Excellent questions Mike.  That's exactly what I was wondering about.

Louis

2008/4/24, Mike <[EMAIL PROTECTED]>:
>
>   > To make sure I have been clear on this ----
> > It does not matter At All how many trades or what length of time the
> > in-sample period covers. Results from the in-sample runs have no
> value in
> > estimating the future performance.
>
> Howard,
>
> In an earlier post you stated that the number of IS observations will
> impact the error bands of the backtested statistics.
>
> Given that these same statistics are then used in the calculation of
> the objective function, which in turn will dictate the parameter
> values to use in the next OOS period. Wouldn't it be a logical
> extension that an IS period should have sufficient observations to
> allow the error bands to stabilize? Not for "estimating the future
> performance". But rather for estimating the best parameter values.
>
> Or, are you satisfied that performant OOS walk forward periods is all
> that counts? How many OOS periods do you like to have before making
> your final judgement?
>
> As always, thanks for sharing.
>
> Mike
>
> --- In [email protected] <amibroker%40yahoogroups.com>, "Howard B"
> <[EMAIL PROTECTED]> wrote:
> >
> > Hi Louis, and all --
> >
> > Select the period of time for the in-sample period that works for
> the system
> > you are using.
> > Select the period of time for the out-of-sample period and
> reoptimization
> > period that is sufficient for the system and the market to stay in
> sync and
> > to give you several walk forward steps.
> > Perform the walk forward analysis.
> > Look at the out-of-sample results from the combined walk forward
> steps.
> > Decide from there whether to trade or go back to the drawing board.
> >
> > To make sure I have been clear on this ----
> > It does not matter At All how many trades or what length of time the
> > in-sample period covers. Results from the in-sample runs have no
> value in
> > estimating the future performance.
> >
> > Thanks for listening,
> > Howard
> >
> >
> > On Tue, Apr 22, 2008 at 8:22 PM, Louis Préfontaine <[EMAIL PROTECTED]>
> > wrote:
> >
> > > 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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