Re: [amibroker] Re: Difference betwee OOS and IS, AmiBroker Email List Archive

2008/4/18, Mike <sfclimbers@xxxxxxxxx>:

Louis,

That's the whole point of walk forward analysis! The goal is to enter
each new OOS period with parameter values *most relevant* to what the
market is about to offer. When parameter values change, it is not a
sign of failure. It is a sign of adaptation to changing market
conditions.

If your parameter values stay the same, that suggests that the market
is continuing as it had been. If your parameter values change, that
suggests that the market has changed and that your strategy has
*adapted* to the change.

The frequency at which your parameter values change will largely be
dependant upon the length of your IS period. If you have a 10 year IS
period and a 2 week OOS period, it will be a loooooooong time before
your parameter values change from one OOS to the next OOS.

That is why Howard advised you in your earlier thread to experiment
with different IS period lengths to determine what the ideal IS
period length is for your strategy.

If you are unable to find a suitable IS:OOS period lengths
combination, that suggests that your strategy is poor and needs to be
reworked or abandoned.

Mike

--- In amibroker@xxxxxxxxxxxxxxx, "Louis Préfontaine"
<rockprog80@xxx> wrote:
>
> Hi Thomas,
>
> I understand what you mean and I agree with you on what you say.
My concern
> is more about what to do when each IS and the following OOS uses
some
> parameters and then each new IS-OOS uses another parameter.
Moreover, all
> those parameters are (as far as I know) the best-of-many and they
are not
> resampled, so I see a potential problem and I have trouble
identifying where
> my system fails because if I use a walk-forward of 2 weeks each 2
weeks has
> new parameters...
>
> Do you understand what I mean? Sorry if I am confusing... English
is not
> my first language.
>
> Louis
>
> 2008/4/18, Thomas Ludwig <Thomas.Ludwig@xxx>:

> >
> > > The problem with that is the following: let's say my signal is
a MA
> > > crossover, and I optimized each MA. I apply a walk-forward of 3
> > > months, and each time the MA Crossover is different. So, in
the end,
> > > if the OOS is worse than IS, I don't know much more because
each time
> > > the walk-forward was acting on different MA Crossover.
> >
> >
> > I disagree. Look at it this way: You perform an optimization ovet
your
> > IS period, and then you usually select the best parameter
combination
> > based on the metric you chose (like K-ratio). The basic
*assumtion* is
> > that this "best" parameter combination gives you a trading system
that
> > can generalize - i.e., it will be able to be profitable even if
market
> > conditions change somewhat. But you can't be sure before you
apply this
> > optimized system to NEW data different from the IS data - that's
the
> > OOS period. That's exactly what walk-forward is doing. It just
adds one
> > more assumption: That you normally wouldn't stick to the same
> > parameters over several years. That's why it walks forward though
the
> > time comparing the optimized result of the respective IS period
with
> > the NEW data of the subsequent OOS period. Now, if you compare
your IS
> > results with the OOS results and you find the latter ones
considerably
> > worse that shows that your system is not robust. Think about the
3D
> > optimization graph available in Amibroker: Such a poor system
would
> > probably produce a 3D surface plot with big changes (spikes,
drops)
> > instead of stable plateaus - i.e. it is *very* dependent on the
> > parameters you chose. A small change in the parameters for the
tested
> > period would lead to poor results as the system has
only "learned" the
> > market structure in that period and will fail if that changes over
> > time.
> >
> >
> > > Do you
> > > understand what I mean? And because the walk-forward only
shows the
> > > BEST result of ONE optimized portfolio result (RAR, RRR, CAR,
etc.) I
> > > just can't make it better because I can't see what is result
number
> > > 2, or 3. In that way, optimization seems superior, but maybe I
am
> > > not using walk-forward correctly. That is my main concern!
> > >
> > > Louis
> > >
> > > 2008/4/17, Louis Préfontaine <rockprog80@xxx>:
> > > > Hi Thomas,
> > > >
> > > > Do you use Walk-forward as a random optimizer like Monte Carlo
> > > > Simulation or do you use it as a parameter optimization
(let's say
> > > > you want to know the best numbers for a MA crossover). Or
maybe
> > > > both?
> > > >
> > > > I ask this because my feeling is that if I use it only as a
> > > > parameter optimization, each parameter would be tested only
one
> > > > time in each IS or OOS, hence this could not be
significative. I
> > > > tried to add a random simulation 5 times to get the best out
of 5
> > > > results, but I was wondering if this was correct or simply a
waste
> > > > of time.
> > > >
> > > > Thanks,
> > > >
> > > > Louis
> > > >
> > > > 2008/4/16, Thomas Ludwig <Thomas.Ludwig@xxx>:

> > > > > > 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...
> > > > >
> > > > > Yes, it's explained there in detail. It's great that
Amibroker
> > > > > now automates this process (that wasn't the case when
Howard's
> > > > > book was published).
> > > > >
> > > > > > 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.
> > > > >
> > > > > If your IS period is 2000-2008 I'm afraid that there is no
time
> > > > > left for the OOS period ;-) Both periods must not overlap!
In
> > > > > the book (and you can configure Amibroker accordingly) the
IS
> > > > > period is chosen to be 2 years and OOS is one year. If you
start
> > > > > the process in 2000, the first IS period would be 2000-2001
and
> > > > > the first OOS period would be 2002. The second IS period is
> > > > > 2001-2002 and OOS is 2003 - and so forth. In my
understanding
> > > > > this approach simulates the fact that you normally don't
trade a
> > > > > sytem with the same parameters unchanged for many years
(unless
> > > > > it's a really long-term system). Rather, you would re-
optimize
> > > > > the system every 1-2 years to adjust it to changing market
> > > > > conditions. That's what the walk-forward test is actually
doing.
> > > > > Every new optimization is compared with the results of an
OOS
> > > > > period. If the OOS results are considerably worse than the
IS
> > > > > results this is a strong hint that the sytem will not work
in
> > > > > real trading.
> > > > >
> > > > > > 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?
> > > > >
> > > > > The OOS results are not necessarily worse - but most often
they
> > > > > are. I've analyzed a couple of systems (which I don't
trade) that
> > > > > had beautiful IS equity curves - they all failed the walk-
forward
> > > > > test spectacularly. So it seems they were all overfitted
and were
> > > > > not able to generalize.
> > > > >
> > > > > Greetings,
> > > > >
> > > > >
> > > > > Thomas
> > > > >
> > > > > > Thanks,
> > > > > >
> > > > > > Louis
> > > > > >
> > > > > > 2008/4/16, Thomas Ludwig <Thomas.Ludwig@xxx>:

> > > > > > > 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-a
> >
> > > > > > >utomat ic-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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