How to Trade – Book Review - Kenneth L. Grant, Trading Risk
In depth book review of Trading Risk, authored by Kenneth Grant. Focus on chapters 2, 3, 4 and 7, which makes up about 6...
How to Trade – Book Review - Kenneth L. Grant, Trading Risk Managing the performance of your trading account must go beyond the discipline of money management. While money management remains critical, it is a subset of the total picture of managing your trading account’s profit and loss. That total picture is what Kenneth L. Grant aptly paints in his book, Trading Risk. Total performance management of trading must treat the profit and losses in a trading account at 2 levels – the portfolio level and at the individual trade level. Kenneth L. Grant is Cheyne Capital’s Global Risk Manager and notable pioneer in designing risk control and capital allocation programs for global hedge funds. Typically with most literature on risk management, you would expect complex numerical formulas beyond the reach of most retail traders who do not have a mathematical background. Kenneth writes in a style that does emphasize the robustness of arithmetical reasoning, but helps you visualize the various types of risks with ample graphs. The content is not so numerically oriented that it is beyond the grasp of anyone who is comfortable with Statistics 101. There are adequate reader reviews on Amazon and Google Book Search, to help you decide if you will get the book. For those who have just started or are about to read the book, I’ve summarized the core concepts in the larger and essential chapters to help you get through them quicker. The number on the right of the title of the chapter is the number of pages contained within that chapter. It is not the page number. The percentages represent how much each chapter makes up of the 244 pages in total, excluding appendices. Chapter 1: The Risk Management Investment. Chapter 2: Setting Performance Objectives. Chapter 3: Understanding the Profit/Loss Patterns over Time. Chapter 4: The Risk Components of an Individual Portfolio. Chapter 5: Setting Appropriate Exposure Levels (Rule 1). Chapter 6: Adjusting Portfolio Exposure (Rule 2). Chapter 7: The Risk Components of an Individual Trade. Chapter 8: Bringing It on Home.
18 18 44 28 24 22 58 32
7.38% 7.38% 18.03% 11.48% 9.84% 9.02% 23.77% 13.11%
Focus on chapters 2, 3, 4 and 7, which makes up about 61% of the book. These chapters are relevant for practical trading purposes. Here are the key points for these focus chapters, which I’m summarizing from a retail option trader’s perspective. Chapter 2: Setting Performance Objectives. There are 3 types of targets to set at the portfolio level. Optimal Target Return is the complete achievement of the “ideal” measure. For e.g. generating trading income that is 2-3 times your household expenses, to evaluate the practicality of trading for a living. Nominal Target Return is the lowest acceptable measure, achievable under most conditions, excluding a catastrophic market event. For example, your trading account should be yielding a rate of return above the historical returns of the S&P 500 of between 10%-12%, before the financial pandemic. Otherwise, why bother with managing the Greeks of option positions, if you are failing to beat a widely accepted benchmark for Equities? Stop-Out Level is when cumulative losses reach an absolute amount below the Nominal Target Return, making it necessary to stop trading altogether for a period. As a guideline, this is 10% x [(60% x Cash Balance at the start of the year); or Net Liquidating Value]. For example, for a $50,000 trading account, 10% x (60% x $50,000) = $3,000 of losses in total, is the absolute amount to halt trading. Why 10%? Blowing up your account is final. There is no bail out package. Stop trading for 2-3 months and reassess your ability to consistently trade profitably, before committing the remaining capital to risk in the markets. Chapter 3: Understanding the Profit/Loss Patterns over Time. This chapter evaluates the profit and loss in terms of Time Units (typically day and week) feeding into Time Spans, Average Profit versus Average Loss, Standard Deviation, Sharpe Ratio, Median P/L, Percentage of Winning Days versus Losing Days, Drawdown and Correlation Analysis. This section focuses on the core metrics of trade performance, for a given period: Win/Loss Probability = Number of Winners / Total Trades. This measures your accuracy in trade selection. Average Winner = Total $ value of Wins / Number of Winners.
