enter trades.

Buying low and selling high Today’s market requires a trader to buy low and sell high, which is very different from a few years ago when a trader could buy high and sell higher. As a

ACTIVE TRADER • July 2002 • www.activetradermag.com

result, traders need an indicator that identifies relative low and high points in a market. Bollinger Bands fill this role in the strategy. Bollinger Bands are price envelopes consisting of lines plotted two standard deviations above and below a moving average (MA), typically a 20-period MA. Most of a market’s fluctuations will fall between the bands, so when price reaches or exceeds one of the bands, the market, by definition, is at a relatively high or low level. (For more information on Bollinger Bands, see the Active Trader Interview with John Bollinger in the January 2001 issue.) For example, when a market is at the lower Bollinger Band, it is nearing an extreme downside level relative to its recent price history. If price is at the upper Bollinger Band, it is reaching an extreme upside level based on recent price history. An important caveat is that a simple tag of the upper or lower band does not guarantee price will reverse. A strongly uptrending stock will persistently tag the upper band, while a stock in a strong downtrend will repeatedly hit the lower band. In this case, the Bollinger Bands will be set to a lookback period of 10 days instead of the conventional 20 days.

Trade rules The strategy is designed to go long on short-term countertrend moves that punctuate the longer-term uptrend. The rules for the strategy are: 1. Identify those IBD top fundamental stocks that also have positive CMF readings. These stocks also must be trading above $20. 2. Wait for price to tag the lower Bollinger Band. 3. Go long if the stock trades 5 cents above the high of the daily bar that hit the lower Bollinger band. If price does not trade 5 cents above the high of the tag bar, then go long 5 cents above the high of the next bar. 4. Place a stop loss 5 cents below the low of the entry bar. 5. Take profits if the stock moves one dollar in your favor. continued on p. 20 19

FIGURE 1 CAPTURING QUICK PROFITS The stock tagged the lower Bollinger Band on Feb. 7 while the CMF was positive. A long trade was entered on Feb. 8 when the stock moved 5 cents above the Feb. 7 high. The price target was hit the next day. Later in the month another setup formed and the entry and exit occurred on the same day. Alliance Gaming Corp (ALLY), daily

Price

35.00

32.50 Sell

Sell

30.00 Buy

Buy

27.50 0.25

Chaikin Money Flow

0 28

4 February

11

19

25

4 March

Source: eSignal 7.0

If the CMF is not positive on the bar that tagged the lower Bollinger Band but turns positive on the next bar, use the high of the second bar. (If the CMF is

negative on the first bar that tags the lower Bollinger Band, we cannot use the high of that bar; if the CMF is negative on the bar following the tag bar, we still can-

FIGURE 2 DELAYED ENTRY On Feb. 5 the stock hit the lower band, but no trade was entered because the CMF was negative. The next day the CMF turned positive, but price did not trade above the previous high, again denying entry. On Feb. 8 the stock tagged the lower band but the CMF was negative. However, the next day (Feb. 12) the CMF turned positive and a long trade was triggered when the stock exceeded the Feb. 11 high by 5 cents. 70.00

Nvidia Corp (NVDA), daily

Price

Sell

65.00 Buy

60.00 No entry

55.00 50.00

Chaikin Money Flow

0

28

Source: eSignal 7.0

20

4 February

11

19

25

4 March

not go long.) Occasionally the CMF will momentarily edge into negative territory when the price is at a lower extreme. Do not enter the market after the second bar. Stocks also must be trading above $20 because the one-dollar move required for the profit target is less likely to occur in lower-priced stocks.

Trade examples The following trades are taken from some of the 17 top fundamental Nasdaq stocks highlighted by IBD on Feb. 2, 2002. When trading this strategy, you can use the list for trading during the month, checking each week to make sure your stocks remain on the list. Figure 1 (top left) shows Alliance Gaming Corp (ALLY), one of the top fundamental stocks as of Feb. 1, 2002. The entry criteria were met on Feb. 8: The previous bar had tagged the lower Bollinger Band, the CMF was positive, and the stock traded above the high of the tag bar ($29.85). On Feb. 11, the stock reached a high of $31.44, exceeding the one-dollar profit target. Then on Feb. 20, the stock touched the lower Bollinger Band a second time and the CMF was positive. The next day we went long 5 cents above the previous day’s high of $29.67. The stock rallied to $30.95 the same day. Figure 2 (bottom left) shows Nvidia Corp. (NVDA). In early February, the stock tagged the lower band but the CMF was negative at the time. The CMF turned positive on the next bar, but the stock did not trade above the high of this bar; no trade was entered. On Feb. 8 the stock tagged the lower band once more, but the CMF had turned negative again; no trade. The next day the CMF turned positive and we went long on Feb. 12 when the stock pushed above the Feb. 11 high of 61.00 by 5 cents. The stock reached 63.35 the same day, fulfilling the price target. Later in the month, the CMF was negative when the stock tagged the lower band (the stock was in a visible downtrend at this point) and no trade was entered. In Figure 3 (opposite page, top), price tagged the lower band on Feb. 7, but did not trade above the high of the tag bar on Feb. 8. As a result, the Feb. 8 high (57.75), plus 5 cents, became the reference point to enter a trade on Feb. 11. We went long on Feb. 11, and the stock hit 59.96 that day (more than a $2 move),

www.activetradermag.com • July 2002 • ACTIVE TRADER

fulfilling the profit target. Also notice that in this case, the low was equal to the previous day’s low, so the position was not stopped out. On Feb. 20 price tagged the lower band but the market fell for two more days. Another tag occurred on Feb. 22, and the high of the day was 52.50. On Feb. 25 the stock rallied above the trigger level, and on Feb. 26 it made a high of 53.57. (If you experienced slippage on your entry, you may have had to wait for the full one-dollar profit.) This example shows why you should take the profit at the target level, despite your entry price: The same day the stock dropped below the entry bar’s low of 51.50, which would have resulted in a loss of more than $1.

tunities for nimble traders. You simply need a solid set of procedures for defining entry, risk and profit-taking. The set described here that incorporates the CMF and Bollinger Bands can be

a departure point for further testing, and can be modified to suit your own personal risk tolerance and profit goals.Ý

FIGURE 3 TAKE PROFITS WHEN YOU CAN The trade on Feb. 25 illustrates that, regardless of your entry price, it’s wise to exit at the $1 profit target. On the same day the trade was entered, price eventually dropped below the bar’s low of $51.50, which would have resulted in a loss larger than $1. Price

Panera Bread Co. (PNRA), daily 65.00 Sell

60.00

Buy Sell Buy

55.00

The rest of the story Earlier we mentioned that just because a stock is on the top fundamentals list doesn’t mean it’s in an uptrend at the time. This final example is from January 2002, and it shows how market participants can turn on a stock with a vengeance. On Jan. 2, one company on the top fundamental list was Dynacq International (DYII). Figure 4 (bottom right) shows the stock steadily climbed from a low of 11.00 in September 2001 to 29.25 on Jan. 7; its PE pushed above 35. In early January, IBD ratings for DYII were: SmartSelect Composite Rating: 98 Earnings Per Share Rating: 99 Relative Price Strength Rating: 95 Industry Group Relative Price Strength Rating: B+ Sales + Profit Margins + ROE Rating: A Accumulation/Distribution Rating: B However, two days after announcing earnings of 17 cents per share (vs. analysts’ expectations of 14 cents per share) on Monday, Jan. 14, an article was published questioning the company’s accounting practices. The stock closed down nearly 7.00 — a 28-percent loss. However, Dynacq was still listed as a top fundamental stock as of Jan. 25 because the IBD screenings do not take into account sudden changes in investor perception.

Fundamental screening, technical trading The stocks highlighted as having top fundamentals by IBD offer many oppor-

50.00 Chaikin Money Flow

0.2 0.1

28

4 February

11

19

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0

Source: eSignal 7.0

FIGURE 4 FUNDAMENTALS DON’T TELL THE WHOLE STORY A stock can get crushed despite having top fundamentals. Two days after a positive earnings announcement, a published article raised concerns regarding accounting practices at the company, and the stock closed down nearly 28 percent. Price

Dynacq International (DYII), daily

Negative article

25.00 20.00 15.00 10.00 5.00

Chaikin Money Flow

0.25 0 -0.25

28 1 8 15 22 29 5 12 19 26 3 10 17 24 31 7 14 22 28 4 October November December January 2002 February

Source: eSignal 7.0

ACTIVE TRADER • July 2002 • www.activetradermag.com

21

TRADING Strategies

22

www.activetradermag.com • September 2002 • ACTIVE TRADER

Getting to know a market means understanding the odds associated with the price moves it typically makes. A handful of simple calculations can put these probabilities at your fingertips. BY THOM HARTLE

here will always be a select group of traders who know just when the market is hitting its low for the day, enter a long position and get out near the high. These traders share a keen, intuitive sense of price direction. Is such talent mandatory for trading success? Not at all. Those of us without an innate feel for the markets can perform simple analysis that allows us to understand the typical price behavior of our favorite stocks and futures. We can then incorporate this valuable information into our strategies. We’ll look at some unique ways to observe and quantify market behavior, and illustrate how to use this information in actual trading. The instrument we will analyze is the S&P500 index tracking stock (SPY), but you can perform the same analysis on any market. The goal in examining the price data is to find patterns in the daily ranges, close-to-close ranges, and the relationship between the open and the low (for days the market closes up) or the open and the high (for days the market closes down). Analyzing simple price patterns makes it possible to determine the odds that different kinds of price moves will occur. As a result, the characteristics revealed in this analysis can be used to tailor trading strategies to the realities of the markets you trade, resulting in more disciplined and probability-based trading — in essence, a mechanical way of achieving a measure of the “intuition” enjoyed by that select group of traders. continued on p. 24

ACTIVE TRADER • September 2002 • www.activetradermag.com

23

FIGURE 1 SPOTLIGHT ON SPY The initial test period for SPY contained both uptrending and downtrending conditions.

trading days of data (late February to mid-May 2002) 118.00 in SPY. The stock switches S&P 500 index tracking stock (SPY), daily from uptrend to downtrend 117.00 and back again. Figure 2 (left, bottom) 116.00 shows the daily range (high minus low) of each bar from 115.00 Figure 1. The blue line is a three-bar moving average of 114.00 the daily ranges and the red 113.00 line is a 10-bar moving average. Comparing this chart to 112.00 Figure 1 reveals the highest volatility occurred when 111.00 SPY was bottoming out in May. Although there is not 110.00 enough data to draw a firm conclusion, this does sup109.00 port the trading adage that 108.00 market turning points — especially bottoms — are 107.00 more volatile than trending periods in terms of daily 106.00 trading ranges. Therefore, if some of your 105.00 March April May other indicators were hint25 1 11 18 25 1 8 15 22 29 1 6 13 20 ing at a top or bottom (such Source: CQGNet as a divergence between price and an oscillator), you functions as a basic measure of volatility could refer to these simple moving averDaily range ages of the daily range as one more conThe first aspect of price behavior to con- — the larger the range, the higher the firmation of a pending reversal. sider is the average daily range, which volatility. Figure 1 (above) shows 60 In addition, the daily range information is vital FIGURE 2 DAILY RANGE for intraday traders — those Arranging the ranges (high-low) of the days in the test period highlights the market’s who close out all open posivolatility characteristics. The high-volatility area corresponds to the May bottom. tions by the end of each trading session. By knowing the current average range 3.0 High-volatility area you can set targets based on how much the market you Three-bar moving average 2.5 trade typically moves in a 10-bar moving average day. Also, intraday traders 2.0 must be able to identify markets with enough intraday volatility to make them 1.5 worthwhile to trade. 1.0

Close-to-close range

0.5 0 Day Source: Excel, data by eSignal 24

The second measure we’ll analyze is the difference between closing prices on a day-to-day basis. We will use absolute values (i.e., all positive numbers) of the close-toclose price moves to make the analysis comparable for www.activetradermag.com • September 2002 • ACTIVE TRADER

FIGURE 3 CLOSE-TO-CLOSE RANGE Measuring the distance between closing prices provides a second perspective on market up and down markets. volatility. Close-to-close moves reflect price gaps between bars. Figure 3 (right) shows the difference between closes 4.5 for the bars in Figure 1, with three- and 10-bar moving 4.0 averages. Note that there is an outlier (an extreme read3.5 ing) at data point 48 — a 3.0 closing difference of $3.91. This reading is much larger 2.5 than the same bar from 2.0 Figure 2 because of the low close on May 7 and a gap1.5 up opening and high close on May 8. Although a larger 1.0 price gap occurred a few 0.5 bars later, the close-to-close move was not as exaggerat0 ed because the bar before the gap closed near its high. Day Some traders may want to use average “true range” Source: Excel, data by eSignal (the greatest absolute difference between today’s high financial press never says the market and today’s low, today’s high and yes- closed up today twice the average true A different perspective terday’s close, or today’s low and yester- range, but they do comment on closing A different way of viewing this price day’s close) for this calculation. differences — e.g., today was the highest information is shown in Figure 4 (left). However, by choosing close-to-close and close in three weeks, or at one point the The price data is adjusted so that each high-minus-low ranges, you have statis- stock was down $6 from yesterday’s bar’s opening price is zero, the high is tical references to know when market close, and so on. With historical num- the net gain from the open, the low is the activity is significant relative to what bers in hand you can put price action in net decline from the open, and the close many other people in the market are perspective and separate facts from is the difference from the open. This pertalking and thinking about. After all, the hyperbole. spective highlights how much the market moved above or below the open on a given day. The next step is to segreFIGURE 4 ADJUSTING THE DATA gate the bars in Figure 4 in This graph shows the daily ranges plotted with the opening price at zero. This highlights terms of days the market how far above or below the open the market moved and where it closed on different days. closed up from the previous close (Figure 5, p. 26) and 3.0 days the market closed 2.5 down from the previous 2.0 close (Figure 6, p. 26). This 1.5 analysis will reveal whether the market has any observ1.0 able tendencies on up-clos0.5 ing or down-closing days. 0 During this 60-day peri-0.5 od, the market closed up 28 -1.0 bars and down 32 bars. (Keep in mind that some -1.5 bars closed below the open -2.0 but above the previous close -2.5 or above the open but below -3.0 the previous close.) As you might expect, the bulk of the Day intraday price movement is Source: Excel, data by eSignal

ACTIVE TRADER • September 2002 • www.activetradermag.com

continued on p. 26 25

FIGURE 5 UP-DAY ANALYSIS above the zero axis (i.e., higher than the open) on upclosing days and below the zero axis (i.e., lower than the open) for down-closing days. There were four instances where price was up more than $1 above the open and closed down (that is, closed below the previous close), and five instances where the price was down $1 or more from the open and closed up. In addition, there were 13 instances (46 percent) in Figure 5 where the price was 50 cents or more below the open, and still rallied to close up for the day. On the other hand, SPY moved more than 50 cents above the open and closed down for the day only nine times in 32 observations (28 percent). Also note that SPYmade no unusual surges or declines during this period. However, there are only 60 bars of data, so a longer-term view would be required before reading too much into these statistics.

