Automated Trading Strategy #37
Strategy 37 made $44K in one year, has a Profit Factor of 1.68 and an annual drawdown of only 2.74%
Click on the table to enlarge. For a link to all strategies and the most recent table, click here.
*Scroll to bottom for Column Definitions
Strategy #37 Analysis:
Strategy 37 is based on a spread trade that uses the inverse relationship of two futures contracts. The algorithm for this strategy looks for a trend using a trend indicator, and then uses the strength of that trend as a guide. In general, the stronger the trend, the better the profit factor. Strategy 37 has a profit factor of 1.68, which means that the strategy made 1.68 times more money than it lost during the period. As shown below, the stronger the trend, the higher the profit factor for this strategy and the lower the number of trades made in the time interval. The picture below illustrates this relationships.
So, if you’re looking for the highest profit factor using this strategy, you would need to select the strongest trend. But, keep in mind that every time you increase the trend strength, it’s harder for the strategy to find a trade that meets the trend requirement so you have fewer trades. In the extreme, you could have a strategy with a profit factor of 99 if you set the trend strength to an extreme and are okay with only making a few trades for the year. We’ll show you how to select the strongest trend in the strategy description.
The results posted in the table at the beginning of this post are based on a trend strength that delivered 310 trades for the year, had a profit factor of 1.68 and an annual drawdown of only 2.74%. In total, the trade made $44K for the period 11/01/2020 to 11/01/2021. It makes on average 1.23 trades per day, and has an average net profit of $177 per day or $144 per trade.
This is the cumulative profit of Strategy 37 over a 1 year period (11/1/2020–11/1/2021). It never falls lower than $1,500, but this is due to timing (when you start the strategy) more so than anything else.
This is how the strategy breaks down on a day-of-week basis. Tuesday looks like the best day to enter.
This is a chart of the strategy by hour of day. Keep in mind, this strategy does not close at the end of the day. The average time in the market for each trade is approximately 148 minutes. The longest flat period is ~10 days.
Summary
Clearly, we like this strategy because of the high profit factor and low drawdown, but it is only profitable 14.52% of the time, which means there’s a lot of opportunity here.
It also has an MAE, MFE and ETD of .09%, .28% and .22%, respectively. So the entry commands are great, but the exit commands could be improved. In general, the lower the MAE and ETD; and, the higher the MFE, the better. This strategy has an MFE that is three times as high as the MAE, which means this strategy’s performance can be attributed to its strong entry command. For an overview of how to analyze MAE, MFE and ETD statistics, click here.
This strategy fits much of our criteria, and has a drawdown of only 2.74%, which is very good given the profitability. The dollar value of max drawdown is -$8K so you would want to have at least a $10K account to trade this strategy. Of course we recommend a buffer, so a $15K account would be better.
Summary
We’re looking for the holy grail of automated strategy which we’ve defined as having the following attributes:
- Profit factor greater than 3
- Annual drawdown less than 3%
- Annual return on max drawdown greater than 500%
- Maximum daily net profit of -$1,000
- Avg Daily profit greater than $1,000
- Less than 5,000 trades annually
- More than 253 trades annually
At present, Strategy 37 only meets 4 out of 7 our criteria. We really like this strategy, and will continue to build on its strong entry command, but the hunt continues.
To learn how to duplicate or download Strategy 37, join us by clicking here.
For links to all strategies click here.
*Table Column Definitions:
- Strategy — The name of the strategy.
- Trades — The number of trades used in the backtest to analyze performance. Our goal is ~1,000 trades for comparison.
- Start date- The beginning date of the backtest.
- End date — The ending date of the backtest.
- # of days — The number of days in the strategy.
- Drawdown — This refers to the maximum drawdown statistic, which provides you with information regarding the biggest decrease (drawdown) in account size experienced by the strategy. Drawdown is often used as an indicator of risk.
- Drawdown = single largest Drawdown
- As an example, your account rises from $25,000 to $50,000. It then subsequently drops to $40,000 but rises again to $60,000. The drawdown in this case would be $10,000 or -20%. Take note that drawdown does not necessarily have to correspond with a loss in your original account principal.
- Return on Max Drawdown — We’ve added a dollar value for max drawdown along with a measure of return (return on max drawdown), which is calculated by dividing net profit by the max drawdown. In this way, max drawdown is considered the max capital investment. You can use the dollar value of max drawdown as a proxy for how much capital you need to trade the strategy. And, the higher the return on max drawdown, the better the strategy is in terms of risk/reward.
- Percent Profitable — This is a metric that shows the number of winning trades divided by the number total trades.
- Profit — The net profit made on the strategy for the backtest.
- #trades per day — The average number of trades made per day using the strategy.
- Profit / Day — The average profit made per day.
- Profit / Trade — The average profit made per trade.
- Lowest daily new profit — The worst performing day of the strategy in the backtest.
- Highest daily net profit — The best performing day of the strategy in the backtest.
- Profit Factor — Gross Profit divided by Gross Loss
- Lowest daily cumulative new profit — The worst performing day on a cumulative basis.
- Highest daily cumulative net profit — The best performing day on a cumulative basis.
Originally published at https://automatedtradingstrategies.substack.com on December 3, 2021.
