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There will always be "fractal" (discontinuous)
events in any market. However, I believe the "average" way
a stock responds to a non-predicted "event" is dependant on characteristics
which are variable between stocks. A simple example is average
volume. One could theoretically encode the principles. As the
average trader gets smarter (this is happening, leveraged by computers) it
may be necessary. At this time, it is not necessary. In any
event, backtesting is adequate to control this. 911 was an event.
Including it would be one way to empirically assess an event.
Richard
<BLOCKQUOTE
>
----- Original Message -----
<DIV
>From:
goldfreaz
To: <A title=amibroker@xxxxxxxxxx
href="">amibroker@xxxxxxxxxxxxxxx
Sent: Friday, November 01, 2002 6:24
AM
Subject: [amibroker] Re: a few
considerations about optimization
Interesting...delta=C-Ref(C,-1);md=MA(delta,45);MAd=MA(abs(delta),45);Graph1=MAd;Graph1Style=1;Graph1Color=colorGreen;---
In amibroker@xxxx..., "Avcinci" <<A
href="">avcinci@xxxx...> wrote:> Franco,>
> Recently I was talking to a professional trader who told me that
some stocks simply don't behave well in any system and others do
extremely well (in backtesting). He attributes this to a term called
the "fractal efficiency ratio," coined by Perry Kaufman. A stock has
to have some non-random movement to be predictable. It's the total
change in price over a given period, divided by the sum of the
absolute values of all the daily changes in price. If a stock has
too small a directional component, then it's a poor candidate for any
system, regardless of how many filters or refinements you add.
You're better off using all that firepower on a better target. I've
been testing a lot of stocks lately individually, finding that many
simply give very bad backtest results and very non-robust parameter
coefficients. So, I eliminate them from my watchlist and concentrate
on those stocks that behave well. This seems to be working well. I
haven't had time to write any code yet to see if the good-performing
stocks have a higher fractal efficiency ratio (personality as you call
it?) than the poor performing ones, but it's worth a try. You must test
over a long enough period of time to encompass bullish, bearish, and
sideways markets, like 1/1/97 (or even earlier) to present time. If you
try this idea out, let me know how successful you are. I'm very interested
in this concept. When I get a chance, I'll try it myself. But, in theory,
it seems to have merit. > > Al Venosa>
> ----- Original Message ----- > From:
Franco Fornari > To: amibroker@xxxx >
Sent: Friday, November 01, 2002 6:15 AM> Subject:
[amibroker] a few considerations about optimization> >
> Hello,> > trying to optimize
any trading system, I think we all have thought, sometime, we would like
to avoid such a tedious process or to do it once and for
all.> It could be possible? This question badgered me for a
long time, unfortunately with no success, yet I feel there must be a
solution.> Why I say that? Because a peculiarity of each
stock, called "personality" by someone, wich seems stable enough. In other
words, I think if we were able to mathematically represent this
characteristic, we could automatically optimize any trading
systems.> But, the big matter is: what is this
characteristic (long term volatility, frequency of peaks and troughs,
price)? How could we assess or measure it? And, first of all, does such a
feature exist or is it only a mirage? How do you think about?>
> Best regards,> > Franco>
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