These are the days from Figure 4 that closed up from the previous close. Isolating these days allows you to identify any characteristics specific to up-closing days. 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0 -0.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5 Day Source: Excel, data by eSignal

Those of us without an innate feel for the markets can perform simple analysis that allows us to understand the typical price behavior of the instruments we trade. FIGURE 6 DOWN-DAY ANALYSIS Isolating the down-closing days helps highlight the price behavior of these bars. 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0 -0.5 -1.0 -1.5 -2.0 -2.5 -3.0 -3.5 Day Source: Excel, data by eSignal

26

Getting more in depth To get a more reliable picture of the price behavior in this market, we will expand the data period to 500 daily price bars (May 25, 2000, to May 24, 2002) and perform more sophisticated analysis. During this period, the market closed above the previous close 245 times and below it 255 times. The average daily range was $1.68, which is in line with the data from Figure 2. Figure 7 (opposite page) analyzes the data by grouping the daily ranges by size in 50-cent increments (i.e., a penny to 50 cents, 51 cents to $1, $1.01 to $1.50, etc.) and counting the number of days that fell into each group. The daily range was $1 or less on 17 days, $1.01 to $1.50 on 118 days, and $1.51 to $2 on 135 days (the

www.activetradermag.com • September 2002 • ACTIVE TRADER

FIGURE 7 DAILY RANGES low of the day. Also, you can use this information to decide where to place a stop if you started the day with an open long position. In this case, if you are holding positions overnight with the goal of catching a oneto three-day price swing, you cannot place your stop 25 cents or less below the open if you are long. Doing so is inviting the market to stop you out, because SPY 57 traded less than 25 cents away from the open only 25 percent of the time. In other 30 words, the odds you will be stopped out are 75 percent. 17 Here’s another scenario: 8 9 If you are an intraday trad3 2 1 0 1 0 1 er and your system is flashing a buy signal when price is down $1.50 from the Daily range ($) open (remember just slightly more than 5 percent of the time the SPY traded where between a penny and 25 cents higher after being down $1.50 from the below the open and closed up for the open) you may want to pass on the day, while the market traded between 51 trade. cents and $1 below the low and still Now let’s look at the statistics for closed up for the day 66 times. The mardown-closing days. Figure 10 (p. 29) ket traded more than $1.50 below the examines the difference between the open and still closed up for the day bareopen and the high on days the market ly more than 5 percent of the time. (Keep closed down from its previous close. The in mind the open can be up or down for open and the high were the same 16 the day, and the close is compared to the days, and there were 67 days when the

Breaking down the daily ranges into 50-cent increments is the first step toward determin ing the probabilities of different kinds of price moves. The daily range for SPY most often fell between 1.5 and 2.99. 140

135 118

120

103

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20 0

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highest total). Reading the chart from right to left, the SPY traded in a range greater than $2.50 on 128 days (only 25.6 percent of the time). The most extreme reading for a daily range, between $8 and $8.50, occurred when the Fed cut interest rates on Jan. 3, 2001. Figure 8 (p. 28) sorts the close-to-close price moves. The average closing change was $1.27. The largest number of closeto-close ranges was less than 50 cents. The highest closing difference was between $6.01 and $6.50. The SPYclosed with a change greater than $2.50 only 12 percent of the time.

Highs and lows analysis Figures 9 and 10 break down the data into days the close was up from the previous close and days the close was down from the previous close, respectively. The data is divided into 25-cent increments. Figure 9 (p. 28) compares the (absolute) difference between the open and the low on days the market closed up from its previous close. On eight occasions, the open was the low. Fiftythree times the market traded some-

Analyzing basic price relationships makes it possible to determine the odds that different price moves will occur. previous close. In other words, the market could open up $1, trade $2 down from the open and finish 50 cents up from the previous close for the day.) This data tells us a few things about trading a long position. First, unless there is incredibly positive news, there’s no need to go long on the open, because the market closed up only eight times (3 percent) on days the open was also the

ACTIVE TRADER • September 2002 • www.activetradermag.com

market opened, traded up between a penny and 25 cents, and then declined. This analysis can help determine where to place a buy stop if short from the day before. First, it appears that because of the bear market, stops can be placed close to the open: The SPYtraded less than 25 cents above the open while still closing down 32 percent of the time. continued on p. 28 27

FIGURE 8 CLOSE-TO-CLOSE BREAKDOWN (Keep in mind, though, The majority of close-to-close moves were between 50 cents and $1.99 (the first three that’s not enough room bars). This information, along with that from Figure 7, gives you an indication of the because there’s a 68-percent size price move you can expect over different periods. chance of being stopped out. Nonetheless, this 140 134 shows the effect of the bear market: The market traded 120 up more than 75 cents and 113 still closed down only 46 percent of the time. 100 95 If you are an intraday trader and your system is 80 flashing a sell signal when price is up $1 from the open, remember that the SPY 60 53 traded $1 higher and still 46 closed down only 32 per40 cent of the time over the 25 past year. However, as is the case with all these statistics, 15 20 32 percent is simply a num8 5 2 2 ber, and it should not be 1 1 0 0 0 used as the sole basis of a trade; it should complement some other form of techniClose-to-close move ($) cal analysis and preferably a Source: Excel, data by eSignal back-tested strategy. This type of analysis can other aspects of money-management. tial profits once the market hits the averbe incorporated with other technical sigage daily range. nals to set profit targets and improve For example, you could plan to take parFinally, Figure 10 shows there were two occurrences FIGURE 9 OPEN-TO-LOW MOVES ON UP-CLOSING DAYS of the high being more than $5 above the open on Measuring how far the market drops below the low and then closes above the previous down-closing days. These close indicates the odds of a higher close fall significantly when the down move is more two occurrences were in than 1.99 points. September 2001 when the 70 SPY opened sharply lower, 66 recovered from the extremely weak opening 60 price, but still closed down 53 for the day (more than 50 $5.75 once and $1.43 the other time). 40

35

Putting the numbers to work

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30 20

20 10

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28

2

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Compiling the information from this analysis gives you a comprehensive and detailed picture of a market. The characteristics such analysis reveals about a market can be of great help in determining logical stop levels and profit targets, especially for shortterm and intraday traders as mentioned earlier. In continued on p.29

www.activetradermag.com • September 2002 • ACTIVE TRADER

FIGURE 10 OPEN-TO-HIGH MOVE addition, some of the numbers highlight the impact of the bear market, and one number is somewhat surprising. Despite the bear market of the last two years, the number of up closes to down closes is not that different (245 vs. 255). Obviously, if we measured the net difference in closing prices, the results would be greater for down days. Another bear market phenomenon is there were only eight up-closing days for which the open was the low price; for down-closing days the open was the high price 16 times. In addition, a hump is evident at the 26- to 50-cent point in Figure 9, while

Similar to Figure 9, this graph organizes open-to-high moves on days the market closes below the previous close. 70

67

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Figure 10 shows a steadily declining series of lower highs. In other words, even though the market did close up for the day, there was enough selling pressure to push prices well below the open, which places the peak in Figure 9 to the right compared to Figure 10. Both these phenomena could be attributed to the bear market. Analyzing a bull market period of similar length might make the differences between bull and bear markets more evident, and would possibly enable you to identify a bull market or a bear market earlier than some other technique, such as the rising or falling 200-day moving average. For example, a shift in the peaks for the high-low analysis in Figures 9 and 10 could be subtle evidence of a change in the underlying trend. Another idea is to track the number of occurrences when the open is either the low or the high of the day.

The data tells us that unless there’s incredibly positive news, there’s no need to go long SPY on the open, because the market closed up only eight times (3 percent) on days the open was also the low of the day.

From subjective to objective

they are now. Gauging the typical price movement gives you a set of practical references for what is high and what is low in the markets you trade, so you don’t have to guess. And anytime you can bring descriptive analysis that matches real-world experience, you improve your chances for success. By incorporating typical price behavior analysis into your decision-making process, you move away from trading decisions based upon greed and fear and move toward objective, probabilitybased trading. You will also develop a big-picture view of your trading, because you will know the characteristics of the markets you trade and how and why your approach works, and that any one trade can occur outside the typical behavior of the market. Both steps — reducing emotion and looking at trades as a group of decisions rather than isolated events — lead to more effective trading.Ý

High and low are usually relative terms in trading, because markets almost always trade higher or lower than where 29

www.activetradermag.com • September 2002 • ACTIVE TRADER

TRADING Strategies

BULL vs. BEAR: The details matter Market pundits often quip bull markets are different than bear markets. But other than one goes up and the other goes down, what does the distinction really mean? This comparison of bull- and bear-market characteristics provides concrete statistics upon which to base upside and downside trading strategies.

BY THOM HARTLE

T

here’s no doubt traders unwilling to sell short are at a disadvantage in a bear market. But even traders who aren’t biased against short-selling sometimes operate under the misconception that bear markets and down moves are simply inversions of bull markets and up moves. As a result, they think trading from the short side is just a matter of reversing the rules of a long-side strategy. This is only true in the broadest sense, however, because bull and bear markets have notable differences. One oft-repeated example is that sell-offs tend to be sharper and quicker than rallies (more on this later). But there’s still more to profiting on the short side than just taking profits more quickly than you would on a long trade. As noted in “Losing your shorts” (Active Trader, September 2002, p. 56), even when the prevailing trend is down, it’s often more difficult to make consistent money selling short than it would be going long if the conditions were reversed. To improve your short-selling acumen, it’s a good idea to perform in30

depth analysis of the markets you trade, compare their bull and bear characteristics, and design and implement your trading strategies accordingly.

Research refresher “Familiarity breeds profitability” (Active Trader, September 2002, p. 38) discussed the typical price behavior of the S&P 500 depository receipts (SPY) using daily open-high-low-close bars, with the goal of identifying characteristics that could serve as the basis for trading strategies. Analysis of the two years from May 25, 2000, to May 24, 2002 (which began with a closing price of $140.25 and finished with a closing price of $108.69), suggested some of the test results were

skewed because of the bear market conditions that prevailed during this period. To see if the results were different during a bullish phase, the same analysis was performed on daily SPY price data from June 1, 1998, to May 23, 2000. At the beginning of this bull period the SPY closed at $109.53; the last close was $138.00. We’ll compare the results of the two periods, which we’ll refer to as “bear” and “bull” market results, respectively. Figure 1 (opposite page, top) shows the prevailing downtrend of the bear market period and Figure 2 (opposite page, bottom) shows the uptrending conditions that characterized the bull market period. continued on p. 32

www.activetradermag.com • November 2002 • ACTIVE TRADER

FIGURE 1 BEAR MARKET From May 25, 2000, to May 24, 2002, the S&P tracking stock fell 22.5 percent. Even so, this period was punctuated by substantial counter-rallies. S&P Index Trust (SPY), daily 150.00 145.00 140.00 135.00 130.00 125.00 120.00 115.00 110.00 105.00 100.00 95.00 90.00 July Aug. Sept. Oct. Nov. Dec. 2001 Feb. Mar. Apr. May

June July Aug. Sept. Oct. Nov. Dec. 2002 Feb. Mar. Apr. May

Source: eSignal

FIGURE 2 BULL MARKET The S&P tracking stock gained 26 percent from June 1, 1998, to May 23, 2000. Comparing the typical price behavior of this period to that of the subsequent bear period, it’s possible to determine if and how trading strategies should be adjusted for up- and downtrending conditions. S&P Index Trust (SPY), daily

155.00 150.00 145.00 140.00 135.00 130.00 125.00 120.00 115.00 110.00 105.00 100.00 95.00

July Aug. Sept. Oct. Nov. Dec. 1999 Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 2000 Feb. Mar. Apr. May

Source: eSignal ACTIVE TRADER • November 2002 • www.activetradermag.com

31

FIGURE 3 BEAR MARKET CLOSE-TO-CLOSE BREAKDOWN The majority of close-to-close moves were between 1 cent and $1.50 (the first three bars). This information, along with that from Figure 5, gives an indication of the size price move you can expect over different periods of time. 140

Differences from close-to-close

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FIGURE 4 BULL MARKET CLOSE-TO-CLOSE BREAKDOWN Interestingly, the close-to-close price moves in the bull period are similar to those of the bear period, except that in this case the most moves were in the $0.51 to $1 range. 140 117 113

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We’ll begin by comparing the differences in daily closing prices for the two periods.

0

1

1

1

1

Figure 3 (left) shows the distribution of absolute values for the day-to-day changes in closing prices during the bear market period. Figure 4 (bottom left) provides the same information from the bull market period. The bear period close-toclose changes peak in the $0.01 to $0.50 range, while the bull market peak is the $0.51 to $1.00 range. The average change during the bear market period was $1.27, vs. $1.39 during the bull period. Apparently, when there is greed involved, traders are willing to continue to pay up until the close. Market lore holds that a bear market falls faster than a bull market rises, but in this case, it appears people don’t like to carry short positions overnight, so there may be a tendency to cover short positions going into the close despite a prevailing bear market. Figures 5 (opposite page, top) and 6 (opposite page, bottom) compare the daily ranges (high minus low) of the two periods. The similarities between the two charts are somewhat surprising. The one difference is the bull market did have one day with a range between $0.01 and $0.50. But despite the large upswing and downswing, the typical daily ranges did not vary. Figures 7 and 8 (p. 34) are the open-to-low moves for days the SPY closed up.

www.activetradermag.com • November 2002 • ACTIVE TRADER

Here, the difference between the bear market and the bull market is more apparent. First, there were only eight days during the bear market for which the open was the low for the day, whereas the bull market had 24 days. Next, the difference between the open and the low during the bear market peaked in the $0.26 to $0.50 range; during the bull market it peaked between $0.01 and $0.25. This indicates traders aggressively buy right after the open in a bull market, thereby supporting prices, while during bear markets they engage in more selling that drives the low further down from the opening before prices rally to close up on the day. Figures 9 and 10 (p. 35) are the open-to-high moves for days the SPY closed down. Again, the difference between the two periods is visible. There were 16 days during the bear period for which the open was the high for the day, compared to just six for the bull period. In other words, during a bull market price still tends to advance after the open, even on days that eventually close down. The bear market open-tohigh difference peak was 67 days for the range between $0.01 and $0.25. The bull market numbers, on the other hand, were shifted to the left, peaking at 53 occurrences for the $0.51 to $0.75 range. Again, it is not surprising that during a bull market buyers would try to push prices higher even when the market ultimately closed down on any one day.

FIGURE 5 BEAR MARKET DAILY RANGES Breaking down the daily ranges into 50-cent increments indicates, along with the close-toclose moves, how much the market is likely to move from day to day. The daily range for SPY usually fell between $1.01 and $2.50 in the bear market period. 140

135 118

120

103

100 80

57

60 40

30 17

20

17 8

0

0

9

0

3

2

1

0

1

0

1

Daily range ($) Source: Excel, data by eSignal

FIGURE 6 BULL MARKET DAILY RANGES There is virtually no difference in the daily ranges for the bear and bull markets, which is somewhat surprising. 160 140

135 118

120

103 100 80 58

60 40

36 16

20 0

0

1

16

8

9

3

2

1

0

0

0

1

Daily range ($) Source: Excel, data by eSignal

continued on p. 34 ACTIVE TRADER • November 2002 • www.activetradermag.com

33

FIGURE 7 BEAR MARKET OPEN-TO-LOW MOVES ON UP-CLOSING DAYS This summary of how far the market drops below the low and then closes above the previous close indicates the odds of a higher close fall noticeably when the down move is more than 50 cents.

What’s it all mean?

