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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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