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Most platforms include that in the backtest report.
But be careful with what you are using it for - if you use those values, and then pick your stops/targets for those same trades based on what you calculated, your results will be biased - meaning that in the future those values will not perform nearly as well...
Can you help answer these questions from other members on NexusFi?
If you have a portfolio of strategies it can be a good tool using MAE to find out intraday equity drawdowns for your portfolio which can be higher then the closed drawdown. There is some portfolio analyzer programs that can do this by loading 1 minute data for the instruments involved in the analyze.
Do you have some advice on how to find out which parameters have the most effect on the success of a system? In optimization and walk forward it is not always realistic to test the entire parameter space, so sometimes I find myself having trouble thinking about which parameters I should adjust in optimization/WF and which I should just leave alone. Do you have any tips on what the best way to identify which parameters should be adjusted and which not?
There are a couple of tricks I use to help narrow down parameters and ranges. The first thing is that in my experience if you have a lot of parameters to start, your system is too complicated. So really before you get to that point, you should simplify your system.
But let's say you have done that as much as possible - then what? I usually will optimize each parameter by itself on a small piece of data, and see what its impact on performance is. After I do this with all parameters, I have a good idea which ones are driving the strategy, and which ones that are not. Then I usually fix or eliminate the ones that are not that important.
Thanks! What about if the parameters are dependent on each other? Changing one parameter at a time will still affect the other if there is some sort of correlation between the two.
You could test them both at the same time. I usually see the second order effects like this to be be a smaller driver than the variable by itself (first order effect).
In doing this, I am guided by trying to simplify the strategy. And unfortunately, sometimes simplifying means you have to give up certain things (like maybe the situation you suggest). But for me, simple rules over everything...
I have a new strategy I am developing but unfortunately it does not produce a huge number of trades. I am on the verge of rejecting it but I thought before I do so, get your thoughts on it. This is for 15 minute futures.
The backtest has 7 years of data. The best optimization so far produces 83 trades during that time. So about 10 trades a year. However each trade produces an average profit of about $350 per contract and that includes slippage and commissions. It has a 75% win rate. So far the strategy only has 1 entry rule and 1 exit rule and a total of 4 parameters. 2 for each rule.
The critical point is gauging the degree of overfitting.
E.g.: If your 7 in-sample years are all within the current 2009-2017 uptrend in the indices,
the system could be next to worthless even with a small set of parameters.
So what are the results of the out-of-sample tests?
If the out-of-sample results are as good and the same system performs
I have similar metrics for a few strategies. If your results are all out of sample or from walkforward, I would put more faith in them. It would obviously be nicer to see more trades.
The bigger question to me is not WHAT the results were but HOW you developed the strategy. Most people don't realize that the HOW is the big deal. For example, if your results are all walkforward, and from your first attempt at creating the strategy, I'd say "great!" But, what if the results you showed are after 6 months of work, where you ran dozens of variations before settling on this one? Then, I'd say "not so great."
Here is an example of a strategy that I trade live. It has 2 parameters to optimize, and I have been trading it live for a few years. But look at the low number of trades - originally that caused me to sit on the strategy and watch it live for a few years before putting real money behind it. But real time performance has shown that this strategy is pretty good.