Average Winner = Total $ value of Losses / Number of Losers. Average Winner / Average Loser = Impact Ratio, measuring how responsive you are in allowing winners ride higher and how quick you are in cutting losses. Performance Ratio = (Win / Loss Probability) x (Average Win / Average Loss), which is a combined metric of accuracy and responsive measuring overall portfolio efficiency. Sustaining the Performance Ratio above 1.00 is key in stepping up the allocation per trade by +1%; or, stepping down the allocation per trade by -1% as the ratio drops below 1.00. In calculating the metrics, it becomes clear if your strengths are in trading long debit spreads, short credit spreads, directional trades (be it up/down) or non-directional trades. Trade in line with what you are intuitively profitable at, be that debit/credit spreads or directional/non-directional trades. The metrics help you guard against trading counter-intuitively in opposition to your strengths. Chapter 4: The Risk Components of an Individual Portfolio. The emphasis of this chapter is on Historical Volatility, Correlation and Implied Volatility and Value at Risk (VaR). While it is educational to understand how these various risks can be aggregated up into a single, portfolio measure of exposure, it is not useful for option traders trading retail portfolios from home. Why? To re-simulate the test scenarios on the portfolio cited in the text, requires specific types of data. The Account Statement of most retail option trading platforms only record each trade’s profit, loss and date. The additional data of each day’s Historical Volatility, Implied Volatility, Correlation coefficient values and Standard Deviation/Variance values will need to be sourced from outside the trading platform. Unless you are trading multiple portfolios on behalf of other individuals, VaR simulations make sense. If you are trading just your own portfolio, it more useful to get an Implied Volatility tool that forecasts IV rising or falling by X% over 30-60-90-120 days. This is a much more affordable way to assess the total impact of IV and Correlation in IV on your portfolio. Chapter 7: The Risk Components of an Individual Trade. The section to focus on here is the Core Transaction-Level Statistics. This includes the Trade Level P/L, Holding Period, Average P/L, Weighted Average P/L, Average Holding Period, P/L by Security or Asset Class and Long Side P/L versus Short Side P/L. The main point here is to monetize the Average Holding Period of a long or short position. For example, as a guideline: ❑ Credit spreads are typically identified for entry between 30-45 days. Does your historical profit show you can get an 80% ROI in 15-20 days, within the 45 day term? If you can, increase either the number of credit spread trades across different products; or, re-size the number of contacts per trade. So, you can turnover more credit spreads within a given period. If your P/L shows otherwise, do the opposite. ❑ Debit spreads are typically identified for entry between 90-120 days. Does your historical profit show you can get a 150%-200% ROI within 30-60 days, within the 120 day term? If you can, increase either the number of debit spread trades across different products; or, re-size the number of contacts per trade. So, you can turnover more debit spreads within a given period. If your P/L shows otherwise, do the opposite. Again, turnover more profitable trades within a fixed period. Do the reverse, if your P/L shows otherwise. In conclusion, the critical points to focus on are the 3 types of targets at the portfolio level, the core metrics of trade performance, identifying your intuitive trading orientation and monetizing the average holding period of long and short trades for efficient trade turnover. Translating these specific elements of trading risk into methods you can rely on every day, builds the required consistency in the profit and loss of your trading account. ---------------------Thanks for reading my article, Clinton Lee. Founder, Home Options Trading: a uniquely retail-focused option-centric trading firm. Please see Consistent Results at http://www.homeoptionstrading.com/consistent_results/, displaying the Model Portfolio's Performance YTD, updated each month-end. The portfolio models a typical retail option trader's account up to USD $50,000. Here's the stats in summary: Return: Profit/Start of Year Cash Balance = $91,593/$58,380 = UP 157%. Win/Loss Probability = 60/68 = 88.24%. Performance Ratio = (Win/Loss Probability) x (Average Win/Average Loss) = 88.24% x $2.99 = 2.64. Positive Expectancy = (Win Probability x Average Win) - (Loss Probability x Average Loss) = $1,347 per trade. Preview an original 55 hour video-based course for online options trading from home, at
http://www.homeoptionstrading.com/original_curriculum.html Purchase the curriculum and receive an $800 options basic course as a Bonus! Clinton's career spans 16 years of treasury, finance and banking across Hewlett Packard, JP Morgan Chase, Citibank, Royal Bank of Scotland (previously ABN Amro); and, is currently a Senior Liquidity Advisor at Bank of America in its Global Treasury Services division. Despite the years in the finance/banking industry, it did not help him directly grasp online options trading from home.