70

66

60 53 50 40

35

33

30 20

20 10

17

8 4

2

2

2

2

0

0

0

1

Open-to-low move ($) Source: Excel, data by eSignal

FIGURE 8 BULL MARKET OPEN-TO-LOW MOVES ON UP-CLOSING DAYS The bull market had most of its open-low moves for up days in the $0.01 to $0.25 range, as opposed to $0.26 to $0.50 for the bear market. This indicates traders are more likely to support prices in a bull market. 55 50

50 45

42 42

40

36

35

33

30 25

24

20

18

15 10 5 0

8 5

5

3

1

2

0

Open-to-low move ($) Source: Excel, data by eSignal

34

0

0

1

0

0

0

It is clear that entry, risk management and profittaking tactics need to take into account the market trend, bear or bull. A trader cannot use the same buy setup and risk points that were effective during the bull market run because the behavior of the market changes during bear phases. Consequently, it’s prudent to spend time developing a sound trend indicator, and then design trade setups based on the trend. Many new traders get into trouble by ignoring these realities. Here’s how the typical trader learning curve might progress: First you learn you have to cut your losses and let your profits run. If you developed your trading technique during the 1990s bull market, you could have designed a viable system that used tight stops because, as Figure 8 shows, in the bull period SPY typically traded down in the neighborhood of only $0.25 to $0.75 from the opening price, and still closed up. However, if you failed to recognize the market’s personality change during a downtrend, you may have bought after the open (when the market was showing initial weakness), and felt confident if the market subsequently moved into positive territory. But during a downtrend (characterized by persistent down closes), it is unlikely the market will climb well into positive territory, as Figure 9 shows:

www.activetradermag.com • November 2002 • ACTIVE TRADER

FIGURE 9

There were only 67 peak opportunities, and the high was less than $0.25 above the open. If you consistently tried to buy post-opening weakness in this kind of environment, you would slowly bleed all of your capital by taking small loss after small loss. The trend is your friend if you know how to take advantage of it by using these kinds of market observations. If your indicator signals the trend is down, you can use the typical bear-market behavior as a starting point for determining entry and exit rules — e.g., going short the SPY if the market is up $0.25 to $0.50 from the open, with your stop a little higher than $1 above the open. Develop separate rules for uptrend market phases.

No getting around the work You may be thinking: Rules, rules, rules. Isn‘t there an art to trading? Yes and no. Intuitively oriented traders probably have a kind of mental spreadsheet, and the profits to prove it. If your profits are not meeting your expectations, take the time to quantify the markets, as well as your trading approach. You will quickly see the relationship between your actions and the market’s, the results of this coming in the form of a series of losing or profitable trades.Ý

BEAR MARKET OPEN-TO-HIGH MOVES FOR DOWN CLOSES

This graph organizes open-to-high moves on days the market closed below the previous close. In the bear market period, the most notable concentration of days had open-to-high moves of less than 50 cents. 70

67

60 54 50 40

37 32

30 23 20

16

14

10 3

2

2

1

0

0 1

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Open-to-high move ($) Source: Excel, data by eSignal

FIGURE 10 BULL MARKET OPEN-TO-HIGH MOVES FOR DOWN CLOSES When SPY was down for the day, the open was the high only six times, and the market often rallied as much as a dollar before closing lower. This shows, in a bull market, price still tends to advance on down days. 60 53 50 44 45 40 31

30

20 14 10

9 6

8

8 2

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Open-to-high move ($) Source: Excel, data by eSignal

ACTIVE TRADER • November 2002 • www.activetradermag.com

35

RISK Control and MONEY Management

Equity curve

DRAWDOWN MANAGEMENT Your system has given you four losing trades in a row. Should you take the next signal, or move to the sidelines? Here are some thoughts on how to determine when to stay out of the market and when to jump back in.

FIGURE 1 EQUITY LINE CROSSOVERS A, B and C mark those periods when the equity line dropped below its moving average, an indication that profitability is in a downtrend and the system’s signals should not be executed.

BY THOM HARTLE

$40,000

$35,000

F

Equity line $30,000

C

or traders not blessed with exceptional market intuition, the best chance of sus$25,000 tained profitability is to trade a system — a 10-period B set of fixed procedures to ensure they act moving average on market opportunities consistently and effectively. $20,000 In addition to entry and exit rules, though, a trading system also must have a risk-management component A that guards against losing a large sum of money on $15,000 any one trade. Trade number The mental challenge of following a system is givSource: Excel ing up control of your trading. On the one hand, you’re faced with the possibility of going broke because your system suffers a drawdown that is longer and Watching the equity line deeper than its hypothetical drawdowns in historical testing or One way to manage the trade-or-not-trade dilemma is to calpaper trading. On the other hand, there is the risk of missing culate a moving average of your system’s equity line (the runtrade opportunities if you do not follow your system to the let- ning total of its dollar gains and losses) to determine when to ter, even when it is in an extreme drawdown. act on its trade signals. When the equity line is above its movWhen should you continue to trade a system, and when ing average, profitability is in an “uptrend,” the system is makshould you stop taking its signals? The following ideas are ing money and you continue to take each trade (see Figure 1, techniques based on analyzing past system returns that above). attempt to balance the fear of losing money with the fear of If the system begins to struggle, the equity line will drop missing trading opportunities. below its moving average, at which point you simply log 36

www.activetradermag.com • February 2003 • ACTIVE TRADER

FIGURE 2 BEFORE AND AFTER The moving average approach (represented by the adjusted equity line) gave up $3,500 in profits, but it also decreased the original equity line’s worst drawdown from $2,653 to $1,720.

Window on profitability

$40,000

$35,000 Equity line $30,000

C

$25,000

B

$20,000

Adjusted equity line

A second approach is to track the percentage of profitable trades within a certain moving window — say, the most recent 10 trades. As long as the percentage of profitable trades in this window is above a certain threshold (e.g., 50 percent), continue to trade. If the percentage of profitable trades drops below the threshold, you would log the trades but not execute them. Then, track the system and resume trading when it returns to profitability by moving back above the percentage threshold.

How they stack up

We’ll apply these two approaches to a two-year hypo thetical track record for a 10-year T-note futures (TY) $15,000 trading system. The system is momentum-based and uses a preset profit target of 10⁄32 for two contracts and a Trade number trailing stop for a third contract. (The target and stop Source: Excel levels were determined using maximum favorable excursion and maximum adverse excursion analysis. FIGURE 3 WINDOW OF PROFITABILITY For more information on these techniques, see “On target trading,” Active Trader, July 2001, p. 44, and The moving window approach (taking trades only when 50 “Taking the guesswork out of stop orders,” Active percent or more of the past 10 trades have been winners) Trader, October 2001, p. 94. All the necessary analysis decreased profitability, but it did not decrease the drawdown, can be done using an Excel spreadsheet.) as the moving average technique did. Figure 1 shows the system’s equity line and its 10day moving average during 1999. (The equity value $40,000 was adjusted to reflect a starting point of $20,000, and the track record begins in 1998 so the 10-period moving average is current at the start of the year.) Using $35,000 the rule of not taking signals when the equity line Equity line drops below the moving average results in three periods when you would have stopped trading, labeled A, $30,000 B and C. (The first losing trade that causes the equity line to drop below the moving average is a real trade, but the next trade would be a paper trade only.) $25,000 Figure 2 (top) shows the original equity line along Adjusted with the new equity line representing the performance equity line of those trades executed when the original equity line 100% $20,000 is above its 10-period moving average. The new, 50% adjusted equity line has flat periods that occur when A B 10-trade profitability window the modified system is not being traded. 0 $15,000 The moving average technique reduced the sysTrade number tem’s profit by about $3,500, but it also decreased the Source: Excel original equity line’s worst drawdown (refer to B in Figure 1) from $2,653 to $1,720. This is a more-thantrades on paper — do not execute them in the market. You con- acceptable compromise for traders who are willing to forego some profit in return for the ability to limit risk to a level they tinue to track the logged signals and their impact on the equity line and its moving average. When the trading system are comfortable with. Figure 3 (bottom) uses a 10-trade moving window and a 50begins to generate profits again, the equity line will cross back above the moving average, at which point you resume execut- percent profitability threshold, which means as long as five or ing trades in the market. continued on p. 38 A

ACTIVE TRADER • February 2003 • www.activetradermag.com

37

FIGURE 4 MOVING AVERAGE: YEAR 2000 more of the past 10 trades are profitable, the system’s signals should be executed. If four or fewer of the past 10 trades are profitable, the trades are merely tracked on paper. There are only two periods, A and B, during which the percentage of profitable trades dropped below 50 percent. Like the moving average approach, the moving window technique sacrificed profits, and for the same reason — lag. However, the moving window did not offset this reduction by shrinking the drawdown as well. That’s not the end of the story, though. Moving forward one year, Figure 4 (top) shows the hypothetical returns for the year 2000. At the beginning of the chart, the original equity line is above the 10-period moving average, which means the original and adjusted equity lines are identical. At point A, the original equity line drops below the 10-period moving average, so the next trade (point B) is only logged on the books. Unfortunately (in terms of trading the modified system), it is a very profitable signal, and it pushes the original equity line back above the 10-period moving average. However, the next trade is a loss, so the system again moves to the sidelines. The difference in profitability at the end of the year was less than $2,000, but the maximum drawdown for the original equity line was $4,592, while that of the adjusted equity line was only $2,692. This was certainly an improvement over the 1999 example, but the modified system still had a lengthy drawdown: It took another 30 trades before the adjusted equity line was able to move above its previous equity peak at trade 14. Figure 5 (bottom) shows the year 2000 results of using the 10-period moving window with the 50-percent threshold. The original system had more than 50percent profitability for the most recent 10 trades until point A. After that, only paper trading was permitted. Real trading resumed at point B when the percent of profitable trades got back to the 50-percent threshold. This time, the moving-window technique dramatically reduced the system’s drawdown — only $1,756 vs. $4,592. By avoiding this drawdown, the money management technique actually outperformed the original system by $500 by the end of the year.

Drawdowns and market conditions

Using the moving average filter was more successful in 2000 than it was in 1999, even though the adjusted equity line suffered through a prolonged drawdown. $40,000

$35,000 Equity line $30,000

B $25,000

Adjusted equity line

A

$20,000 10-period moving average $15,000 Trade number

Source: Excel

FIGURE 5 MOVING WINDOW: YEAR 2000 The moving window technique that underperformed in 1999 outperformed in 2000, reducing the system’s drawdown and increasing profitability by the end of the year. $40,000 Adjusted equity line

$35,000

$30,000 Equity line $25,000

$20,000

100%

B $15,000

A

10-trade profitability window

50% 0

What was happening in the market that resulted in Trade number such a severe series of losing trades? Figure 6 (oppoSource: Excel site page) is a daily chart of the continuous 10-year Tnote futures contract. The system struggled during the middle of the year when the T-note was in a nearly two-month ly tying a trading system to the price action of a market. In other words, you should know what kind of price behavior trading range before it embarked on a trend. The profit targets your system is relying upon to capture profits. (In this way, the that are typically met during a trending market were not being reached during the trading range, so the system was taking system’s profitability itself becomes an indicator of the type of market environment you are in.) losses. One lesson from this experience is the importance of logical38

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FIGURE 6 MARKET CONDITIONS MATTER

Stick to the rules Having a rule that tells you when your system is failing to perform permits you to move to the sidelines based on logic and discipline, rather than fear. The more you can remove emotion from trading, the higher your chances of long-term success. For the techniques outlined here, the choices of a 10-period moving average and a 10-trade moving window with a 50-percent threshold were arbitrary. Other parameters may work better or worse, and should be explored fully before trading. Finally, this study highlights the value of developing a trading method and documenting all of its trades — both historically and in real time. Doing so allows you to perform the kind of analysis described here to manage your money in a more scientific fashion. Ý

Because of the congested market conditions that prevailed for a good portion of the test period, the system’s profit targets were not met as often as they would be in a trend environment. This underscores the importance of under standing the price behavior your system relies on to generate profits. 10-year T-note continuous futures (TY), daily 93,000

92,000

91,000

90,000

89,000

88,000 April 3 10

May 24 1

8

June 15 22

1

July 12 19 26 3

August 17 24 1

14 21

Sept. 1

Source: CQGNet

ACTIVE TRADER • February 2003 • www.activetradermag.com

39

TRADING Strategies

Narrow-range bars and inside

Opening shots

bars represent short-term volatility lows out of which price can move sharply. This strategy uses a simple volatility measurement to determine where to enter trades to capitalize on this behavior. FIGURE 1 IDENTIFYING SHORT-TERM VOLATILITY CHANGES The bars at A, B and C are all relatively narrow-range bars that represent short-term consolidations. Applying specific entry rules allows you to take advantage of moves out of the consolidation when volatility increases.

BY THOM HARTLE

IBM (IBM), daily

I

n the late 1980s, Tobey Crabel published a series of articles detailing various short-term price patterns for futures trading. The patterns were designed to detect shortterm volatility changes — that is, a market would move into a short-term consolidation, and then break out of it. Two of Crabel’s patterns will be covered here. The first is an inside day that is smaller than the previous four days (IDnr4) and the second is a day whose range is less than that of the previous six days (NR7). An NR7 day does not have to be an inside day. Figure 1 (right) contains examples of these price patterns (in a stock rather than a futures contract). Bar Ais an IDnr4: It is an inside day and its range is smaller than the ranges of the previous four days. Bar B is an NR7 day. In this case, the day’s range is smaller than the previous six days’ ranges. Finally, bar C qualifies as both an IDnr4 and an NR7 day.

40

82.50 80.00

C

77.50 75.00

B

72.50

A

70.00 67.50

29

August 1 5

12

19

26

Source: CQGNet

Analyzing IBM daily bar data from Oct. 1, 2001, to Nov. 15, 2002, revealed that 15 IDnr4 and 44 NR7 days occurred over this 286-trading day period. This means these patterns are somewhat rare. However, many trading opportunities present themselves if you look for these patterns across a number of stocks.

Trading the patterns Crabel recommended trading these patterns the next day using an entry strategy based on the opening price and a preset value called the “stretch.” He had two versions of the strategy — one called the opening range breakout (ORB)

www.activetradermag.com • April 2003 • ACTIVE TRADER

and the second the opening range breakout preference (ORBP). The stretch value is the 10-day average of the difference between the open and the low or high, whichever is smaller. For example, if the open was 79.50, the high was 80.33 and the low was 77.98, you would use the difference between the open and the high (0.83) vs. the open and the low (1.52). Figure 2 (top) shows the stretch range for IBM over the last year: from an extreme of just under $1 to just over $0.20, with the average just over $0.50. The entry strategy using ORB is to place a buy stop just above the opening price plus the stretch amount, and place a sell stop just below the opening price minus the stretch amount. The first stop triggered is the trade, and the other automatically becomes the protective stop. If other technical indicators provide evidence of a strong trend, then use the ORBP: Place the entry stop in anticipation of the trend continuing. For example, if the stock is in an uptrend, enter only a buy stop above the opening price plus the stretch amount. If filled, place the protective stop below the stretch subtracted from the open.

FIGURE 2 TAKING A STRETCH The “stretch” is an amount added to a bar’s opening price to determine the entry point and stop level, respectively. $1.20 $1.00 $0.80 $0.60 $0.40 $0.20 $0.00 Day

FIGURE 3 FACTORING IN THE TREND Whether a market is in a trend (defined here by a 30-day EMA) dictates the trade entry technique that is used.

