[maildigger]

*both systems traded in may & june
*both systems trade the US indices
*no overnight risk
*max daily risk = 2.5% of capital


A)
40% winners
60% losers
expectancy/contract = 0.6 point

made 23%

B)
60% winners
40% losers
expectancy/contract = 3.25 point

made 8%

C. Neither.

Without knowing the per trade stop-loss limit for each, I wouldn't trade either.

-fs

[maildigger]

Maybe I should ask another question! How would you compare (on which criteria) 2 systems and determine which one is better?

[darthtrader2.0]

If you read the "System Developement with Acrary" thread on elitetrader and Evidence Based Technical Analysis, it seems the best way to judge a system with our current tools is to run monte carlo simulations of the same hold time as your systems to see that your system does much better than random.
If you were to find that both systems have an edge better than random then you would probly want to check for the correlation between the systems themselves. If they are strongly correlated then you would want to go with the system with the better sharpe I would think.
If the systems are weakly correlated togather then you might want to run both at the same time if they have an edge better than random.

[maildigger]

Are there more simple methods that could be used to evaluate?

[darthtrader2.0]

Well, I mean i guess you could just trade the one with the better sharpe ratio.
To me the biggest issue though is only testing on trades in may and june. I think you really need to question if that is a robust enough test as those two months had pretty similar volatility, trend/rangebound characteristics to them. Right now its pretty impossible to say if your system is exploiting a characteristic of the market or simply gets lucky under the specific trade characteristics from may/june.

[maildigger]

I would like to discuss more in general how one could evaluate a tradingmethod (based on objectif ratio's). How do you "know" you have a certain edge?

[darthtrader2.0]

Are you talking automated or discretionary though? For discretionary, I would think the key is to simply keep very good metrics on your performance and also judge your trading against some measure of volatility like the VIX. Who knows, maybe there is nothing wrong with you method but you either get scared with a jump in volatility or the method fails from lack of volatility. How exactly you would do that though I'm not sure.
For automated I just don't see anyway around monte carlo simulations against either detrended and/or "de-volatilized" data. If your just doing historic backtest with optimizations I don't see how you can get around the fact that you will never know if you have an edge or if your simply curve fitting to the trend/lack of trend, volatility/lack of volatility that is present in the data your testing against. Even if your not using optimization, you can't know if your system has a real edge or if you have just got lucky as far as the situation goes with the data your testing against. You need something to test against thats not the data itself(ie..10,000 random trades from a monte carlo engine)