Often when comparing trading system performance, the natural inclination, is to compare returns. If you have two trading systems that traded a $100,000 account, and made a 30% return, and produced a 15% drawdown, and had the same length of drawdown, they would seem pretty much the same, right? I would say the answer to that is “not always.”
What if one trading system only used an average of $30,000 in margin while the other used an average of $70,000? Theoretically, you could have funded the first account with less money and invested the remaining dollars elsewhere.
So, I am suggesting that you consider viewing returns as based of off the account size required as opposed to an arbitrary number. By doing this, you can form the arrive at the best decision about the starting funding level in your account. In other words, you may trade the account as though it were a 100k account, but only put up $30,000 in trading funds because that is all you think you need. Many trading systems, money managers and CTA’s allow for such a notional funding approach. It can be an efficient use of capital.
The commercial testing software Trading Recipes has an intriguing way of computing these numbers. It can run a worst-case analysis. What this does is looks at every possible start date over time (for example 10 years). If there were 1000 different trades you could have started trading from, then it (Trading Recipes) tests the trading system from every single one of those 1000 trades. It then sums the worst drawdown and the required margin starting from each one of those 1000 trades, and it goes on to show how the system performed over the next 12 months. A start trade report allows you to create a frequency distribution of yearly returns cross-referenced to the account size required.
For the sake of this example, I am going to test 4 different trading systems and compare the results. The portfolio is 15 diversified markets that are all reasonably high in liquidity. Also, I have approximated margin based on two times the 5-day average true range multiplied by the point value, and then took the average of that over a period of 5 years. I have done it this way because margins change dramatically over time. Changing margins get caused by changes in a market’s underlying volatility. Computing this way will cause the margin to rise during higher volatility periods, and decrease during lower volatility periods. This risk-adjusted method is like live margin requirements. I think this is far more robust than to use the current margin values because past margin was likely different. Even though these may not be the exact margin amounts the above formula does seem to be close to the current margin levels in many commodities. You could always use a higher multiple if you wanted a greater “cushion.” I am showing you this for demonstration purposes; you need to decide the best way to simulate the past and future margins in your testing. It would be terrific if data vendors like CSI sold data files for trading systems with the exact exchange minimum margin requirements throughout history, although I have not seen it.
Trading Systems Comparisons
For all tests:
Period tested was: 1/1/90 through 12/31/2003
Data: CSI back-adjusted contracts
Slippage and commissions: $75
Starting Capital: $100,000
Money Management: Risk 2% of equity a trade or one contract if the risk is less than $3000 (whichever is greater).
15 market portfolio: Euro Currency, Corn, Kansas City Wheat, Cotton, Sugar, Coffee, Crude Oil, Natural Gas, Japanese Yen, Swiss Franc, Five-Year Notes, Thirty-Year Bonds, Nikkei Index, London Nickel and London Copper
In the first test, we will use a Channel Breakout System similar to the “Turtle” method of trading. Specifically, this system buys at the highest price of the last 20 days and sells at the lowest price of the last 20 days. It then exits at the lowest price of the last 10 days for long positions and the highest price of the last 10 days for short positions. Risk computations are as a multiple of average true range, and protective stops get placed at those same levels.
Channel Breakout (20/10)
Starting periods available to test since 1990: 2080
Average required account size: $62,026.00**
Average first-year profit: $39,086
Ratio of average account size required to average first-year profit: 0.63
In this next test, we use the same exact rules as above except the input values change to 50 and 20 (From 20 and 10)
Channel Breakout (50/20)
Starting periods available to test since 1990: 1017
Average required account size: $35,009.00**
Average first-year profit: $52,341.00
Ratio of average account size required to average first-year profit: 1.49
Aberration Trading System:
Starting periods available to test since 1990: 472
Average required account size: $12,502.00**
Average first-year profit: $23,148.00
Ratio of average account size required to average first-year profit: 1.85
Checkmate Trading System
Starting periods available to test since 1990: 551
Average required account Size: $15,922.00**
Average first-year profit: $39,659.00
Ratio of average account size required to average first-year profit: 2.49
Synergy Trading System
Starting periods available to test since 1990: 536
Average required account size: $17,358.00**
Average first-year profit: $52,196
Ratio of average account size required to average first-year profit: 3.00
**(Margins were approximated, they could be significantly higher or lower)
Trading Systems Results Summary
Here, you can see an intriguing phenomenon. The average first-year profits for the Channel Breakout (20/10) were almost the same as Checkmate. The average required account size for Checkmate was less than half. Similarly, the average first-year profits for Channel Breakout (50/20) were almost the same as Synergy. The average required account size for Synergy was again about half.
Information like this can be valuable for somebody who wants to fund an account notionally. If nothing else, it is an eye-opening perspective of how two trading systems can produce almost the same profit in a year given the same account size and money management, yet one of those trading systems can boast a much lower historically required account size. A reversal system or a short-term system like the (20/10) Channel Breakout will likely have higher requirements because of greater numbers of simultaneous trades.
We have done these tests on many other trading systems. If you would like to see those reports, or if you would like the complete spreadsheet reports used in generating these tables, please contact us.
By: Dean Hoffman
FUTURES TRADING IS NOT SUITABLE FOR EVERYONE AND PAST PERFORMANCE IS NOT NECESSARILY INDICATIVE OF FUTURE RESULTS. THERE IS RISK OF SUBSTANTIAL LOSS IN FUTURES TRADING OR WITH ANY TRADING SYSTEM OR PROGRAM. CAREFUL EVALUATION OF YOUR PERSONAL FINANCIAL SITUATION MUST BE DONE PRIOR TO DECIDING TO TRADE IN THE FUTURES MARKETS OR ANY GIVEN TRADING SYSTEM OR METHODOLOGY.