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<SPAN
class=163254812-19102003>interesting as usual howard (:-). one piece I wanted to
drill into a bit.
<SPAN
class=163254812-19102003>
<SPAN
class=163254812-19102003>I wonder what the effect of using performance measures
that concentrate on certain things at the expense of others actually is.
<SPAN
class=163254812-19102003>
<SPAN
class=163254812-19102003>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.
<SPAN
class=163254812-19102003>
<SPAN
class=163254812-19102003>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.
<SPAN
class=163254812-19102003>
<SPAN
class=163254812-19102003>is this something you've investigated or thought about?
anyone else?
<SPAN
class=163254812-19102003>
<SPAN
class=163254812-19102003>dave
<BLOCKQUOTE dir=ltr
>
<FONT face=Arial color=navy
size=2>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.
<SPAN
><FONT
face=Arial color=navy size=2><SPAN
>
<SPAN
>Thanks,
<SPAN
>Howard
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