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Why do the parameter values HAVE to be the same for all market types?
Parameter values have to fall within a same range of values (min &
max, for eg., 0 to 17% for sell and 0 to 28% for buy - buy eagerly,
sell reluctantly) for all markets, regardless of size or nature... I
don't need to do optimization for that, else you are curve-fitting.
How did I arrive at these parameters? Walk-forward testing...The
idea is to search for a signal within those range of values...
rgds, Pal
--- In amibroker@xxxxxxxxxxxxxxx, "Al Venosa" <advenosa@xxxx> wrote:
> Test *unoptimized* system on small, mid & large cap stocks in bull,
bear & sideways market conditions, same parameters for all.
>
> Mark: I agree up to a point. However, I'm not convinced that a
system must perform equally well across all markets using the same
parameter values, as you suggest. For example, if your system
performs admirably on the large cap stocks but not on the small cap
stocks, and within the large cap group the parameter values are
robust in and of themselves (i.e., no local maxima on the response
surface diagram), why not trade the system on large cap stocks? Also,
if you optimize the same system on small cap stocks and find the
parameter values are different from the large cap parameters but are
robust, why not use those different parameters for the small cap
issues? Why do the parameter values HAVE to be the same for all
market types?
>
> I use the stocks of the S&P 600, 400, and 500 indices and 2 year
bull, bear and sideways periods (for a total of 6 years per stock).
Rationale behind this: to find systems that profitably *tested out in
the past* on a large number of (somewhat tradeable) stocks of varying
market caps in multiple sectors under different market conditions,
under the assumption that this indicates the system is robust enough
to profitably *trade select issues in the future*.
>
> What I like to do is optimize over a period that encompasses BOTH
bullish AND bearish periods at the same time, like 1/2/99 to 12/31/01
or 02 as opposed to selecting separate 2-year bullish and 2-year
bearish periods. Usually, systems have a short component and a long
component to them (unless you only like to trade either long or short
per se). So, optimizing the parameters in a trading period that
includes both bull and bear market action lends a certain degree of
robustness in and of itself if you find a reasonably flat response
surface. Then, when you test in the succeeding OOS period and get a
reasonable performance similar to the IS period, with no local maxima
in the 3-D space of the trading diagram, then you have a fairly
robust system in my mind.
>
> ...My commission setting(s) in AB: proprietary, based on my
*slippage* research using data from actual trades. But you could
choose an arbitrary say, 1% to get started.
>
> What about setting 0 commissions just for starters when developing
your system. After you have done sufficient optimizing and forward
testing, then set your commissions/slippage to your 1% or 0.5% or
whatever and then see if the system crashes. If it does, trash it.
>
> Looking forward to your remaining 8 posts.
>
> Al Venosa
>
>
>
>
> ---
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