Hi Howard,

What would you consider to be a sufficiently large sample for IS and then
for OOS?  If I develop a system that makes 250 trades a year, then if I
select IS-OOS of 2-3 weeks then it's no more than 10-15 trades.  Is this
enough?

Regards,

Louis

2008/4/22, Howard B <[EMAIL PROTECTED]>:
>
>   Hi Simon --
>
> From your description, the system was developed on a set of data, but not
> tested on any data that was not used during development.  The data used
> during development is called the in-sample data.  Data used for testing that
> was not used during development is called the out-of-sample data.
>
> The in-sample results always look good -- we do not stop playing with the
> system until they look good.  The in-sample results have no value in
> estimating the future out-of-sample results.  In order to estimate what the
> likely profitability will be when traded with real money, out-of-sample
> testing is necessary.
>
> I have documented systems that have over 1,300,000 closed trades and
> reasonable looking results for the in-sample period, but were not profitable
> out-of-sample.
>
> There is no substitute for out-of-sample testing.
>
> Thanks for listening,
> Howard
> www.quantitativetradingsystems.com
>
>
> On Thu, Apr 17, 2008 at 2:29 AM, si00si00 <[EMAIL PROTECTED]> wrote:
>
> >   Hi all,
> >
> > I have a friend who has developed a trading system. It is an intraday
> > system that makes on average around 5 futures trades per day. We were
> > discussing it the other day and a point of disagreement arose between
> > us. He claims that there is no necessity for him to test the strategy
> > on out of sample data because he has back tested it using over 8 years
> > of historical intraday data, and the patterns the strategy predicts
> > occur 70% of the time or more.
> >
> > My question is, does anyone know if the data-mining bias can be
> > considered irrelvant when the sample size is so large? (in this case,
> > the sample size is roughly 8400 trades). Put another way, with so many
> > observations, how many different rules would have to be back tested in
> > order for data-mining bias to creep in?
> >
> > Thanks in advance for any thoughts you might have!
> >
> > Simon
> >
> >
>  
>

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