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Gary,
ncAlpha and/or other risk-reward type ratios seem to do the job.
I don't think I'd call that method auto optimizing.
Fred
--- In amibroker@xxxxxxxxxxxxxxx, "Gary A. Serkhoshian"
<serkhoshian777@xxxx> wrote:
> Fred,
>
> Related to your points below, I have a few questions.
>
> 1. Understanding your point about equity feedback. Which
selection criteria have you found to be most robust? With any
selection measure it seems we have to make a leap of faith that good
performance in the past will continue in the future. I'm finding
Alpha to be useful.
>
> 2. Your second comment related to making system auto adjustments
on the fly. Isn't that essentially auto-optimizing or is it more in
line with the IP method that DT has been sharing?
>
> Thanks for sharing,
> Gary
>
>
>
> Fred <fctonetti@xxxx> wrote:
> Howard,
>
> With regards to equity feedback what I think I was trying to say
was
> that I have not found equity feedback to be a particularly good
> methodology of deciding what to trade as opposed to evaluating a
> particular trading system where I would certainly agree that the
> curve itself and the statistics that rleate to it are very
> important. For example I've never found attempting to measure and
> then utilize how well some particular security moved during the
last
> up move of what ever magnitude you want to describe the up move as
> being as indicative of what's likely to happen during the next up
> move.
>
> As far as markets changing characteristcs over time and the
inability
> of at least SOME systems to adjust to those, I would certainly
agree
> that this is true in a lot of cases. My particular preference in
> this regard is to write systems that make their own adjustments on
> the fly for changing conditions as opposed to testing short samples
> of data on a walk forward basis.
>
> Fred
>
> --- In amibroker@xxxxxxxxxxxxxxx, "Howard Bandy" <howardbandy@xxxx>
> wrote:
> > Hi Fred -
> >
> >
> >
> > If I look at the equity curves of two trading systems, one that
has
> been
> > upward sloping and smooth, and the other irregular, that tells me
> that one
> > trading system has been better than the other. If I project into
> the
> > future, I only have past behavior to use as a guide. So my
> preference is
> > the trading system associated with the better equity curve. Am I
> missing
> > something?
> >
> >
> >
> > Howard
> >
> >
> >
> > -----Original Message-----
> > From: Fred [mailto:fctonetti@x...]
> > Sent: Sunday, October 19, 2003 10:24 AM
> > To: amibroker@xxxxxxxxxxxxxxx
> > Subject: Objective functions (was RE: [amibroker] Re:
Optimization -
> - again)
> >
> >
> >
> > That IS what I was trying to say. I suspect because equity feed
> back
> > is like looking in a rear view mirror, great for letting us know
> > where we were and how we could have adjusted the past to make it
> > better, but that's about it.
> >
> > --- In amibroker@xxxxxxxxxxxxxxx, "Dave Merrill" <dmerrill@xxxx>
> > wrote:
> > > don't think I get what you mean here fred.
> > >
> > > you can't be saying that metrics on the equity curve of a
trading
> > strategy
> > > or its parameters aren't useful, right? that's the only thing
we
> > have to
> > > judge the effectiveness of our methods and settings.
> > >
> > > so you must be saying that equity feedback isn't a useful
concept,
> > > regardless of how you measure "good" equity. do I have that
right?
> > >
> > > if so, as I've said, my experience agrees -- none of the
> indicators
> > I've
> > > tried are wonderfully profitable when auto-optimized this way.
I
> > just cannot
> > > for the life of me understand why that's the case, if backtests
> > tell us
> > > anything useful about future performance.
> > >
> > > if I've misunderstood completely, my apoligies (:-)
> > >
> > > dave
> > > Like a lot of other things that sound like they SHOULD work,
I
> > have
> > > never found metrics related to equity curve feedback to be of
> much
> > > value in the determination of system parameter values.
> > >
> > > --- In amibroker@xxxxxxxxxxxxxxx, "Dave Merrill"
<dmerrill@xxxx>
> > > wrote:
> > > > interesting as usual howard (:-). one piece I wanted to
drill
> > into
> > > a bit.
> > > >
> > > > I wonder what the effect of using performance measures that
> > > concentrate on
> > > > certain things at the expense of others actually is.
> > > >
> > > > for example, my auto-optimization stuff currently uses
simple
> > > profit per bar
> > > > to choose parameter values. my gut-level assumption was
that
> > since
> > > it was
> > > > ignoring drawdown (among other things), the resulting
systems
> > might
> > > have
> > > > higher drawdown than I was comfortable with, but that
profit
> per
> > > bar should
> > > > be as good as the trading method could produce.
> > > >
> > > > maybe that's not the case. maybe by choosing a more balanced
> > > success metric,
> > > > not only would the other factors not considered by my
> simplistic
> > > first pass
> > > > metric be improved, but profitability might be improved as
> well.
> > > >
> > > > is this something you've investigated or thought about?
> anyone
> > else?
> > > >
> > > > dave
> > > > Note ? it is perfectly valid to have different objective
> > > functions for
> > > > different purposes. For example, I might be modeling the
> > behavior
> > > of a
> > > > sector, say oil services, with the intent of trading
> individual
> > > stocks based
> > > > on what I learn. In this case, I want to identify periods
of
> > > rising prices
> > > > with careful attention to turning points, but without much
> > interest
> > > in
> > > > overall profit. On the other hand, I might be modeling
> > individual
> > > high beta
> > > > tech stocks, in which case my model includes several stop
loss
> > > techniques
> > > > and I care most about avoiding drawdowns.
> > > >
> > > >
> > > >
> > > > Thanks,
> > > >
> > > > Howard
> > >
> > >
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