Thank you very much Thomas.  So in fact the walk-forward measures the
data-mining bias in some way?  I will read what you say I should read, and I
will look at chapter 20 in Howard's book...

But still, so far I get the impression that if I backtested let's say cross
(ma,ma...) for 2000 to 2008 and I take this best result and it is 100% CAR,
then eben if OOS is 50% CAR I guess there can still be place for data-ming
bias (or curve-fitting) because the optimization was done with the best
result.

Anyway, if I understand correctly what you say, the OOS will ALWAYS be less
than IS because the IS is optimized - that is, it will take the best-of-100
(or 200, etc.) result, and compare it with a more random result that would
occure in real life.  Am I wrong?

Thanks,

Louis

2008/4/16, Thomas Ludwig <[EMAIL PROTECTED]>:
>
> Louis,
>
> in the IS period your system is optimized, then the best values from the
> optimization are used to perform a test over the IS and OOS periods.
>
> If the OOS results are worse than the IS results, this means that the
> system doesn't generalize well enough. BTW: This topic is very well
> explained in chapter 20 of Howard's book. I also suggest to look at
>
> http://www.amibroker.com/kb/2008/02/12/getting-started-with-automatic-walk-forward-optimization/.
>
> I must say, that walk forward testing has completely changed my way of
> thinking. It's much easier to see now if a trading system is worth a
> second look.
>
> Greetings,
>
> Thomas
>
>
> > Hi,
> >
> > I've been experimenting with walking-forward, and I have some
> > questions regarding how it works.
> >
> > I ran a complete random optimization or buying/selling using the
> > variables I set (a MCS in fact), and systematically OOS results were
> > worst than IS.  I don't understand how it works, because whatever if
> > the sampling is IS or OOS it is always the same variables that are in
> > place.
> >
> > Anyone could explain how this work?
> >
> > Thanks,
> >
> > Louis
>
>
>
>
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