Time is of the essence

IBM (IBM), daily

According to Crabel, the earlier in the trading session the entry stop is hit the more likely the trade will be profitable at the close. A trend triggered quickly in the session could rack up a substantial profit by the close and should be held for a possible two- to three-day run. Once filled (and if the market is exhibiting a strong trend early), then move the protective stop to breakeven. If you are not filled early in the session, reduce the size of the position as time passes through the day. Any positions filled near the close are suspect. In this case, you may have only a small unrealized profit, and probably should not hold the trade overnight.

77.50 75.00

B

72.50

A

70.00 30-day EMA 67.50

29 continued on p. 42

80.00

C

Rules in action Figure 3 (bottom) is Figure 1 with the

82.50

August 1 5

12

19

26

Source: CQGNet

ACTIVE TRADER • April 2003 • www.activetradermag.com

41

addition of a 30-day exponential moving average (EMA). Bar A is the IDnr4 day. Considering the market moved above the previous resistance level at 72.50 in the act of confirming a double bottom pattern, and the 30-day EMA was rising and provided a support level, it’s logical to conclude the stock is in an uptrend. Accordingly, we want to use the ORBP guidelines. At this time, the stretch was 0.49. The next day IBM opened at 71.55, so the

The long-entry stop was 76.98, which was hit later in the morning. The stock closed at 79.35 for a profit of 2.37 that day, not including slippage. This open profit warranted holding the position overnight. The next day, the stretch is used as a trailing stop, based on the opening price (79.35). The stretch had increased to 0.53, making the stop level 78.82 (79.35-.53), which was not hit. The next day, the stock opened at 81.56. Subtracting the

FIGURE 4 DETERMINING LOGICAL TARGETS To increase the odds of profitability, you can take partial profits when price moves in your direction by 66 percent of the 10-day average daily range. 4.0

10-day MA of the daily ranges

3.5 3.0 2.5 2.0 1.5

Stretch

1.0 0.5 0 Day

entry stop price was 72.04 (71.55 + 0.49) and the stop loss was 71.06 (71.55 – 0.49). That day IBM climbed as high as 73.78, fell as low as 71.19, and closed at 71.90. In this situation, when there is no profit at the close, you should take the loss (in this case, 14 cents plus any slippage). Bar B is the NR7 bar. The market is clearly in an uptrend, and the prudent thing to do is trade with the trend, again following the ORBPguidelines. After the NR7 day, the stock opened at 76.50; the stretch was 0.48. In this case, the stock made a low of 75.98 (0.52 below the open) in the first few minutes, which would have triggered a short sale if we did not use the ORBP rule to trade with the trend. 42

stretch (0.53) sets a new stop at 81.03, the approximate level at which the trade would have been stopped out. Bar C is the combination IDnr4 and NR7 bar. Still trading from the long side, the market opened the next day at 81.90. Adding the current stretch of 0.53 created an entry stop of 82.43. But because the high was 82.00 on this day, no long trade was executed. As an example of what would happen taking the trade against the trend, subtracting 0.53 from the opening of 81.90 would have put you short at 81.37. The stock closed at 81.00, which would have resulted in a small profit if you exited at the close. If you stayed short, however, expecting some follow-through profit

taking, you would have been stopped out at 81.48 (using the stretch the following day to determine the stop-loss).

Profit targets One way to take partial profits is to use a percentage of the 10-day moving average of the daily ranges as a target. Figure 4 (left) compares the 10-day average of the daily ranges compared to the stretch amounts. The average daily range is 2.55, but it ranges from just above 1.50 to just over 3.50. A reasonable target is 66percent of the current 10-day moving average, just to be sure to put away some partial profits when you have the chance. For example, at the bar after A in Figure 3, the current 10-day moving average of the range was 2.78. Assuming that once you are stopped into the long position you are confident the low at 71.19 is in place for the day, add 66 percent of 2.78 (1.85) to 71.19 for a target of 73.04. This would have given you partial profits of 0.98 on this day before slippage, which offsets the loss taken had you held the position at the close. In addition, had you traded against the trend after the bar C trigger, you would have been short at 81.37. The 10day moving average of the daily ranges had increased to 3.06, so the target would have been the high of 82.33 – 2.04 = 80.31 (3.06 * 0.666 = 2.04), which would have been reached. Finally, once in a trade, consider moving your stop to breakeven if the market has reached a point that represents 50 percent of the 10-day average of the daily range.

Be a specialist Avery important aspect of applying this kind of pattern-based technique is your ability to execute trades with as little slippage as possible. Identifying these types of price patterns, and combining them with rules for entering, managing risk and taking profits in various markets amounts to specializing. And specialization is as popular and profitable an endeavor in trading as it is in other disciplines.Ý

www.activetradermag.com • April 2003 • ACTIVE TRADER

TRADING Strategies

What goes UP must come DOWN The balance of up volume and down volume can tell you a lot about the market’s bias during the trading day. Here we detail a unique volume-based indicator and ideas for using it in the markets.

W

BY THOM HARTLE

hen analyzing the broad market, many traders consult volume to confirm price moves. Total volume is most often the subject of this analysis, but comparisons of up volume (total volume in stocks that are up on the day) and down vol-

FIGURE 1 UP AND DOWN VOLUME Up volume reflects how much trading is occurring in stocks that are trading up for the day; down volume is the opposite. This bottom part of the chart plots up volume minus down volume. Up volume was usually higher on days the market closed up, and vice versa. S&P 500 (SPX), five-minute

950.00 925.00 900.00 875.00 850.00 825.00 800.00 775.00 15,000

Up volume - down volume

10,000 5,000 0 -5,000

7

14

Source: CQGNet

43

21

28

Nov. 1 4

11

18

25

Dec. 2

-10,000

ume (total volume in stocks that are down for the day) can provide additional insight into market behavior. Typically, if up volume is greater than down volume, the market will be up on the day, and vice versa. Figure 1 (left) shows an example of the relationship between daily up and down volume. The top half of the chart is the S&P 500, and the bottom is the difference between up volume and down volume. When the S&P closed up, the difference between up volume and down volume was positive; on days the market closed down, the difference was negative.

General volume characteristics The battle between up volume and down volume is similar to a car race in which one car is running at top speed and the other is sputtering along. When traders and investors are very bullish, they are buying more — or more aggressively — than they are selling. Up volume is greater relative to down volume, and the market advances. If traders and investors are bearish, the opposite is true. During periods when buyers and sellers are balanced, the up and down volume statistics will be closely matched and a trading range will unfold. An intraday view of two days — one where the bulls dominate and one where the bears are in charge — offers additional perspective on the interplay of up and down volume.

www.activetradermag.com • May 2003 • ACTIVE TRADER

FIGURE 2 UP VOLUME LEADS DOWN VOLUME On an bullish day for the S&P 500 index, up volume (left) increased at a much greater rate than down volume (right). C

NYSE advancing volume, five-minute

(All of the following charts feature five-minute bars.) Figure 2 (top) shows three charts for Nov. 1, 2002. The upper left is up volume, the upper right is down volume and the S&P 500 is on the bottom. Points Aand B represent the previous (Oct. 31) close, a day on which down volume was approximately 200 million more than up volume, and the S&P closed down just less than five points. On the Nov. 1 close (points C and D), however, up volume was more than 1 billion shares and down volume was less than 400 million shares. It’s no surprise, then, the S&P 500 was up more than 15 points on the day. The steady rise and steeper angle of ascent of the up-volume line relative to the down-volume line is an indication of solid buying power. Figure 3 (bottom) shows the difference between up volume and down volume compared to the S&P 500 on Nov. 1. When the opening bell rang, the S&P 500 was down from the previous close and the difference between up volume and down volume was negative. At point A, the difference bottomed and climbed into positive territory just as the S&P 500 moved into positive territory. Also, notice that while the volume difference made a new high at point B, the S&Pdid not make a new high until a short time later. Not all stocks included in the calculation of the volume statistics are in the S&P500. Here, up volume was continuing to climb at a faster pace than down volume, indicating the broad market was still rising. The S&P 500 soon followed. Figure 4 (p. 32) is more interesting. The top half of the chart shows the ratio (rather than the difference) of up volume to down volume. There appears to be a greater correlation between this calculation and the index, as the peaks and troughs of the two series are closely aligned. The ratio of up-to-down volume runs nearly 2-to-1 for most of the day. There are two components to the ratio — up volume and down volume. The next step is to analyze the individual components to see if an indicator can be created.

A

1.0B

NYSE down volume, five-minute

1.0B

B

800M

800M

600M

600M

D

400M 200M

Nov. 1-8:30

0

10:30

12:30

1-14:30

400M 200M

Nov. 1-8:30

0

10:30

12:30

1-14:30

S&P 500 (SPX), five-minute 900.00 895.00 890.00 885.00 880.00

Nov. 1-8:30 Source: CQGNet

9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 1-14:30

FIGURE 3 MOVIN’ ON UP As the S&P gradually moved up, so did the difference between up volume and down volume. Up volume - down volume

600M 400M

B

200M 0

A

-200M

S&P 500 (SPX), five-minute 900.00

C

895.00 890.00 885.00 880.00

Nov. 1-8:30 Source: CQGNet

9:30

10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 1-14:30

Designing an indicator The primary challenge of developing an indicator is to have up volume and down volume start each day at zero. To accomplish this, the indicator must be quick to drop values from the previous

ACTIVE TRADER • May 2003 • www.activetradermag.com

day, like a simple moving average. Also, because both up volume and down volume climb all day, it may be advantageous to calculate the rate of change of these values; acceleration or deceleration in the rate of change might forewarn, or continued on p. 45 44

FIGURE 4 THE UP-VOLUME/DOWN-VOLUME RATIO Instead of subtracting down volume from up volume, the top part of this chart shows up volume divided by down volume. Like Figure 3, the line steadily climbs throughout the day. However, this calculation tracks the S&P more faithfully than the subtraction formula.

action in the lookback period. One such measurement can be derived from linear regression. Up volume/down volume ratio 3 A linear regression line is a “bestfit” straight line plotted through data points. If the data points are zig-zag2 ging upwards, a best-fit line drawn through the points would be rising or have a positive slope. If the data points are zig-zagging downwards, 1 the best-fit line would have a negative slope. If the data points were zig-zagging sideways, the best-fit line would S&P 500 (SPX), five-minute be horizontal — that is, its slope 900.00 would be zero. (For more information on regression lines, see “The next-bar 895.00 forecast”.) The top of Figure 5 (bottom) shows 890.00 up volume, and below it is an indica885.00 tor that tracks the slope of a best-fit linear regression line of the up volume 880.00 using a five-period lookback. (The Nov. first five readings are ignored because 1-8:309:00 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 1-14:30 they include the previous day’s valSource: CQGNet ues.) The market began on a negative note, but up volume was climbing FIGURE 5 THE UP-VOLUME SLOPE LINE from the early part of the day, and the slope indicator started just above zero. Below the up-volume line (top) is a line reflecting the slope of a five-day linear A little after 9:30 a.m. CT, the slope regression line at each bar. A linear regression (or “best-fit”) line incorporates all indicator shot above +250, indicating a data points of a lookback period. The slope sunk to (or below) the zero line at the large increase in buying. same time price made intraday pullbacks. At points A and B the slope line dropped near zero and below zero at 1 . 0 B Up volume point C. These low readings coincid750M ed very closely with the S&P’s pull500M backs within the day’s uptrend. More 200M importantly, the slope line was above 0 zero almost the entire day and consisIgnore these readings Up-volume slope tently had readings at or above +250. 250 Figure 6 (opposite page, top) is like 0 Figure 5 except it shows down volA B C -250 ume. At point A, the slope was just over +150, much higher than the up S&P 500 (SPX), five-minute volume reading for the same period 900.00 in Figure 5. With down volume dominating the early market, the S&P 500 895.00 was down in the first hour of trading. 890.00 The peak at A coincided with the bottom in the S&P, and when the market 885.00 began to advance, the slope line dropped to nearly -100 (point B). This 880.00 is where the up volume advanced Nov. above +250 in Figure 5. 1-8:30 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 1-14:30 Source: CQGNet This change represented a real shift toward up volume, and the fact the However, this isn’t necessarily the best at least confirm, the current price trend. up-volume slope line had a higher intraThe most common way to measure measurement, because it ignores the day peak than the down-volume slope rate of change is to compare the current prices between the current and the oldline suggested an uptrend was in the value to the value x prices ago — for est in the lookback period. A better cal wings. For most of the day, the downculation would incorporate all the price example, five bars, 10 bars, etc. volume slope line stayed between -100 45

www.activetradermag.com • May 2003 • ACTIVE TRADER

FIGURE 6 THE DOWN-VOLUME SLOPE LINE to +100, except for one excursion to +200 at point D. This coincided with the worst sell-off of the day. Figure 7 (bottom) shows how the up volume, down volume battle plays out on a down day. The top part of the chart plots the up volume divided by the down volume. The trading day started with the up-volume/down-volume ratio above 40 percent, a number that fell to 20 percent by the end of the session. The top portion of Figure 8 (p. 47) contains the up volume, with its slope line. The market opened down but the slope line bounced back to just below +75 at point A. For the better part of the day the slope stayed at relatively low levels as the market worked its way down. This confirmed the lack of buying. The only decent rally came at point B, when the slope moved back to +75. Figure 9 (p. 34) shows the down volume with its slope line for the same day. The slope line quickly moved above +100 and hovered near this level for most of the day until surging higher toward the end of the day. Although these are only two examples of trending days, in both situations the slope line provided a good indication of the dominant market force. Strong uptrending days have up-volume/down-volume ratios of 2-to-1 (200) or higher. Downtrending days are accompanied by up-volume/down-volume ratios of less than 1-to-2 (50). On non-trending days, the ratio tends to be much closer to 1-to-1 (100).

The slope indicator for down volume peaked at the same points the up-volume slope line made temporary bottoms in Figure 5. Down volume

750M 500M 250M 0

Down-volume slope

Ignore these readings

C

A

D

B

200 100 0 -100

S&P 500 (SPX), five-minute 900.00 895.00 890.00 885.00 880.00

Nov. 1-8:30 Source: CQGNet

9:30

10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 1-14:30

FIGURE 7 ON A DOWN DAY The up-volume/down-volume ratio (top) on a day the S&P declined essentially mimics the downtrend in the index.

Market context

Up volume/down volume ratio

.500 .400 .300 .200

S&P 500 (SPX), five-minute

910.00 905.00

What sets the stage for an uptrending or downtrending day? Most often, 900.00 some news event will push people’s psyches in one direction or the other. 895.00 The catalyst can be expected news, such as economic releases, or 9-8:30 9:30 10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 9-14:30 unplanned, such as a group of analysts simultaneously making comSource: CQGNet ments early in the morning. Therefore, a quick check of the morn- volume/down-volume is 50 or less after extended run, or a breakout of support and resistance. On days such as these, ing volume statistics can often give an the first hour of trading, the sellers will check the slope indicator early in the day likely be in control all day, barring some indication of what kind of day to expect. other news that reverses the crowd’s and see whether up or down volume is If the news was good and the up-volmore dominant. If the up slope line hits ume/down-volume ratio is 200 or high- mentality. +200 and down slope line only rises to Sometimes the market action may be er, expect a market that will wind its way +50, higher highs are likely. On the other more technical in nature — for example, upward. the result of profit-taking after an On the other hand, if upcontinued on p. 47 ACTIVE TRADER • May 2003 • www.activetradermag.com

46

FIGURE 8 UP-VOLUME SLOPE ON A DOWN DAY Short-lived intraday rallies are accompanied by peaks in the up-volume slope line. Up volume

400M 300M 200M 100M

Up-volume slope

100

B

A

50 0

S&P 500 (SPX), five-minute

910.00

A

905.00

B 900.00 895.00

9-8:30 Source: CQGNet

9:30

10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 9-14:30

FIGURE 9 DOWN-VOLUME SLOPE ON A DOWN DAY The slope of down volume remained steadily above the zero line and shot up at the end of the day when the index declined. Down volume

1.0B 750M 500M 250M

Down-volume slope

0 300 200 100 0

S&P 500 (SPX), five-minute

910.00 905.00 900.00 895.00

9-8:30 Source: CQGNet

9:30

10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 9-14:30

hand, if slope for the down volume climbs to +150, and the up volume drops to –60, the bears are in control.

