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Thank you very much for your feedback. I was hoping to get some general benchmark on setting the commission and slippage. My background is in currency trading; hence, trading S&P is new to me. As for PF >1.5, it is easily achieved by reducing the number of trades i.e. trending systems. In my experience, when PF is too high, you don't have a large enough sample of trades and your system will tend to curve fit. All of my trading systems must have over 500 trades else I would not use them.
It looks like it may have some potential. . . what I was initially impressed with is your data pool of trades, as most people that bring strategies to the forum seem to be thrilled with their holy grail strategy that has some 100 or less trades over the past 10 years. The larger the data pool, the more *potentially* trustworthy that your underlying logic is saying something real, though its absolutely no guarantee.
RP had an excellent point, the best thing you can do, by far, is to test the 'live walk' period of time, now. . i.e. from the date of creation, to the present date, and see if it falls flat.
You asked if there was room for improvement, and to that I would say 'absolutely'. . . The profit factor is certainly a bit low for anything you'd want to realistically trade live, *but* since your data pool of total trades is still quite large, you have room to make some tweaks and refinements.
Have you tested it yet over any similar instruments, such as NQ, YM, etc, to determine whether it performs decently there? Or any market wide testing in general? This would be another valuable step, its extremely useful 'confirmation' to see that a strategies underlying logic works across multiple instruments, especially instruments that tend to be highly correlative with the one you've created the strategy for.
Also, do you have any information as to the average 'time in market' of your average trade?
Lastly, I don't use tradestation, can you be sure that your tests aren't taking trades on top of one another, i.e. entering into another trade even if the first trade is still active? This can produce very large trade counts that aren't actually realistic, because what its actually doing, in effect, is entering several times, each time your conditions are triggered, over a short and staggered period of time. .
Lastly, just to confirm, the long/short directions use mirror image logic, right. . the same logic, flipped, for both directions? Oh, and lastly lastly, in regards to ballpark numbers you should be looking to obtain, I agree with Tymb, roughly, in that anything below 1.5 PF is generally uninteresting, but you can obtain that, at least, with just a little TLC here, I believe.
Let me know the answers to those q's, and perhaps I can be a bit of further help, if you'd like
To give you some idea of what I consider to be decent results, here is a strategy I've been running live for a few months now. . . however, its *vital* to note that no strategy should ever be trusted solely on the merit of its own backtest results in isolation. This strategy has been tested marketwide, and 'scored' according to not only its own backtest results, but the backtest results of every other instrument upon which the core logic was tested. . . I also look at its performance numbers relative to all other optimization results I've ever had with the same Instrument/HourOfDay/MarketDirection combination, as I think its vital that you compare apples to apples insofar as is possible. . and this is just the tip of the iceberg, unfortunately. Long story short, backtest results like this do mean something, but woe to anyone that trusts them implicitly, in isolation, without examining a plethora of other data points/factors. The healthy looking backtest is only a starting point, and a somewhat weak one, at that.
Also, its vital to note that one should never expect live results to perform equal or better to the backtest results, over a significant enough period of time, a large enough data pool of trades. . . it will virtually always, without exception, perform worse. This is to be expected, since attaining a strategy with *zero* curve fitting is simply an absolute impossibility. . the goal here is to create as robust and high-confidence of a strategy as is possible, with the expectation that it will earn more than it loses. . not that it will produce a 2.0/3.0+ PF across all market conditions.
Now that the disclaimers are out of the way:
It's my first time uploading graphics to this forum, fingers crossed that I did so properly. . .!
You need to forward test or your system will be curve fitted with data snooping bias. You should try do your analysis on a small set of data and then forward test for around the same amount of data.
If your forward test PF doesn't degrade significantly (it will almost certainly degrade), then it's probably workable. However your PF is a bit low, so any slight degradation will make this unviable.
Also the market has changed heaps since 2001, you should try test from 2008~ onwards as you would need to cater for all the algo activity present today.
Final thing is $12-15 net per trade is too low, any sort of additional slippage, or any degradation can turn this negative very fast.
Also not sure why you chose $2.50 for slippage? ES is $12.50 a tick so you're slippage is $10 too low.
Commission at IB, which is one of the cheapest is $4.04 per round turn, so your commission also too low.
If you fix those two, then your $12-15 net profit will now be less than 0 I believe.
You might want to try discretionary trading the ES for a few months first so you understand how the market behaves and then try to automate that understanding, at the moment it looks like you have just data mined this, which is pretty much guaranteed to not work.
Absoutely. The combination of a PF of only 1.17 and inadequate allowance for dealing costs is almost bound to turn the method described from overall profit into overall loss, I'm afraid. This was all pointed out in some detail in the other thread, a month or so ago, though.
Thank you for your comment. Can you be more specific on your criteria on how you judge a trading system to be curve fitted? As for me, I have a few simple rules for a system design to avoid curve fitting:
1) number of trades must be greater than 1,000 to avoid curve fitting
2) the test period must be over 10+ years or longer
3) single year profit can not account for more than 30% of the total profit
4) Ratio of total profit divided by max drawdown must be greater than 20
5) Use WFO whenever possible
6) Fixed lot trading during system design i.e. no compounding or manipulation of trading lot size
Currently, I am focused on currency trading and have not made the switch to ES. My 8-month old daughter is a handful and most of the time, I am not getting enough sleep. If anyone have a demo account, I can run this system on your account for free. As long as your broker can work with MC, we should be good. If the performance is good after 3-6 months, I also offer to run on your live accounts for free for another year or so. This way you have a stake in the project to ensure it is success.
Thanks for sharing. Are you using market orders or limit orders to enter the trades? What will happen if you extend your back testing from 2000 to 2015? BTW, are you holding orders overnight and during the weekends?
Also, how did you design this system? Did you come up with an idea and test it for the first time and these are the results or did you design, test, modify and these are the results?
You might be on to something or you might not, it really depends on the design and testing methodology you employed.
