#090: MY STUDENT'S STRATEGIES (CASE STUDY #37)
When you’re developing a new strategy, in some markets, like Russell 2000, it is quite simple to find one. Especially when you’re building a long-biased strategy. But, just as well, there are some other markets that are not so easy to find a strategy for. One of them is sugar. You can spend weeks trying to find a robust strategy for such a market without any luck. But I have a couple of students that managed to do precisely that. This is why I haven’t presented you with too many strategies for the sugar market before (this is actually probably the first one).
A good way to start building an automated trading strategy is to take knowledge from discrete trading and apply it when developing an automated strategy. That’s exactly what one of my students did and added his favorite conditions for the sugar market to the Smart Code from the Breakout Strategies Masterclass.
But let’s take a look at the basic settings now:
Market: Sugar (S)
Main time frame (data1): 15-minute
Secondary time frame (data2): N/A
Time template: 8:00am - 2:30pm
Profit factor: 1.56
Win %: 19.35%
Avg.trade: 161.87 USD
Exit: Stop-loss or Profit Target (avg. winning trade +2,335.84 USD)
Stop-loss: Variable, biggest $1,467.20 USD (avg. losing trade -359.89 USD)
What you can notice in the overview above is that under 20% of all trades of the strategy are profitable. That is quite low. Out of 5 positions, 4 of them will lose. In the past 8 years, the strategies had just 2 maximum consecutive winning trades. And up to 18 consecutive losses. With 40 trades per year on average, that is roughly 6 months. In these times you really need to have faith in the strategy and be sure you have done all the robustness-testing thoroughly. But on the other side, this strategy has a RRR (risk-reward-ratio) of 6.5 (the avg. profit is 6.5 times higher than the avg. loss), which is probably the highest we’ve had in this series.
The strategy has done, in less than 8 years, over $50,000 profit, that is over $6,200 average. And since the close to close drawdown is $6,082, the average net profit to max drawdown is slightly above 1:1. The ratio of long and short trades is almost equal (153/157), the percentage of winning trades is also similar (20.26% / 18.47%), but the average net profit is slightly higher in long trades. And so is the profit factor and overall net profit.
Let’s take a glance at how these numbers look on a chart:
As you can see, the characteristics of the equity curve match the percentage of the winning trades - there are some big wins (up to $2,834.80 per contract) usually followed by a lot of smaller losses. The accumulated losses before another big win usually reach between $1,000 and $2,000, but there are also some that reach $5,000 (or more). Like in the beginning, at about trade number 50, then again after trade number 200, and then again right before the close, at trade number 300. So these losses are nothing uncommon, they are something you need to get prepared for.
Let’s take a look at the numbers more in detail:
As I already mentioned, the long trades generate a slight bit more of profits than the short side ($27,287 to $22,890), the average trader net profit is about $35 more for long trades, but besides that, the characteristics of long and short trades are similar.
This is usually the part in which the strategy is tested on other markets as well, but since the sugar market is so specific, this strategy wasn’t tested on other markets.
But, as you can see, even with the less than 20% of winning trades, you can still have a profitable system that can generate nice profits and can be an interesting system for your portfolio (as the correlation to other systems in your portfolio will probably be close to 0), but you have to know that there can be up to 18 consecutive losses, and probably get ready for even more when you do the Monte Carlo Analysis.
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