Taking another step During obvious trend days, another calculation involving the volume slope 47

indicators can help decipher intraday price action: the difference between the up-volume slope line and the down-vol ume slope line. An uptrending day provides the first example. The concept here is the short-term market trend peaks as the up-volume

level peaks, and the up-volume slope line peaks shortly after. At the same time, the down-volume will trough and begin to rise, and the down-volume slope line will turn up. Watching the differences between the two slopes can highlight volume changes, and in turn, market shifts. Figure 10 (opposite page, top) is another chart of Nov. 1. The top part of the chart plots the difference between the up-volume slope line and the down-volume slope line. (Remember the first five readings are ignored because they incorporate the previous day’s readings.) A horizontal line is placed at +50, a level chosen (instead of zero) because the difference between the two slopes may not cross zero. Recall that just after 9:30 CT on this day, the up-volume level crossed above the down volume level (see Figure 3), and the up-volume/downvolume ratio was close to 2-to-1 (see Figure 4). Both developments are signs of an emerging uptrend. Let’s develop some hypothetical trading rules: 1. A buy signal occurs when the slope-difference line turns up after it has fallen below 50. 2. The risk point is just below the low of the entry bar. 3. Take a profit when the slope-difference line crosses above 50, and then back below 50. Each letter in Figure 10 marks an entry; the exits are marked on the appropriate price bar. There are a number of good entry and exit points, with some losing trades occurring during congestion (see points C and D). Trade E was stopped out because the market traded below the low of the entry bar. However, because the slope-difference line was below the +50 line, the trade was re-entered. Another idea is to experiment with a higher exit threshold, such as a rise above and a drop below 200. Figure 11 (opposite page, bottom) shows a downtrending day. In this instance, we placed a horizontal line at the -50 level of the chart showing the difference between the two slopes. For a downtrending market (i.e., the difference between the up volume and down volume is negative, and the up-volume/downvolume ratio is 50 percent or less), go short

www.activetradermag.com • May 2003 • ACTIVE TRADER

FIGURE 10 SLOPE-DIFFERENCE LINE when the slope-difference line is above -50 and turns down. The risk point is just above the high of the entry bar, so take profits if the slope-difference line crosses back above -50. The first trade (point A) was a loser, but the next trade was profitable despite a lower entry point than the previous trade. Trade C was caught in some sideways market movement. You would not re-enter after this trade because the slope-difference line was below -50, not above. Trade D had a nice open profit, but the majority was given back, and trade E was a good run down until the close. These signals could be improved by calculating the typical price move following an entry, using maximum favorable excursion (MFE) analysis to set targets.

The ups and downs of the market Intraday up- and down-volume statistics offer insight into the dynamics of buying and selling pressure. When the up- and down-volume numbers are nearly the same throughout the day, the market tends to trade back and forth — the case on most trading days. However, there are days when the market makes significant moves, and the intraday volume numbers can help identify trade opportunities. Remember, there is usually some event that causes people to favor one side of the market on a given day. In the first hour or two, you can determine if up or down volume is dominating by looking at the raw difference between the two, the ratio or by using slope analysis. However, trending conditions do not develop every day, which is why intraday traders have mostly good days and bad days and, only occasionally, great days. The concept of tracking the intraday volume statistics presented here is the groundwork for further research. Traders could use the slopedifference line of the up volume and down volume as the basis for a system, or elements for either entry and exit strategies within other systems. Finally, on those days with a bullish bias, watch for the down volume indicator to show signs that its ascent is waning. The market will typically rally from that point. Likewise, on bearish days, the

The difference between the slope of the up-volume line and the slope of the down-volume line captures many of the market’s intraday turns. Trades that were entered are marked by letters, with the exits noted. Slope difference

600 400 200

A Exit

F

Exit

C

B

0

Exit

D

-200

E S&P 500 (SPX), five-minute

900.00

Exit Exit

Exit

B

A

Exit

C

D Exit Exit

F

E

Re-enter Exit

895.00 890.00 885.00 880.00

Nov. 1-8:30 Source: CQGNet

9:30

10:00 10:30 11:00 11:30 12:00 12:30 13:00 13:30 14:00 1-14:30

FIGURE 11 TRADING ON A DOWN DAY When the trend is down, the slope differential can be used to signal trade opportunities. Moves above and below the -50 line are the initial triggers. Slope difference

B

Exit C

D

200

E Exit

100 0 -100

A

-200 -300 -400

S&P 500 (SPX), five-minute

Exit

A

907.50 905.00

B Exit

Exit

D

Exit

E

902.50 900.00 897.50

C

895.00 892.50

9-8:30 9:00 9:30 Source: CQGNet

10:00 10:30 11:00 11:30

bears will take charge when the up volume slows. This may seem counter-intuitive, but it will have you thinking about buying in an uptrend (after a pullback driven by an advance in the number of

ACTIVE TRADER • May 2003 • www.activetradermag.com

12:00 12:30 13:00 13:30 14:00 9-14:30

down-volume stocks) or selling a rally (after a short-term rise in the number of up-volume stocks).Ý

48

Do markets have intraday price characteristics short-term traders can use to improve their strategies? We crunch some numbers to find out when the market is moving and when it’s snoozing.

BY THOM HARTLE

V

olatility, although often associated negatively with choppy, uncertain market conditions, is essential for traders: The market has to go somewhere to make a position profitable. What traders wish for is not low-volatility conditions; on the contrary, they prefer high volatility occurring in the direction of their positions. The degree of volatility is especially crucial for intraday traders because they try to capture short-term price movement; they do not have the luxury or desire to hold a position overnight. For such traders, knowing when the most volatile periods occur during the trading day would be a valuable piece of information — if there were a consistent pattern to that volatility. Traders could then focus on those periods with the most promise of price movement and avoid those less likely to offer tradable volatility.

Gathering the evidence We will determine if different times of 49

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TABLE 1 AVERAGE RANGES: FIRST HOUR OF TRADING

the trading day exhibit noticeable volatility characteristics by analyzing 10-minute price bars in the S&P 500 EMini futures (ES) between 8:30 a.m. and 3:10 p.m. CT, from Jan. 2 to March 31, 2003. This daily trading period coincides with normal market hours at the New York Stock Exchange (NYSE) plus 10 minutes (we will see if anything interesting occurs in the futures after the NYSE closes). The total historical analysis period encompassed uptrends, downtrends and sideways price movement. The total number of price bars over these 61 trading days is 2,440 — forty 10-minute bars per day. The narrowest price-bar range was .50 points and the largest was 15.00 points. (We are not concerned with direction, just the ranges of the 10-minute bars throughout the trading day.)

The largest average 10-minute range (4.46 points) was the 9 a.m. period, which corresponds to when many economic reports are released. Time

8:30

8:40

8:50

9:00

9:10

9:20

Average range

3.62

3.68

3.60

4.46

3.54

3.32

FIGURE 2 9:20 PERIOD VS. THE 12:20 PERIOD The 9:20 periods are plotted as a line and the 12:20 periods are plotted as a histogram. There were only six times (less than 10 percent of all occurrences) that the 12:20 period had a larger range than the 9:20 period the same day. 8.00 7.00 6.00 5.00 4.00 3.00

Intraday time patterns Figure 1 (opposite page) shows the average ranges for each 10-minute trading period in the trading day, beginning with the bar that opens at 8:30 a.m. and the final bar that opens at 3 p.m. The most volatile time of the day is the first hour of trading, when the 10-minute average ranges noticeably exceed those during the rest of the day as traders discount overnight events. Table 1 (top) lists the average values for the first hour, and shows the largest average 10-minute range (4.46 points) is the period beginning at 9 a.m., which is likely because so many economic reports are released at that time. Referring back to Figure 1, the average ranges taper down to less than 2 points at 12:10 p.m., climb again as the market nears the close, and finally drop off in the final few bars. It is safe to assume the combination of a lack of news and the lunch hour plays a role in the declining volatility during the middle of the trading day in Chicago. This initial analysis suggests the best trade opportunities are early in the trading day. After all, markets are all about continued on p. 51

2.00 1.00 0.00 Day

Source: Excel; data from CQGNet

FIGURE 3 2:20 PERIOD VS. THE 12:20 PERIOD Here the 2:20 period (plotted as a line) is compared to the 12:20 period (plotted as a histogram). The 12:20 range was larger than the 2:20 range 15 times (25 percent of all occurrences) the same day. 10.00 9.00 8.00 7.00 6.00 5.00 4.00 3.00 2.00 1.00 0.00 Day

Source: Excel; data from CQGNet

ACTIVE TRADER • August 2003 • www.activetradermag.com

50

FIGURE 4 AVERAGE RANGES MINUS MEDIAN RANGES The difference between the average and median ranges shows almost all of the values are positive, indicating there is a positive skew to the data. 0.60 0.50 0.40 0.30 0.20 0.10 0.00 -0.10 Time

Source: Excel; data from CQGNet

FIGURE 5 RANKING THE RANGES The ranges span 0.50 to 14.75. The most common range value is 2.00, with 313 occurrences. The number of occurrences of 2.00 or larger is 1,702, or 69.8 percent. 350 300 250 200 150 100 50 0 Range

Source: Excel; data from CQGNet

FIGURE 6 LARGEST RANGES This chart shows both time and size of 10-minute ranges that were 6.25 points or more. Twenty-three of the 32 occurrences, or 72 percent, occurred before 10 a.m., with nine occurring during the 9 a.m. bar. 16.00 14.00 12.00 10.00 8.00 6.00 4.00 2.00 0.00 Time

price discovery, and the process is in full force as traders adjust to the release of economic numbers and individual stories driving particular companies and market groups. As the trading passes the mid-point of the session, traders who may have held onto losing positions likely will be forced out when volatility increases as the market nears the close, while traders on the right side of the day’s trend may see better profits with a little patience. For a more direct comparison of highvolatility and low-volatility periods, Figure 2 (p. 50) shows the 10-minute ranges for all the 9:20 a.m. periods (the blue line) and the 10-minute ranges for all the 12:20 p.m. periods (the histogram) over the 61-day analysis period. There were only six times (just less than 10 percent) that a 12:20 p.m. 10-minute range was larger than the 9:20 a.m. period 10-minute range for the same day. The average range for the 12:20 p.m. period was 1.99, and the number of times the range was 2 points or larger was 32 (52 percent). The 9:20 a.m. period was 2 points or larger 55 times (90 percent). Figure 3 (p. 50) compares the 2:20 p.m. periods (the blue line) to the 12:20 p.m. periods (the histogram). The 12:20 p.m. range was larger than the 2:20 p.m. range on only 15 days, or 25 percent of the time. However, the range of the 2:20 bar was 2 points or greater 48 times (79 percent). Figure 3 also shows that one 2.20 p.m. bar had a range of 9 points. Because of its abnormally high range, this represents an “outlier” — a statistical anomaly. To counter the disproportionate effect an outlier can have when calculating an average, some statisticians use the median value instead. The median is the center point, or middle, observation in a data set, with the data arranged from the lowest to the highest value. Because there are 61 observations (trading days) in the analysis period, the median will be the value 30 places below the maximum range and 30 places above the minimum range for any of the 10-minute periods.

Source: Excel; data from CQGNet 51

www.activetradermag.com • August 2003 • ACTIVE TRADER

FIGURE 7 AVERAGE 10-MINUTE RANGES, QQQ Here are the average ranges for each 10-minute period, beginning with the bar that opens at 8:30 a.m. and the final bar that opens at 3 p.m. Again, the best trade opportunities are in the morning when volatility is the highest. 0.25 0.20

Comparing the

0.15

averages to the

0.10

medians, almost all the values are

0.05 0.00 Time

positive, indicating

Source: Excel; data from CQGNet

there is a positive

TABLE 2 FIRST HOUR OF TRADING, QQQ

skew to the data. Figure 4 (opposite page, top) charts the difference between the median and average values for all the 10-minute periods. Almost all the values are positive, indicating there is a positive skew to the data — which means the ranges tend to be larger than the median range. Interestingly, the 12:20 p.m. and 12:30 p.m. periods have negative values, again highlighting how the market slows down during the noon hour. (The 2:40 p.m. hour has a negative difference, as well.) How common is a 9-point range for a 10-minute bar? Figure 5 (opposite page, middle) sorts the ranges by size, from the smallest (.50) to the largest (14.75) and the number of occurrences. The most common range is 2 points (313 occurrences). The number of ranges 2 points or larger is 1,702 (69.8 percent). There were only two 10-minute ranges of 9 points. Figure 6 (opposite page, bottom) plots the time and size of 10-minute ranges that were 6.25 points or larger (there were 32 such occurrences). Twenty-three (72 percent) occurred before 10 a.m., with the most (nine) occurring during the 9 a.m. bar.

Analyzing a second market: QQQ Let’s review the same period for the

In QQQ, the opening 10-minute bar and the 9 a.m. bar had average ranges of 19 cents. Time

8:30

8:40

8:50

9:00

9:10

9:20

Average range

0.19

0.18

0.17

0.19

0.17

0.15

FIGURE 8 AVERAGE MINUS THE MEDIAN, QQQ Most of the differences between the averages and the medians are positive indicating a tendency for the ranges to be larger than the mid-point of the data. 0.0300 0.0250 0.0200 0.0150 0.0100 0.0050 0.0000 -0.0050 -0.0100 Time

Source: Excel; data from CQGNet

Nasdaq 100 index-tracking stock (QQQ). The narrowest range was 3 cents, and the largest was 63 cents. Figure 7 (top) shows the average ranges for each 10minute period throughout the trading day. As was the case with the S&P E-Mini futures, the most volatile time of the day is the first hour of trading, during which

ACTIVE TRADER • August 2003 • www.activetradermag.com

the average ranges exceeded those of the remainder of the day. Table 2 (middle) lists the average values for each 10minute period in the first hour. Figure 8 (bottom) plots the difference between the average ranges and the median ranges for each 10-minute period. Again, almost all the differences are posicontinued on p. 53 52

FIGURE 9 THE 9:20 PERIOD COMPARED TO THE 12:20 PERIOD The individual 10-minute ranges for the 9:20 period are plotted as a line and the 12:20 periods are plotted as a histogram. There are only three occurrences when the 12:20 period had a larger range than the 9:20 period. 0.60

tive, suggesting the ranges tend to be, on average, larger than the median range. Figure 9 (top) shows the individual 10-minute ranges from all the 9:20 a.m. periods (the line) and all the 12:20 p.m. periods (the histogram). In this case, the 12:20 p.m. period had a larger range than the 9:10 a.m. period on only three days. The QQQ had one 10-minute bar from this period with a range of 50 cents on one day. Now, let’s look at how the sizes of the ranges rank over the total analysis period. Figure 10 (middle) shows the size of the 10-minute bar ranges and the number of times each occurred. The most common range was 9 cents (271 occurrences). In fact, more than 72 percent of the 10-minute bars had a range of 9 cents or higher. Using only the ranges greater than 25 cents (there were 49), Figure 11 (bottom) plots the ranges vs. the time of the day. Again, most of the occurrences are in the morning, with 40 of the 49 (82 percent) outliers occurring before 10 a.m., and 10 of those in the 9 a.m. bar.

