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Well I had no idea my question would spur such a debate. After
reading opposing viewpoints, here is what I have converged to:
I am trying to find the best systems with which to trade my 10
favorite stocks. I have about 50 systems at my disposal. I have
decided to backtest each stock (against all systems) with 5000 bars,
1000 bars (which excludes the dot com bubble years) and 250 bars.
Then, for each security, I will choose a system that performs well
over all three time periods.
So do I have an ice cubes chance in hell?
--- In equismetastock@xxxxxxxxxxxxxxx, "David" <junk@xxxx> wrote:
>
>
> While I do respect your opinion on the matter that more
> isn't "necessarily" better given changes in market conditions from
> the past. My view lies more in the fact that if you can design a
> system not only to perform well in past market conditions, but also
> in the dramatic recent changes, your system is obviously more
> robust. And I'm not talking about a system that performs well in
the
> past "on average." I mean consistent gains yearly as much is
> possible. I would much rather have a system that performs just as
> well in the past as it is still doing recently, than having a
system
> that performs well recently but not in the past. In that aspect I
> believe more is better.
>
> But maybe my motives are different. I look for robust systems that
> can be applied to various securities for diversity and perform
> consistently. I'm not looking for max possibly return. If a
> businesss is to be run, you can't expect to have occasional
> profitable results showing up here and there just when they feel
like
> it. If your system can only do well in today's market but not a
> decade old market, who's to say that history won't repeat itself
and
> the market reverts to old? Not to say you can't adjust your system
> when the time comes, but you cannot pinpoint that until possibly
> years too late.
>
> You said that the number of bars used has very little influence on
> curve fitting. In the most ridiculous of examples, if you have
only
> one month of data and go test a basket of systems, you will
obviously
> come up with a few that bought and sold at the exactly the right
> point. Not necessarily because they are good systems. So what's
> next? You can't have one month of data represent a whole year of
> market movememt, it's not accurate enough of the whole. What about
a
> year? That sounds like a decent amount, but it only represents 10%
> of a decade worth of data. Just as a month is only roughly 10% of
a
> years worth of data and thats not accurate enough, then how should
> one year be enough when it's only 10% representative of the market
> conditions over the past decade? Maybe, that then lies more in the
> time frames you plan to choose. If your trade time frame with the
> designed system is short, then superfragalist may be right, more is
> not necessarily better. The short time frame expected to trade
might
> be close enough to the previous short tested time, then you might
> make money with the system you designed for it. But I wouldn't be
> willing chance my money on it. So even aside from the possible
curve
> fitting issue, I still would find the lack of bars to be a negative
> obstacle given that your system wouldn't have had time to "prove"
> itself in more varying market conditions. As I said, I respect
your
> view superfragalist, but the aforementioned reasons is why I
believe
> otherwise. But after writing this, I guess a lot boils down to
> personal objectives and trading style.
>
> Best Regards,
> David
>
> --- In equismetastock@xxxxxxxxxxxxxxx, superfragalist
<no_reply@xxxx>
> wrote:
> >
> > Sorry, but I don't agree with this statement. "I'm sure everyone
> > would more than emphatically agree with me that the more
historical
> > bars the better to test on."
> >
> > While I do agree that using too little data can be a problem, too
> > much data is just a big an issue. Curve fit is a complex issue
and
> > the number of bars of data you use to develop your system has
very
> > little influence on it.
> >
> > I'm not going to go into a long piece on curve fit because there
> are
> > many really good systems development books and internet articles
> that
> > define, explain and debate the issue.
> >
> > Curve fit is easy to test for using out of sample data in walk
> > forward tests. Indicators can be tested for robustness prior to
> walk
> > forward testing.
> >
> > Curve fit is caused by over optimization, lack of robustness in
the
> > indicators, too many variables in the optimized equation and poor
> > selection of variables within the equation.
> >
> > Not one of the systems development books that explore the issue
of
> > curve fit have a set number of bars of data that should be tested
> to
> > reduce curve fit or to validate equations.
> >
> > No one says that 500 bars are too few and 2000 bars are too many.
> > Everyone has a different view. However, most authors and systems
> > develop people do agree on what causes curve fit.
> >
> > Robert Colby in The Encyclopedia of Technical Market Indicators
> often
> > tests using 20 to 40 years worth of data. Does that mean that the
> > best performing systems he has found historically will work well
> > today. Absolutely not. He admits that many of the historcially
best
> > performing systems have done poorly in the last few years. Is it
> > because of curve fit? No, it's because his historical data
averages
> > out all types of market cycles and the last few years have been
> > anything but average. The point of his book is not to use what's
> been
> > great over forty years, but to look in similar places for current
> > versions of the similar things that will work in these markets.
> >
> > Sorry I can't support your opinion. I've gotten a different
> > perspective from studying the issue.
> >
> > Esignal is slowly increasing the amount of historical data they
> > maintain because of intraday system's developers requests for the
> > data. However, there has been talk that the historical data will
> not
> > be available to users of MS but only to Esignal trading clients.
> > Equis says this is not true, but I've seen some evidence of it.
> >
> > Historical one minute data since 1997 on the S&P 500 can be
> purchased
> > for about $2500 from Price-data.com. For people doing intraday
> > trading that's reasonably priced. You can buy individual symbols
> for
> > $75.
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