FUTURES
Trading System Lab
Adaptive RSI system for futures
FIGURE 1 TRADE EXAMPLE Applying Bollinger Bands to the RSI creates dynamic overbought and oversold levels that caught two good trading opportunities in the S&P 500 E-Mini futures.
Market: Futures. System concept: The Relative Strength Index (RSI) is a momentum indicator that oscillates between zero and 100, where values above a certain level (default 70) indicate overbought situations and values below 30 indicate the opposite. The indicator’s default lookback period is 14. (See “Key Concepts and Definitions,” p. 81, for more information on the RSI.) Typically, the indicator’s overbought and oversold levels are fixed. Standard RSI systems usually issue buy signals when the RSI exits the oversold area (i.e., crosses above 30) and give sell signals as soon as the RSI leaves the overbought area (i.e., drops below 70). This system experiments with changing the overbought/oversold levels depending on market condiSource for all figures: Wealth-Lab Inc. (www.wealth-lab.com) tions. For example, during low-volatility periods it is usually better to set the boundaries at, FIGURE 2 EQUITY CURVE say, 60 and 40, because the indicator is less likely to The system was profitable overall, but it did have one substantial fluctuate extremely higher or lower during such peridrawdown period. ods. Conversely, very volatile periods might require levels of 80 and 20 to avoid generating too many false signals. This system changes the RSI’s oversold/overbought boundaries dynamically. (As the testing will illustrate, doing this converts a losing system into a profitable one.) To accomplish this, the system applies Bollinger Bands (see “Key Concepts and Definitions,” p. 81) to the RSI itself. As a result, instead of using fixed overbought and oversold levels, these readings are defined by the dynamic Bollinger Band calculation — as the bands change according to the RSI’s volatility, so do the overbought/oversold levels. Rules: 1. Go long next day at market if the 14-day RSI crosses above the lower Bollinger Band, using a 100-day simple moving average and two standard deviations for the Bollinger Band parameters. 2. Exit long next day and go short at market if the 14-day RSI crosses below its upper Bollinger Band. 3. Place a stop-loss four times the 10-day average true range (ATR) from the entry price. Figure 1, which shows trades in the S&P 500 E-Mini futures (ES), illustrates how the RSI bands adapt to changing volatility. In August 2003, the lower band was at 44 and the higher band was at 74. On Aug. 8 the RSI crossed above its lower band, issuing a buy signal; a standard RSI system with a fixed oversold level of 30 or 40 would not have caught this trade opportunity. The system stayed in this trade until Jan. 12, when the RSI crossed below the upper band and the system went 68
short. It exited when a second crossover above the lower band occurred on March 18. Money management: Risk a maximum of two percent of account equity per trade. The number of contracts is calculated using the “basis price” (the closing price of the entry bar), the stop-loss level, and the dollar value of a one-point move in a particular contract. www.activetradermag.com • November 2005 • ACTIVE TRADER
FIGURE 3 DRAWDOWN CURVE For example, if a contract has a point value of $250, assume the system goes long at $100 (the basis price) with an initial stop-loss at $90. To determine the trade’s dollar risk, multiply the point value ($250) by the difference between the basis price and the risk-stop; in this case $250*$10 = $2,500. If the portfolio’s equity at the time of the trade is $1,000,000, because we are risking two percent of our total equity (or $20,000), we would buy eight contracts. Had total equity been less than $125,000, we would not have been able to take this position because its dollar risk would exceed the system’s two-percent equity risk. This position-sizing method avoids risky trades with the potential to wipe out the account. Starting equity: $1,000,000. Deduct $20 commission per round-trip trade per contract. Apply two ticks of slippage per order.
Other than the 2002-2003 drawdown, the system suffered mostly minor setbacks.
FIGURE 4 ANNUAL PERFORMANCE Three of the 10 years in the test period were losers; six of the seven profitable years had annualized profits of more than 10 percent.
Test data: The system was tested on the Active Trader Standard Futures Portfolio, which contains the following 20 futures: British pound (BN), soybean oil (BO), corn (C), crude oil (CL), cotton (CT), Nasdaq 100 E-Mini (NQ), S&P 500 E-Mini (ES), five-year Tnote (FV), Euro Forex (EC), gold (GC), Japanese yen (JY), coffee (KC), wheat (W), live cattle (LC), lean hogs (LH), natural gas (NG), sugar (SB), silver (SI), Swiss franc (SF), and 30-year T-bonds (US). The test used ratio-adjusted data from Pinnacle Data Corp. Test period: January 1995 until January 2005. Test results: The portfolio equity curve (Figure 2) shows two nice periods during which equity increases steadily and drawdowns are minor. However, between these periods (from January 2002 until January 2003) a large 40.8-percent drawdown occurs.