Another piece, not the whole puzzle This study says nothing about the way the ranges unfold. The fact that the average for the 9:20 a.m. bar is slightly larger than the 9:40 a.m. bar says nothing about the relationship between these two bars. Having said that, the best volatility opportunities (for traders with the proper skills) occur primarily during the early part of the trading day; they taper off toward noon, and then rise again. In addition, there is a slight tendency for the occasional large move within the individual periods, which also offers the trader a better-than-average opportunity. If you analyzed an intraday trading approach without incorporating a reference to time patterns, you might develop target and risks points that are not as logical or useful because of unforeseen changes in volatility. Those traders not following equities or their counterpart futures contracts should perform the same analysis on their favorite markets.Ý

0.50 0.40 0.30 0.20 0.10 0.00 Day

Source: Excel; data from CQGNet

FIGURE 10 RANGE RANK, QQQ The most common range was 9 cents, with 271 occurrences. Over 72 percent of the 10-minute bars had ranges of 9 cents or higher. 300 250 200 150 100 50 0 Range

Source: Excel; data from CQGNet

FIGURE 11 LARGEST RANGES, QQQ The majority of the exceptionally large occurrences are in the morning with 40 of the 49 (82 percent) occurring before 10 a.m. Ten of those are in the 9 a.m. bar. .6 .5 .4 .3 .2 .1 0 Time

Source: Excel; data from CQGNet

53

www.activetradermag.com • August 2003 • ACTIVE TRADER

TRADING Strategies

Trends, consolidations and

UNCHANGED VOLUME Traders often monitor total volume, or up volume and down volume. This analysis studies the price action that follows days with high levels of unchanged volume. BY THOM HARTLE FIGURE 1 CALM BEFORE THE STORM The highest unchanged volume reading corresponded to a market pause that preceded a substantial run up. S&P 500 index (SPX), daily 1,000.00

D 975.00 C B 950.00 A 925.00 High unchanged volume Unchanged volume

40 mil. 30 mil. 20 mil. 10 mil.

12 Source: eSignal

54

19

27

2 June

9

T

he best trade opportunities arise when a market is trending in a certain direction, but markets alternate between these desirable trending phases and hard-to-trade congestion phases. Given this reality, a tool that highlights congestion would make it easier to position oneself to take advantage of the next trend phase. An “internal” indicator that helps in this regard is the volume of unchanged stocks trading on the New York Stock Exchange (NYSE). The NYSE breaks down the total volume into up volume (the volume of stocks trading above the previous day’s close), down volume (the volume of stocks trading below the previous day’s close) and unchanged volume (the volume of stocks unchanged from the previous day’s close). There are two issues to explore here: First, can a high unchanged volume reading be attributed to a high number of stocks in a directionless mode? Second, what happens the following day respective to a high unchanged volume day’s high or low? Does the market trend after a high unchanged volume reading? We investigate these issues regarding NYSE unchanged volume statistics via the S&P 500 because of the popularity of its index-tracking stock (SPY) and the E-Mini S&P futures contract (ES).

The volume message The insight volume offers is that it directly reflects the degree to which traders and investors are committing money to the market or liquidating positions. Here are a few unchanged volume statistics from recent market history. From June 1, 2002, to June 2, 2003 (252 days), the lowest unchanged volume reading (just over 1 million shares) occurred on July 5, 2002. The highest reading was 58.3 million shares on September 20, 2002. Sorting the data

www.activetradermag.com • October 2003 • ACTIVE TRADER

FIGURE 2 UP AND DOWN MOVES This table shows how much the S&P 500 index exceeded the previous bar’s high or low after a day with unchanged volume of 24.1 million shares or more. 35 The high is exceeded

30 25 20 15 10 5

from low to high values and looking at the top 25 percent of the unchanged volume results in 63 observations, with the lowest unchanged volume reading of this group just over 24.1 million shares and the highest 58.3 million. Now let’s look at the market action following a high unchanged volume reading. Figure 1 (opposite page) shows the S&P 500 cash index and the unchanged volume level at each day’s close. May 23, 2003, (bar A) was an inside day and the unchanged volume was just under 39 million shares. This reading was the 12th highest reading during the observation period. The following day, the S&P 500 index traded below the low of bar A by 0.09 points, but the market then rallied and the index made a high 17.56 points above the May 23 high. The day after bar B’s unchanged volume reading of 25.6 million, the market traded 2.69 points higher than bar B’s high, then reversed and traded below its low by 3.89 points. Bar C had an unchanged volume reading of 31.8 million, and the index traded 13.73 points above the previous day’s high before reversing and closing near the open. Finally, on bar D the unchanged volume was 32.5 million, and the next bar violated the bar D low by just 0.84 points before turning up. Two of the four examples had sizable moves, one traded both above and below the previous day range, and two made slight down moves before reversing to the up side. Were there any noticeable patterns here? Of the 63 observations with unchanged volume of 24.1 million shares or more, there were only three times the following day was an inside day. Of the 60 remaining examples, only five took out both the previous day’s high and low, forming outside bars. Figure 2 (top, right) shows how much the following day’s low or high exceeded the previous day’s low or high when

0 -5 -10 -15 The low is exceeded

-20

FIGURE 3 DEGREE OF MOVEMENT — UP MOVES For the most part, higher unchanged volume levels were followed by bigger moves above the previous high. 30

The high is exceeded

25 20 15 10 5 0

Lower

Unchanged volume

Higher

FIGURE 4 DEGREE OF MOVEMENT — DOWN MOVES Unlike the higher unchanged volume/up move relationship shown in Figure 3, this table shows little correlation between unchanged volume levels and down moves the next day. 20

The low is exceeded

18 16 14 12 10 8 6 4 2 0

Lower

Unchanged volume

Higher

continued on p. 56

ACTIVE TRADER • October 2003 • www.activetradermag.com

55

FIGURE 5 UP MOVE IN A DOWNTREND The day after this high-unchanged volume day was an up day, one of two days that interrupted a downtrend. S&P 500 index (SPX), daily

1,075.00

1,050.00

1,025.00

1,000.00

975.00 26.7 million shares unchanged 950.00 3 June

10

17

24

Source: eSignal

FIGURE 6 DOWN MOVE IN UPTREND The day after this high-unchanged volume day moved lower, but the market turned back up the next day. 900.00

S&P 500 index (SPX), daily

875.00

850.00

was -10.13 points. Another aspect of this data to consider is the relationship between the unchanged volume level and the degree of the following day’s price movement. Figure 3 (p. 55) shows how the previous day’s high was exceeded according to the level of unchanged volume, from the lowest to the highest. There is a slight bias in that the lower unchanged volume levels appear to have slightly lower extremes, with the exception of the second example from the left, which followed the last day of the year, a day typically with low volume because of the holidays. Figure 4 (p. 55) is similar to Figure 3, except that it displays the amount by which the previous low was broken. There is no correlation between the size of the penetration and the unchanged volume level. Finally, is there any correlation to the trend of the market? Analyzing some of the largest moves suggests the prevailing trend does not exert much influence. For example, Figure 5 (top) shows the S&P rose more than 27 points after the June 14, 2002, unchanged reading of 26.7 million shares while the market was in a downtrend. On March 28, 2003, the unchanged volume reading was 24.8 million shares and the following day the S&P dropped 17 points below the previous day’s low (see Figure 6, left). However, another look at Figure 1 shows two up days following high unchanged volume readings in an uptrending market.

Potential applications 24.8 million shares unchanged

825.00

800.00

10

17

24

31

April

Source: eSignal

the previous day’s unchanged volume exceeded 24.1 million shares. Of the higher highs, 12 were 10 or more S&P points higher, with six exceeding 20 points. The average difference was 9.14 56

points. For days when the previous unchanged volume was greater than 24.1 million shares and the low was exceeded, the market fell more than 10 points 11 times. The average difference

The patterns following high unchanged volume readings can help clue you in to different opportunities or risks by revealing the typical behavior following certain price bars. For example, this analysis suggests if today’s high is approximately 15 or more points above the high of yesterday’s high unchanged volume day, the likelihood of higher prices becomes more remote. Similarly, a low that exceeds the high unchanged volume day’s low by more than 10 points on the downside is a low-probability situation for a short trade. Ý

www.activetradermag.com • October 2003 • ACTIVE TRADER

TRADING Strategies

The TELLTALE spread BY THOM HARTLE

Analyzing the relationship between the E-Mini Nasdaq 100 and the E-Mini S&P 500 can indicate when the broad

T

rend analysis of the stock market can take several forms: measuring an index’s percentage change market is making a genuine move over a period of time, comparing the index to a moving average and so on. Furthermore, some or when it’s faking people out. traders refer to tools such as the number of advancing stocks relative to declining stocks and volume to determine a particular trend’s strength or weakness. Spread analysis, or measuring the TABLE 1 S&P 500 COMPOSITION price difference (or ratio) between two stock indices, is another way to gauge The S&P 500 consists of the 500 largest publicly traded companies measured the robustness of a move in the stock by market cap. It is designed to reflect the broader market. market. By identifying the typical relationship between two indices and recogTop stocks Top groups nizing when that relationship deviates General Electric 3.19% Financials 20.50% from its pattern, you can determine the Microsoft Corp. 3.06% Information technology 16.20% trend and identify potential reversals. Also, although this approach is generalPfizer, Inc. 3.00% Health care 14.80% ly longer term, you can track the Exxon Mobil Corp. 2.67% Consumer staples 11.70% Nasdaq-S&P spread on an intraday basis to insure you are on the right side of Wal-Mart Stores 2.62% Consumer discretionary 11.10% intraday trends. Citigroup Inc. 2.45% Industrials 10.40% This study analyzes the relationship Johnson & Johnson 1.71% Energy 5.80% between two of the most popular stock indices, the S&P 500 (SPX) and the American International Group 1.60% Telecom services 3.90% Nasdaq 100 (NDX), which also underlie IBM 1.59% Utilities 3.00% the two most popular equity index Intel Corp. 1.51% Materials 2.70% futures contracts, the S&P 500 E-Mini (ES) and the Nasdaq 100 E-Mini (NQ), Source: Standard & Poor’s 6/30/03 traded at the Chicago Mercantile 57

www.activetradermag.com • November 2003 • ACTIVE TRADER

TABLE 2 NASDAQ 100 COMPOSITION The Nasdaq 100 is comprised of the 100 largest companies trading on the Nasdaq (financial companies are excluded), based on market cap. The index is heavily weighted with technology stocks. Top stocks

Top groups

1. Microsoft Corp.

10.15%

1. Computer & office equipment 28.39%

2. Intel Corp.

5.10%

2. Computer software/services

28.01%

3. Cisco Systems Inc.

4.49%

3. Telecommunications

11.69%

4. Amgen Inc.

4.28%

4. Biotechnology

11.45%

5. QUALCOMM Incorporated 3.65%

5. Retail/wholesale trade

9.86%

6. Dell Computer Corp.

3.24%

6. Health care

4.51%

7. Comcast Corporation

3.07%

7. Services

3.16%

8. Oracle Corp.

2.82%

8. Manufacturing

1.94%

9. eBay Inc.

2.65%

9. Transportation

0.99%

10. Nextel Communications, Inc.

2.48%

Source: www.nasdaq.com 6/30/03

FIGURE 1 THE SPREAD PERSPECTIVE Calculating the difference between the Nasdaq 100 E-Mini futures (top) and the S&P 500 E-Mini futures (middle) results in a spread chart (bottom) that shows when one index is outperforming the other. Exchange (CME). We’ll use the spread between the S&P and Nasdaq 100 futures contracts in this analysis. We’ll begin by looking at a longer-term use of the Nasdaq-S&P spread before shortening the time horizon and examining ways to identify intraday trend changes.

Nasdaq E-Mini (NQ), weekly 1,500 1,250 1,000

Finding the market leader: S&P safe haven vs. Nasdaq growth The S&P 500 is a capitalization-weighted index of companies with market caps (stock price multiplied by number of shares outstanding) in excess of $3 billion. The larger a company’s market capitalization, the more its stock price affects the index value. The S&P 500 is designed to reflect the risk and return characteristics of the broader, large-cap market. Table 1 (opposite page) shows the top individual holdings and the group breakdown of the S&P 500. The Nasdaq 100 is comprised of the 100 largest businesses, excluding financial companies, traded on the Nasdaq stock market exchange. The index uses a “modified capitalization-weighted” approach, by which stocks are weighted with a proprietary algorithm whenever any stock represents more than 24 percent of the index’s total market value, and/or the combined weight of all stocks with weightings of at least 4.5 percent exceeds 48 percent of the index’s total market value. Table 2 (above) is a recent list of the top Nasdaq 100 continued on p. 59

ACTIVE TRADER • November 2003 • www.activetradermag.com

S&P 500 E-Mini (ES), weekly Divergence between S&P 500 and Nasdaq 100

1,000

800 NQ-ES spread, weekly 300 200 Rising spread is bullish

100 0

April

July

October

2003

April

July

Source: CQG, Inc.

