Any takers on this one? For instance I was just testing a system on a certain 
intraday interval. I then tested it against the same interval but in increments 
of +1 and -1, from -5 to +5. For the most part it was stable, in the sense that 
the more I incremented it the better it did, and the more I decremented it the 
worse it did, but never falling below a respectable Sharpe or % return, 
although at the low end it was 50% of the total return of the in sample 
version. This tells me that my signal is mis-timed to the market, but it seems 
to be mistimed in a consistent way. Thoughts?




________________________________
From: Potato Soup <[email protected]>
To: AmiBroker (Discussion List) <[email protected]>
Sent: Wed, January 6, 2010 5:16:48 PM
Subject: Re: [amibroker] Optimizing

    

In sample is always bad to rely on. But how do you define out of sample? If you 
are backtesting one symbol with intraday data and less than 100 trades per 
year, do you start with the oldest year and optimize, then test out of sample 
the newer years? Or do you start with the best perfoemong years, hoping that it 
improves the worst performing years? Or do you test all years and then verify 
by using another symbol as out of sample?
________________________________

From:  Howard B <[email protected]> 
Date: Wed, 6 Jan 2010 14:30:45 -0700
To: <[email protected]>
Subject: Re: [amibroker] Optimizing

Hi Markus --

The characteristics of a desirable trading system are yours to decide.  Whether 
you want to focus on trend following systems, on mean reversion systems, on 
pattern systems, statistical systems, or whatever else is completely up to you. 
 

I meant no criticism.  My suggestion about allowing the relationship between 
the two moving average lengths was simply to point out that what was originally 
thought of as a trend following system might transform itself into a mean 
reversion system under some circumstances.

As always -- do your own research, including in-sample testing and 
out-of-sample validation.  Walk forward testing is extremely valuable.  
In-sample results are always good and have no value in estimating future 
performance of a system.

Thanks,
Howard










      

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