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Hi Dave –
It sounds to me like you Do get it.
If the out of sample results based on your
auto-optimization are profitable, you have confidence that the current set of
parameters will be profitable. If the OOS are not profitable, the model needs
to be redesigned.
I see equity feedback as a great tool in
system design and evaluation.
Howard
-----Original Message-----
From: Dave Merrill
[mailto:dmerrill@xxxxxxx]
Sent: Sunday, October 19, 2003
2:08 PM
To: amibroker@xxxxxxxxxxxxxxx
Subject: RE: Objective functions
(was RE: [amibroker] Re: Optimization -- again)
<span
>I'm not trying to
be argumentative, honest (:-)... I'm more than a little sick of saying the same
thing over and over, but I j u s t d o n ' t g e
t i t .
<span
>------------------------------
<span
>I fail to see the
huge difference in principle between equity feedback and backtesting.
<span
>let's start by
assuming that backtesting performance of a system and its parameters over some
period of past data tells you something about its future performance. it's not
a perfect predictor, but it's the best evidence we have. does this seem like a
reasonable starting point? what alternative is there?
<span
>if that's true,
why is it better to do it only once? what justification is there for picking one
examination period over another? clearly market behavior will change
continually after that. don't we need a way of working that looks at what's
been happening and evolves our response?
<span
>sounds like we
examine performance up to some point and adjust, trade with the best-choice
system and parameters for a while, then examine and adjust again later. make
sense? what alternative is there?
<span
>so then, how
often do we re-examine performance history? to put it differently, how long do
we ignore any changes in market dynamics that may or may not have occurred? why
would intermittently refusing to look and respond improve system performance or
reliability?
<span
>
<span
>if that needs to
be done, why not have the system itself do it, as part of its inherent
operation? why is it better for us as an outside agent to periodically run
some separate tests, reach into the internals of the system, and change stuff?
<span
>
<span
>or should we just
continue with the system and parameters we choose at the beginning? are
they somehow more valid than what we'd choose later, using the same
backtesting methods, but on a different date range of data?
<span
>
<span
>------------------------------
<span
>
<span
>I realize that
even if it seems to make sense logically, this all a complete crock if no systems
put together like this even backtest well, never mind forward testing.
<span
>
<span
>but every time I
think about abandoning this line of research, it seems like the first thing I'd
want to do with a new system would be (let me guess), test and possibly adjust
it using data up to some date, then run with it for a while after that and see
if equity growth is good. if it is, I'd want to lather, rinse and repeat with
other in and out of sample data, to make sure that wasn't coincidence.
<span
>
<span
>sounds way too
familiar to be a completely different animal.
<span
>dave
From:<font size=2
face=Tahoma> Fred
[mailto:fctonetti@xxxxxxxxx]
<span
>
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 <font size=2
face="Courier New">
where we were and how we could have
adjusted the past to make it <span
>
better, but that's about it.
<font size=3
face="Times New Roman">
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BUG REPORTS to bugs@xxxxxxxxxxxxx<font size=2
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>
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