58

A bullish stock market is reflected by an uptrending Nasdaq 100-S&P 500 spread. A bearish market is characterized by a downtrending spread. cent), followed by information technology (16.20 percent). In terms of growth stocks, the technology industry offers far more opportunities than the financial services industry. Microsoft (MSFT) is the most heavily weighted individual holding in the Nasdaq 100 and the second most heavily weighted in the S&P 500. Because it accounts for a large enough percentage in both indices, MSFT has a FIGURE 2 HIGHLIGHTING LEADERSHIP relatively muted effect on the spread between the two. The growth-oriented Nasdaq 100 tends to lead the S&P to the Because of its large technology component, in an upside as well as the downside. When it doesn’t, as was the expanding economy the Nasdaq 100 should lead (i.e., case at points C and F, this lack of leadership can result in rise at a faster rate than) the S&P 500 when the overall trend weakness in the overall market. market is moving higher because more money managers and investors will be attracted to the potential of growth stocks. On the other hand, in a declining ecoG 1,300 nomic environment, financial services companies offer D a safe haven for money (plus, many financial compa1,250 nies pay dividends). That will tend to pull money 1,200 away from Nasdaq stocks and into S&P stocks. As a A result, the Nasdaq 100 should lead the S&P when the 1,150 market is moving lower, as well. 1,100 In other words, a bullish stock market is reflected by Nasdaq E-Mini (NQ), daily an uptrending Nasdaq 100-S&P 500 spread (the H Nasdaq 100 price minus the S&P 500 price). A bearish E stock market will be characterized by a downtrending 1,000 Nasdaq 100-S&P 500 spread. 950 B

individual stock holdings and a breakdown of its most heavily represented groups. The Nasdaq 100 contains a much higher percentage of technology stocks than the S&P. Table 2 shows the computer and

Weekly perspective

Figure 1 (p. 35) shows the Nasdaq 100-S&P 500 relationship from the fourth quarter of 2002 into the second quarter of 2003. The top and middle charts show 300 the Nasdaq 100 E-Mini and S&P 500 E-mini futures, New high respectively, while the bottom panel shows the spread 275 between the two. F Both the Nasdaq 100 and the S&P 500 futures con250 tracts reached new lows in October 2002. However, C during the fourth quarter of 2002, the Nasdaq 100 225 embarked on a substantial rally, bettering its July 2002 NQ-ES spread, daily 200 high; the S&P 500, however, was unable to surpass its summer (August) high. The Nasdaq-S&P spread 21 1 12 19 27 2 9 16 23 1 14 21 28 1 jumped sharply higher, reflecting the Nasdaq 100’s May June July Aug. more accelerated rally. Both markets peaked in Source: CQG, Inc. December 2002 and moved downward until February. The Nasdaq-S&P spread made a slightly lower low office equipment industry group comprises 28.39 percent of in January, just below its December low. As the S&P 500 moved the Nasdaq 100, followed by the computer software/services lower, the spread started to climb again, reflecting the Nasdaq 100’s outperformance relative to the S&P 500. The Nasdaq 100 group at 28.01 percent. The top group in the S&P 500 is financial stocks (20.50 per- made the second low of a double bottom in March 2003, at S&P 500 E-Mini (ES), daily

59

900

www.activetradermag.com • November 2003 • ACTIVE TRADER

wider margin (approximately 1.28 percent vs. .87 percent, based on closing prices on May 6 and May 15). The spread (see line C) was flat between these two peaks, indicating the Nasdaq 100 was no longer outperforming the S&P. This situation was followed by a short correction into the week of May 19. FIGURE 3 INTRADAY INSIGHT Moving forward, the Nasdaq 100 peaked in early June while the S&P 500 peaked in mid-June. This Although intraday price data is more volatile than daily or divergence, indicated by the declining spread (line F), weekly data, the Nasdaq-S&P spread relationship reflects the was part of another correction that lasted until the end same dynamics. Here, the spread (bottom) pushed above its of the month. downtrendline before the Nasdaq or S&P futures did. In July, the Nasdaq 100 surged to new highs, while the S&P 500 made a lower high. This divergence pre1,250 Nasdaq E-Mini (NQ), 30-minute ceded a correction in the broader market. (Interestingly, though, the spread itself surged to new T1 highs, which reflects leadership on the part of the 1,225 Nasdaq and should be a longer-term bullish sign.) The spread does not necessarily indicate a correction is complete; it does not wave a red flag. 1,200 Nonetheless, there is value in being alerted to condiSupport tions that signal a potential correction.

which point both markets rallied into June. The developing spread relationship signaled this period of strength in the overall market: The spread bottomed in October and began forming a series of higher highs and higher lows, indicating a bull-

S&P 500 E-Mini (ES), 30-minute

T1

990 980 970

Support

960 NQ-ES spread, 30-minute 250

T1

240 230 220 Support 25

26

27

30

1 July

2-8:30

Source: CQG, Inc.

ish market environment based on the better performance of the Nasdaq 100 relative to the S&P 500.

Divergence on the daily time frame In addition to gauging the relative strength of the indices when they are moving in the same direction, divergence between the Nasdaq 100 and S&P 500 on the daily time frame can signal potential market corrections. Figure 2 (opposite page) is a daily chart of the E-Mini Nasdaq 100, E-Mini S&P 500 and the spread between the two. Line A shows the Nasdaq 100 rising to slightly higher highs in May while the S&P 500 surpassed its early May highs by a ACTIVE TRADER • November 2003 • www.activetradermag.com

Intraday applications On a very short-term basis, the Nasdaq-S&P spread can help keep you on the right side of intraday trends. The same basic guideline holds, in that the Nasdaq 100 should lead the way, both up and down. Although simple trend analysis, such as drawing trendlines, can help to spot changes, intraday spread charts, like individual markets, are very volatile. For example, during the latter part of June 2003, the stock market was moving sideways. On July 1, the market broke key support levels, but the spread did not break its equivalent level. As the market began to recover, and moved back up through the previous broken support level, the spread broke the down trendline shown in Figure 3 (left). The Nasdaq 100 and the S&P 500 did not break their trendlines until later in the session.

Majority rules Analyzing the Nasdaq 100-S&P 500 spread relationship reflects the idea that if the majority of stocks are not rising — or, if the market-leading stocks are lagging the broader market — the trend may lack staying power. The spread between the Nasdaq 100 and the S&P 500 can function as a gauge of how healthy or weak the overall market is. If one of the major indices is not keeping pace, the spread will fail to make new highs or lows. In those situations, watch for a trend change. 

For other articles by Thom Hartle, visit the Active Trader online store at www.activetradermag.com/purchase_articles.htm. 60

TRADING Strategies

Choosing the proper

TIME FRAME

Intraday traders can use time frames ranging anywhere from one minute to more than an hour. Is there a way to find the most appropriate time frame given your trading approach? Read on to find out. BY THOM HARTLE

T

raders typically incorporate several tools and concepts, such as price patterns, indicators, money management, and entry and exit strategies in a trading plan. But how much consideration do they give time frame? For example, people who trade on an intraday basis might gravitate to five-minute bars without giving the matter too much thought. Five minutes just seems like a reasonably compact, easy-to-reference time frame. But is there really any advantage to five-minute bars over two-minute bars, 10minute bars or any other time frame? The answer depends on the time frame you use to define the trend, which should be different from the time frame on which

you execute trades. This usually means defining trend direction on a longer-term time frame and executing trades in that same direction using setups on a shorter-term time frame — a “multiple time frame” approach. To illustrate this process, we will begin by identifying support and resistance levels with a basic chart pattern. To that end, we need to consider how support and resistance levels occur.

What makes a support or resistance level?

Support is often characterized as a price level at which buyers repeatedly come FIGURE 2 PIVOT POINTS into the market The pivot low and pivot high shown FIGURE 1 WHERE THE VOLUME IS here represent the evaporation of buying and selling at low and high The highest and lowest prices for a given day tend to have the lowest volume. price levels illustrated in Figure 1. Pivot high

1029.25 1028.75 1028.25 1027.75 1027.25 1026.75 1026.25 1025.75 1025.25 1024.75 1024.25 1023.75 1023.25 1022.75 1022.25 1021.75 1021.25 1020.75 1020.25 1019.75 1019.25 1018.75 1018.25 1017.75 5.00K Source: eSignal

61

1

Sell signal is a move below the low of bar 2 or the close of bar 3.

10.00K

15.00K 20.00K Volume

25.00K

30.00K

3

1 2

2

3

Buy signal is a move above the high of bar 2 or the close of bar 3.

Pivot low

Source: Fibonacci Trader

www.activetradermag.com • December 2003 • ACTIVE TRADER

FIGURE 3 TOO MANY TREES, NOT ENOUGH FOREST Although only three are labeled, this five-minute chart contained 32 pivot highs and lows. and hold up prices; one theory is large S&P E-Mini (ES), five-minute institutional traders scoop up cheap 1,030.0 securities or contracts when they drop to 2A 1 a certain level. Resistance is considered 3 the opposite — a level at which sellers 1,028.0 offer large numbers or size into the market, checking a rally. However, Figure 1 (opposite page, far 1,026.0 left) tells a different story, in terms of how the high and low for a trading day are typically set. It shows how many con1,024.0 tracts traded at different price levels in the September E-Mini S&P 500 futures 3 1,022.5 contract on Sept. 5, 2003. It doesn’t show 12 1,022.0 when the market traded at a particular price, only the total volume that occurred at each price level that day. Notice the 1,020.0 highest and lowest prices for the day are the levels with the lowest volume. Figure 1 suggests the market stopped 1,018.0 going up because increasingly higher 123 prices eventually failed to attract enough B buyers willing to pay for the contract at 1,016.0 those levels. Volume decreased as price 9/5/03 9/8/03 advanced to the top of the day’s range, Source: Fibonacci Trader which means the market stopped going up because it ran out of buyers. Similarly, the low for the day occurs because at some point pivot lows and one pivot high have been labeled. Point A is the falling prices fail to attract additional selling — i.e., the market pivot high for the day and point B is the pivot low. stopped falling in Figure 1 because there were no more sellers. Here’s the problem of using five-minute bars: If you look at This process repeats throughout the day, with the market often a daily chart and conclude the trend is up, and you want to go making several new intraday highs or lows. The ultimate high long, what are your chances of spotting the intraday pivot low and low prices can occur at any time during the day. that represents the lowest low of the day — the most favorable How does this behavior manifest itself on a standard price entry point? chart? Figure 2 (opposite page) shows two examples of a threeObviously, you need to reduce the number of intraday pivot bar pattern called a “pivot,” in which price makes its final highs and lows to improve your odds. Using a longer-term move into new territory (a higher high or lower low) on bar 2 intraday time frame would accomplish this. Figure 4 (p. 63) and reverses direction to form bar 3 (making a lower high or shows a 30-minute chart. Now there are just three pivot lows higher low). The first example in Figure 2 is a pivot low and the and two pivot highs. (In this example, bar 1 of the first pivot second is a pivot high. low is using the low of the previous day’s final bar.) In the Based on the conclusions about support and resistance from middle of the chart, it appears the large spike-down bar would Figure 1, the ultimate high or low reached in bar 2 and the subbe bar 2 of a pivot low (these bars are marked A, B and C), but sequent retracement of bar 3 in a pivot pattern is the result of there is no overlap between bar A and bar C. The pivot concept price exhaustion in that direction. With the completion of bar is based on the idea that a market is not attracting sellers near 3, the pivot high or low is in place. An early warning a pivot is the pivot low area. In this case, the fact that bar B sold off so forming is the violation of bar 2’s high (for a pivot low) or bar sharply and bar C did not retrace enough to overlap with bar 2’s low (for a pivot high). A is a sign bar C is just a correction of bar B, and not the beginOnce a pivot low or high is in place, the market has estabning of a reversal. (If the first bar gaps lower, as it did here, it lished support or resistance at that price level. means the trading occurred in the evening Globex session, so the previous day’s bar would be bar 1.)

The daily pivot

Depending on the intraday time frame, any number of pivot lows and highs can form throughout the trading day. However, only one pivot high can be the high for the day and only one pivot low can be the low for the day. For example, Figure 3 (above) shows a five-minute chart of the September 2003 E-Mini S&P500 futures. There are 16 pivot highs and 16 pivot lows in this chart; to avoid clutter, only two ACTIVE TRADER • December 2003 • www.activetradermag.com

Five bars a day keeps the guessing away

Moving to an even longer-term time frame, Figure 5 (p. 63) shows an 81-minute bar chart that divides each day into five price bars. Now, only two pivot lows and one pivot high appear. Because a pivot high or low pattern consists of three bars, continued on p. 63 62

FIGURE 4 REDUCING THE NUMBER OF PIVOTS Increasing the time frame to 30-minute bars reduces the number of pivot highs and lows. S&P E-Mini (ES), 30-minute

2

1,030.0

3

1

1,028.0

1

1,026.0

1,024.0

3

2

A

3 1,022.5 1,022.0

1

2

1,020.0

C 1 B

3

1,018.0

2 1,016.0 9/8/03

9/5/03 Source: Fibonacci Trader

FIGURE 5 THE 81-MINUTE BAR Using 81-minute bars divides a trading day into five bars, reducing the num ber of pivot highs and lows to one each. S&P E-Mini (ES), 81-minute 1,030.0

2 3

1

1,028.0

1,026.0

1 3

1,024.0 1,022.5 1,022.0

2

1,020.0

3

1

1,018.0

2 9/5/03 Source: Fibonacci Trader

63

9/8/03

1,016.0

breaking the day into five 81-minute bars increases the chances of identifying the ultimate high or low for the day. If we were using five-minute bars, the chances of identifying the ultimate high or low during the day would be remote because of the high number of pivot lows and highs. The choice of 81-minute bars is most appropriate for trading if you are following the trend on the daily time frame (a multiple time frame approach). For example, if the daily trend was defined as up based on the market closing above a rising 20-day moving average, you could enter on pivot lows on the 81minute bar time frame.

Multiple time frames In Figure 6 (opposite page), the daily range is plotted as boxes that “encapsulate” the five 81-minute bars for each day, along with a 20-day moving average (plotted as a “step” line). In essence, the encapsulation rectangles are like transparent daily bars that allow you to see the intraday action on the 81-minute bars. At point A, the daily bars form a pivot low (labeled 1, 2 and 3); bar 2 temporarily penetrates the 20-day moving average. The combination of the rising moving average and the formation of a pivot low on the daily time frame signals an uptrend. Trades can be based on the formation of pivot lows on the 81-minute time frame, entering on the close of bar 3 (or on a move above bar 2’s high) of an intraday pivot, and risking a move to the low of the entry bar. However, if this represents too much risk and you prefer to trade shorter-term price bars, you can work backwards to set up a similar multiple time frame analysis on the time frame of your choosing. Let’s use five-minute bars as an example. Using the same approach of five bars of the short-term time frame per one bar of the longer-term time frame, you would use 25-minute bars to define the trend and look for pivot lows and highs on the five-minute bars to enter trades. (Using 25-minute bars does leave one unaccompanied five-minute bar at the end of the trading day, however.) Figure 7 (opposite page) shows fiveminute bars encapsulated on a 25minute basis. Each red rectangle repre-

www.activetradermag.com • December 2003 • ACTIVE TRADER

FIGURE 6 LOOKING AT MULTIPLE TIME FRAMES

sents a 25-minute bar and pivot lows and highs on the 25-minute bars will be used to define the trend. The first 25minute bar of the day gaps down, but still qualifies as bar 2 of a pivot low. A pivot low is established when the market trades above the high of the 25minute pivot bar 2, which signals a low on the longer-term time frame and a rising trend. At this point, you would look for a pivot low on the five-minute bars to go long. Again, you can buy as the market moves above the bar-2 high of the fiveminute pivot low, with a stop at or near the low of the entry bar. In this example the market did advance until it formed a 25-minute bar pivot high, after which it tumbled hard, forming only three five-minute pivot highs (two of which are contained in the same 25-minute encapsulated bar) during the decline. These three pivot highs were the better trade setups — everyone wants to catch this kind of sharp decline — but such opportunities are rare. Another 25-minute pivot low formed after the sharp decline, signaling the trend was turning back up, and a number of pivot lows formed on the fiveminute bars.

Here, 81-minute bars are “encapsulated” by rectangles that function as transparent daily bars allowing one to see the price action of two distinct time frames. S&P E-Mini (ES), 81-minute 1,030.0

1,022.5 1,020.0

Pivot low

1,000.0 Pivot low

3 1

Encapsulation is a patented trademark of Robert Krausz.

990.0 Pivot low

Moving average

2

A

8/25/03

9/2/03

9/8/03

980.0

Source: Fibonacci Trader

FIGURE 7 BACK TO THE FIVE-MINUTE TIME FRAME Using the approach from Figure 6, the five-minute bars here are encapsulat ed by the 25-minute range, which is the time frame that defines the trend.

