If you are serious about trading and Kenneth Grant’s Trading Risk isn’t already in your library, I think you should consider getting a copy. Who is Kenneth Grant? Here is his bio from Amazon:
Kenneth L.Grant is Cheyne’s Global Risk Manager, and is the Managing Member for Cheyne Capital, LLC, the firm’s U.S. arm. Mr. Grant is a pioneer in the field of hedge fund risk management and capital allocation. Before joining Cheyne, he created risk control programs at two of the world’s leading hedge funds, Tudor Investments and SAC Capital, where he was eventually promoted to the title of Chief Investment Strategist. Mr. Grant holds a Bachelor of Science in Economics and Mathematics from the University of Wisconsin, an MA in Economics from Columbia University, and an MBA from the University of Chicago Graduate School of Business.
I won’t present a review as many others have already written same but I will suggest that you buy the dead tree version rather than an e-book as this is likely to serve as a reference for future use and one that you may want to highlight sections of.
The past four years have been incredible for US stocks with the S&P 500 up more than 60%. If we could go back in time to March, 2010 and I gave you the option to 1. buy and hold SPY for four years with you knowing the S&P 500 was about to enjoy a fantastic bull run or 2. trade a strategy that shorts US stocks, will have a string of eight consecutive losses, will have a 20% drawdown, loses on 35% of the trades and will have four trades that each lose over 50%, which strategy would you choose? Very few traders can stomach the psychological challenges of the drawdown (especially when the broad market is rising), shorting stocks while the broad market is rising over 20%/year, eight consecutive losses and trades that individually lose over 50%.
Following is the equity curve for a short strategy that I am working on and it suffered all the negative performance attributes mentioned above.
The short strategy is based on a 5-stock portfolio and trades US stocks that are priced over $5 and have an average daily trading volume in excess of 500,000 shares. This is a backtest and must, therefore, be taken with suspicion about its performance going forward. Nonetheless, my point is that it is possible to have a strategy that provides an overall return that most traders find acceptable yet there are granular aspects of the trades that some may not be able to cope with.
Traders who can’t accept what some may perceive as failure will never enjoy success. Drawdowns, consecutive losses and losing trades will all be a part of a successful trading system. Of course, the system must have a positive expectation with an acceptable drawdown. For the system discussed here, the Monte Carlo annual average return is 33.8% and the Monte Carlo drawdown is 21.8%.
I recently seen the following on a forum:
Given the following two systems, which would you prefer:
- System A which has a 60% win rate with a ratio of average win to average loss of 1:1
- System B which has a 40% win rate with a ratio of average win to average loss of 2:1
The first step most traders would undertake is the calculation of the expectancy for each system.
E = (Win Rate x Average Win) + ((1 – Win Rate) x Average Loss)
E = (0.60 x 1.0) +((1-0.6) x -1.0)
E = 0.20
E = (0.40 x 2.0) +((1 – 0.40) x -1)
E = 0.20
Over a large enough set of trades, we can expect both systems to generate identical returns. So all things being equal, the systems are identical but all things are not equal. When you consider a trading system, what other performance measure should be at the top of the list besides return? It’s maximum draw down of course. For example, if Systems A and B both generate annual returns of 15% but one system will incur a maximum draw down of 15% and the other will incur a maximum draw down of 25% you will choose the system with the lower draw down.
If all we have is the information given above for both systems, how can we determine which system is likely to have the higher draw down? One possibility is to perform a Monte Carlo (MC) analysis.
I performed a MC analysis on both systems using a sample size of 5,000 trades. As expected, the returns generated by both systems were almost identical but System B had a much higher draw down in the MC analysis. At the 95% confidence level, System A had a Return-to-Draw Down ratio of 2.48 versus 1.47 for System B.
Other traders selected System A as well albeit by using different methods of comparison.
Lately I have had conversations with investors who can’t hold back from telling me how well their stocks have performed in recent years. I’m happy that they have done well but can’t overlook the time period that they are considering.
It is human nature to place more weight on recent trading performance than historical trading performance. I suspect most of us are guilty of that. Let’s bear in mind what happened five years ago this month by considering the following chart of the S&P 500.
The S&P 500 hit a low in early March, 2009 but then began a five year bull run. From the low of March, 2009 to now, the S&P 500 has achieved a compound annual growth rate (CAGR) of 21.4% which is incredible. The past five years have been a period in time where buying and holding SPY has worked very well but you must not confuse a bull market with brains.
Let’s look at two other time periods with the same end point, March, 2014, to see how the S&P 500 has performed. For the seven-year period from March 01, 2007 to now, the S&P 500 has achieved a CAGR of 4.0%. For the ten-year period from March 01, 2004 to now, the S&P 500 has achieved a CAGR of 4.8%. Clearly, the past five years have been exceptional for the S&P 500 but, in my opinion, there is no possibility of a repeat performance for the next five years.