STRATEGY SUMMARY Profitability Trade statistics Net profit ($): 1,003,130.88 No. trades: 493 Net profit (%): 100.31 Win/loss (%): 52.54 Exposure (%): 18.42 Avg. trade (%): 1.50 Profit factor: 1.18 Avg. winner (%): 10.87 Payoff ratio: 1.25 Avg. loser (%): 8.71 Recovery factor: 1.40 Avg. hold time (days): 79.01 Drawdown Avg. hold time (winners, in days):101.78 Max. DD (%): -40.79 Avg. hold time (losers, in days): 53.80 Longest flat days: 462 Max. consec. win/loss: 10/9 LEGEND: Net profit — Profit at end of test period, less commission • Exposure — The area of the equity curve exposed to long or short positions, as opposed to cash • Profit factor — Gross profit divided by gross loss • Payoff ratio — Average profit of winning trades divided by average loss of losing trades • Recovery factor — Net profit divided by max. drawdown • Max. DD (%) — Largest percentage decline in equity • Longest flat days — Longest period, in days, the system is between two equity highs • No. trades — Number of trades generated by the system • Win/Loss (%) — The percentage of trades that were profitable • Avg. trade — The average profit/loss for all trades • Avg. winner — The average profit for winning trades • Avg. loser — The average loss for losing trades • Avg. hold time — The average holding period for all trades • Avg. hold time (winners) — The average holding time for winning trades • Avg. hold time (losers) — The average holding time for losing trades • Max. consec. win/loss — The maximum number of consecutive winning and losing trades www.activetradermag.com • November 2005 • ACTIVE TRADER
Because of this drawdown, the overall performance is “only” 100 percent after 10 years. The drawdown curve in Figure 3 shows how dramatic the continued on p. 70
PERIODIC RETURNS Avg. Sharpe Best Worst Percentage Max. Max. return ratio return return profitable consec. consec. periods profitable unprofitable Weekly Monthly Quarterly Annually
0.16% 0.70% 2.09% 9.21%
0.52 7.61% -7.64% 0.50 12.20%-13.25% 0.51 17.05%-23.15% 0.42 49.61%-28.01%
50.57 60.00 60.00 70.00
11 11 8 4
14 6 3 1
LEGEND: Avg. return — The average percentage for the period • Sharpe ratio — Average return divided by standard deviation of returns (annualized) • Best return — Best return for the period • Worst return — Worst return for the period • Percentage profitable periods — The percentage of periods that were profitable • Max. consec. profitable — The largest number of consecutive profitable periods • Max. consec. unprofitable — The largest number of consecutive unprofitable periods Trading System Lab strategies are tested on a portfolio basis (unless otherwise noted) using Wealth-Lab Inc.’s testing platform. If you have a system you’d like to see tested, please send the trading and money-management rules to
[email protected]. Disclaimer: The Trading System Lab is intended for educational purposes only to provide a perspective on different market concepts. It is not meant to recommend or promote any trading system or approach. Traders are advised to do their own research and testing to determine the validity of a trading idea. Past performance does not guarantee future results; historical testing may not reflect a system’s behavior in real-time trading.
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FUTURES
Trading System Lab
continued from p. 69
FIGURE 5 EQUITY CURVE — STANDARD RSI SYSTEM drawdown peak is at the beginning of 2003. However, the rest of the test period contains relatively small drawdowns, from which the system recovers quickly. Seven of 10 years in the test period are profitable (Figure 4, p. 69) and six show annual profits of more than 10 percent. The system’s relatively low average profit/loss of 1.50 percent makes this system vulnerable to both higher commission costs and slippage. The system’s exposure (18.4 percent) is not too high; perhaps it’s worth considering increasing the position size to improve profits. However, this is a double-edged sword as risk and drawdown will increase, too. To get an idea if the dynamic overbought-oversold levels provided by Bollinger Bands improved the RSI’s performance, we also tested the system using fixed levels of 30 and 70 (all other parameters and rules were the same). Figure 5 shows this system’s equity curve: It was a consistent loser over the entire 10-year test period. Bottom line: Replacing fixed RSI overbought and oversold levels with adaptive levels converted a losing indicator/system into a profitable one. The adaptive system’s relative success highlights the potential benefits of incorporating ideas that respond to changing market conditions, including volatility fluctuations. -José Cruset of Wealth-Lab
Using standard, fixed RSI overbought and oversold levels produced terrible results. Every year was a loser, and the system destroyed 65 percent of its initial equity.