Don’t put the cart before the horse Many traders select a time frame and struggle to make their trading fit that time frame, rather than first deciding how they want to trade and then picking an appropriate time frame. When selecting a time frame on which to trade, make your decision based on a multiple time frame perspective. In this case, dividing a longer-term (daily) time frame into five shorter-term (81-minute) periods and using a threebar pivot pattern to define trends and support and resistance provided the framework for a simple trading approach. Trading in the direction of the trend of the longer-term time frame and using chart patterns or indicators on the shorter-term time frame for entry signals should increase your success. Ý

1,010.0

Encapsulation

S&P E-Mini (ES), five-minute

2

1,030.0

3 Trend is down

1

1,028.0

1

1,026.0

1

2

3

Pivot high 1,024.0

3 2

1,022.5 1,022.0

Pivot low

Trend is up 1,020.0

1

3 2

1,018.0 Pivot low Trend is up

9/5/03 Source: Fibonacci Trader

ACTIVE TRADER • December 2003 • www.activetradermag.com

1,016.0 9/8/03

64

TRADING Strategies

The method trader The trading world is filled with truisms and generalities, but there are no magical indicators or secret recipes when it comes to trading well. Profitable trading is grounded in a process — how you approach your trading approach.

BY THOM HARTLE

65

www.activetradermag.com • April 2004 • ACTIVE TRADER

Knowledge is experience, and the essence of experience is self-reliance. — T.H. White, The Once and Future King

W

hen in comes to consistently profitable trading, there are many roads leading to the promised land, but as the saying goes, “Many are called, but few are chosen.” New and struggling traders are always looking for something — an elusive insight or technique — that will put everything into focus and allow them to excel. Like virtually any other profession, though, the answer is not some bit of mysterious knowledge or a perfect trading tool. Proficiency boils down to three steps: Specialization, preparation and execution. This should not come as a surprise. For example, when we need medical attention for an out-of-the-ordinary problem, we seek a physician who specializes in the field of medicine specific to our affliction. The physician will prescribe a set of procedures, be they medicinal, surgical or otherwise, that have shown a high probability of success in curing the disease or treating the symptoms we have presented to them. We rightfully expect when a physician prescribes a course of treatment he or she has the proper knowledge, training and skills to do so; and that the treatment is not unproven or experimental, unless we agree to it. Unfortunately, we do not set the same high standards for ourselves when we attempt to make money in the markets. Think about what so many traders and investors do — place a trade based on the latest news event, after reading a newspaper article, or seeing something on television. Compare this to a visit to your doctor’s office. What would you think if your doctor, if asked for details about the medication he was prescribing, could not provide any information regarding its efficacy because it was something new he’d just seen on TV the night before? Part of the problem is trading does not have the relatively uniform education, training and regulation that are the norm in most other professions. But that is not the primary issue. The reality is traders, because they are in an essentially individual and entrepreneurial business, have to take responsibility for everything they do. And the most critical responsibility is knowing the probabilities associated with every trade they make. Many people believe the key to making money is finding the perfect indicator or pattern. This is not the case. The key is knowing the probabilities of what the market will do in the aftermath of any price pattern or indicator, and having set procedures to make the most of that knowledge. To do that, you have to work through a great deal of material to find techniques that fit your needs. It’s the trading equivalent of putting yourself through medical school and settling on your specialty.

Determining your expertise It takes a considerable amount of research before you can make an informed decision about your area of specialization. It is only after having acquired a broad background continued on p. 67

ACTIVE TRADER • April 2004 • www.activetradermag.com

66

FIGURE 1 TESTABLE TRADE SETUP The trade setup shown here — whether or not it turns out to have merit — has an advantage over many trading ideas because it has specific, quantifiable attributes that can be tested. (The pivot low is labeled “1, 2, 3.”) 38.50

Nasdaq 100 index-tracking stock (QQQ), 30-minute

38.40

Upper Bollinger Band 38.30 38.20 38.10 38.00 37.90 37.80

1

Lower Bollinger Band

37.70

3

37.60

2

Tagged the lower Bollinger Band

37.50 Rising long-term moving average 37.40 1/16/04

1/15/04 Source: Fibonacci Trader

FIGURE 2 GANN LINE NO.1 When considering a trading technique, you should always ask yourself if it can be converted into precise, testable rules. This Gann-based technique would not pass the test. Nasdaq 100 index-tracking stock (QQQ), 30-minute

2 1

3 Pivot high

Entire bar above 1x1 line

38.50 38.40 38.30 38.20 38.10 38.00 37.90

Trend reversal

1 3 2 1/15/04 Source: Fibonacci Trader

67

37.80 37.70 37.60 37.50 1/16/04

that you can narrow your focus and select techniques that fit your risk-reward temperament. This balance is an important issue to consider as you work your way through various trading approaches. Your tolerance for risk and goals for reward will impact the markets you trade and the time frame on which you trade them. There is no “correct” time frame to trade; the goal is to find the one you are most comfortable with. Consider the differences between day traders and position traders. Day traders most likely cannot cope with overnight risk and want to be flat at the end of every trading session, starting each day fresh. They do not like to see big profits turn into small profits — or worse, losses — because of overnight events. Position traders are more likely to consider intraday price action as meaningless noise — the product of the random nature of the market. They are more at ease holding positions and attempting to capture longer-term trends and less comfortable taking multiple positions during a trading day. Regardless of the time frame, as you study various trading concepts, market tendencies and patterns, you will begin to identify some that appear to have consistently favorable outcomes. In other words, you will recognize certain aspects of market behavior and think, “I’ve seen this happen before, and the market always seems to rally.” Now you’re onto something. For example, you might be studying a technique that combines indicators and price patterns. Perhaps, you’ve determined if the market is in an uptrend (based on a set moving average value) and price tags the lower 10-day Bollinger Band and forms a pivot low (a three-bar support pattern), there is a tendency for the market to rally (see Figure 1, top). Your goal is to determine the precise probabilities of this tendency and determine whether it merits trading. There is a subtle but important point to absorb here. This pattern has specific attributes that can be defined and tested (in the preparation phase). This is not always the case with “setups” traders use. There is no lack of vague and ambiguous trading concepts and rules: “Look for a breakout of a tight consolidation,” “Buy when a very large bar forms and prices closes near the low,” and so on. But without precise definitions of what constitutes a “tight consolidation,” a “very large bar” and “near the low,” there is no way to identify past examples of these patterns and determine the odds of what will happen after them. And without that information, how can you trade? In Figure 2 (left) for example, an upward 1x1 “Gann line” (which is a 45-degree trendline that is supposed to represent price moving in equilibrium with time) is drawn off a pivot low (a three-bar support pattern consisting of a low with a higher low on either side). A trader might have a rule that if an entire bar’s range is above the upward 1x1 Gann line (signaling a rapidly rising trend), it indicates the trend may be vulnerable to a reversal. Then, if a pivot high (the opposite of a pivot low) forms, go short if the market breaks the rising 1x1 line. However, a 1x1 Gann line reflects a price-to-time ratio — www.activetradermag.com • April 2004 • ACTIVE TRADER

The key to making money is knowing the probabilities of what the market will do in the aftermath of any signal generated by a price pattern or indicator. e.g., one point or price movement per one time unit — and this ratio can change simply on the basis of how a chart is constructed. Figure 3 (right) is the same price chart, but drawn on a different scale. There are subtle but critical differences between this chart and Figure 2 — most significantly, the break of the 1x1 line occurs at different points on the two charts because of their different price scales. As a result, depending on how your software plots charts, different signals would occur using the same trading “rules.” (The solution in this case would be an additional rule that requires the price-to-time ratio to always be a fixed number. This way, every chart will always create the same signals.) So, while working through a technique, you must always ask yourself if it is something that can be converted to precise, testable rules. An example of a testable one-bar pattern is: Today’s high is the highest high of the past 10 bars and is at least 1.5 percent above yesterday’s high, today’s low is below yesterday’s low, and today’s close is in the lowest 10 percent of the bar. The ability to convert market patterns into precise definitions, which in turn can be translated into trade setups and procedures, enables you to test their outcomes and determine their value. This determination is the goal of the preparation phase.

Preparation: Beyond “system testing” Testing trade setups is hardly a new idea, and there are numerous software programs that expedite the process of designing and implementing trading systems. Sometimes, however, a great deal of computer power can be a bad thing. We can miss opportunities if we rely on standard systemtesting programs to do all our analysis. Many new traders essentially take a trading idea and “ask” the computer to check it out. If the summary test statistics — net profit, maximum drawdown, etc. — indicate poor performance, a trader will likely toss out the idea. However, if the testing had been a little more hands on — for example, incorporating direct observation of the outcome of trades on charts and extending the performance analysis beyond the confines of a typical analysis program — then, after a little tweaking, a successful trading approach might emerge after all. All it takes to perform valuable analysis is a spreadsheet such as Excel. First, print out a series of charts with the signals that are the basis for your potential trades. Next, import the same data into Excel, or at least the date, time (if intraday), open, high, low and close. Then you can set up columns to log various trade setups, such as “Setup 1-buy,” “Setup 2-buy,” “Exit 1,” “Exit 2,” etc. Most importantly, you can create a column for the maximum favorable excursion (MFE) and maximum adverse excursion (MAE) for each trade. The MFE is the difference between the setup’s entry price and the position’s largest open profit; the ACTIVE TRADER • April 2004 • www.activetradermag.com

MAE is the difference between the entry price and the position’s largest open loss. With this information, you can determine the typical outcomes of your trade setups. Figure 4 (p. 32) shows an Excel spreadsheet containing the information for a sample trading approach. The first two columns contain the date and time, the next four contain the setup’s indicator values, and the next four show the open, high, low and close prices. The next column is used to enter the trade number (in the row of the bar on which the trade occurred). You could also log this number on the appropriate bar on a chart, either a printed or electronic version. The setup for this trade, which is based on a set of rules that indicate a purchase on the close of the bar, is labeled L-1. The next two columns contain the MFE and MAE for the FIGURE 3 GANN LINE NO. 2: SAME “SETUP,” DIFFERENT RESULT Because the Gann line is inconsistent and can change depending on how a chart is constructed, the same price action shown in Figure 2 produces different results here sim ply because the chart is drawn using a different scale. Nasdaq 100 index-tracking stock (QQQ), 30-minute 38.60

Pivot high

2

Entire bar above 1x1 line

1

3

38.40 Trend reversal 38.20

38.00

37.80

1

3 37.60

2

37.40 1/15/04

1/16/04

Source: Fibonacci Trader

trade. For example, trade number 35 occurred on the close of the 12:00 bar. The position reached its maximum open profit of 18 cents on the 14:30 bar; this value is entered on the same row as the trade number in the MFE column. The trade reached its largest open loss of -6 cents on the next bar, and this MAE continued on p. 69 68

FIGURE 4 AN EXCELLENT SOLUTION Spreadsheet analysis allows you to perform a great deal of hands-on analysis. This example shows the trade date and time, indicator values, price data, trade number, setup, MFE and MAE values, profit or loss, and reason for exit. After compiling this information for all your trades, you can then sort the data and perform in-depth analysis that reveals key informa tion about profit targets, stop levels and other aspects of a strategy.

Source: Excel

value is entered in the same row in the MAE column. Because the trailing stop was not hit and positions are not held overnight, the trade was exited at the close. Use the same line for key information about each trade (the highlighted rows). This will help later when you want to sort the data by trade number. The final two columns contain the trade’s profit or loss (P/L) and the reason for the exit. The other three trades were based on a different setup (L-2) and two of them were stopped out using a trailing stop. The last trade shown was exited on the close. Anatural question is how many trade examples are necessary to draw meaningful conclusions about a trade setup. But the more important issue is different types of market conditions. First, you should review a setup using price data that has uptrends, downtrends, trend reversals and trading ranges. Avoid testing in a period dominated by one price direction. That said, gathering information on at least 100 trades is a good start. At this point you can begin to do some interesting work. For example, you can copy all the trades and paste their values in another spreadsheet page and sort the data different ways. For example, you could sort by trade number, then by MFE to see if there is a price target value that has a high probability of being hit on a regular basis. In Figure 4, the MFE was more than 10 cents for three of the trades. If you had 100 trade examples, you might find the market was making a favorable move of 10 cents at least 60 percent of the time. If the corresponding MAE is low — meaning, the trade isn’t going against you more than it is going in your favor — then you have a potentially viable trade idea. Similarly, you could sort by MAE and determine at what point you should abandon a trade because a majority of trades that hit a particular MAE level do not recover to be winners. Other ideas to consider are sorting trades by the type of setup or time of day to determine if there is a particular time that works best for a particular setup. 69

None of this analysis can be completed until you have specialized on a trade approach and have converted it into precise entry and exit rules. But once you have completed these first two steps — specialization and preparation — you will have a very clear understanding of the nature of your strategy. You might discover it is not as good as it initially appeared, and avoid rushing into the market and losing money. Also, by manually working through the charts and logging the information in a spreadsheet, you have the opportunity to discover a slight variation on your original idea that may be an improvement. This is less likely to occur if you let the computer do all of the work. “Pattern probabilities” (opposite page) illustrates another way to use a spreadsheet to measure the probabilities of trade setups and determine their value. Finally, all this work is an excellent way to develop good skills for trading when the market is actually open. It is similar to a basketball player spending hours in the gym shooting nothing but foul shots so he is confident and behaves automatically during the pressure of a real game. Once you have tested your ideas and identified high-probability targets from the entry setups and risk points for managing the trade, you are ready for the execution phase.

Implementing the strategy At this point, you have a collection of procedures to follow and can trade objectively and consistently. You have moved away from trading by the seat of your pants, jumping from one technique to the next and wondering why you experience inconsistent results using a patchwork collection of strategies. With this framework you no longer have to concern yourself with forecasting the markets; simply follow your tested procecontinued on p. 70

Additional research The MFE and MAE analysis concept is from John Sweeney’s book, Campaign Trading: Tactics and Strategies to Exploit the Markets (1996, John Wiley & Sons). Trading in the Zone by Mark Douglas (2001, Prentice Hall Press) is a good source of information on the value of thinking and trading in probabilities. “On-target trading,” Active Trader, July 2001, p. 44. “Taking the guesswork out of stop orders,” Active Trader, October 2001, p. 58.

www.activetradermag.com • April 2004 • ACTIVE TRADER

dures. This will relieve you of the psychological pressure of being right or wrong on any one trade. You will be trading based on probabilities that have been proven over dozens of trades. But that doesn’t mean the work is over.

Going forward It is important to continue to update your spreadsheet with real-time trades. Markets change, and if you begin to see results that are inconsistent with your original analysis, you can spot this before it becomes a real problem.

The three steps outlined here — specialization, preparation and execution — reflect the same basic process that carries people in a wide range of disciplines from the novice to professional stage. Moving from broad-based approaches to specialized techniques that are converted to procedures with probability-based outcomes puts you in a position to succeed. It takes a lot of work, but the end result is having the skills to be consistent, regardless of the trading approach you use.Ý

Pattern probabilities

A

nother way to use a spreadsheet is to determine the probabilities of a price pattern before you even design specific rules for trading it. Figure 5 (below) shows an excerpt from a spreadsheet that shows several statistics — the average price move, median price move, the maximum price move and the minimum price move — in the three days following the completion of a price pattern. To perform this kind of analysis, you must first import the open-high-low-close price data for the period you wish to test (the “open” column is hidden here). The period here spans May 31, 2000, to Dec. 13, 2000; many of the rows are hidden to conserve space. Column F contains the pattern’s conditions. In Excel, it is easy to string together several “If” conditions that describe a pattern. In this case, the pattern is a bar with three conditions:

These conditions are shown in the formula bar (for cell F22) as: 1. (C22-C21)/C21>0.01 2. E22