Paul,
I understand what you are saying but I’m
not sure what you do with the combined fitness when you get it … Do you
use it to compare different systems to each other ?
Personally from the perspective of multiple
automated WF’s I am more interested in … When to reoptimize …
IO already has the capability to reoptimize
based on:
- Some static amount of time occurring during
the OOS i.e.
//IO: WFAuto: Rolling: 2: Weeks
- or in some undefined amount of time
based on some number of long/short entries/exits etc i.e.
//IO: WFAuto: Rolling: 2: LongEntrys
What I’ve been playing with recently
is something a little different that is also based on a variable amount of time
in the OOS i.e. the capability to automatically reoptimize when some condition
related to the performance metrics occurs during the out of sample period i.e. MDD
goes beyond some static threshold or when it goes beyond some relationship to
the same or different performance metrics of in sample.
For example …
Assume the In Sample Performance Metrics
are prefaced by IS and Out of Sample Performance Metrics are prefaced by OS
then one should be able to write ( in terms of IO Directives )
//IO: WFAuto: Rolling: Condition: OSMDD > 10 or OSMDD > 0.75 * ISMDD
In reality I suspect this is what most
people actually do i.e. find some yardstick(s) that tell them their system is
broken or about to be broken and then reoptimize at that time.
From: amibroker@xxxxxxxxxxxxxxx [mailto:amibroker@xxxxxxxxxxxxxxx] On Behalf Of Paul Ho
Sent: Tuesday, May 06, 2008 10:41
AM
To: amibroker@xxxxxxxxxxxxxxx
Subject: [amibroker] Fitness
Criteria that incorporates Walk Forward Result
Howard calls it the objective function. Fred calls it
Fitness. What I
meant by Fitness Criteria is a mathematical function on which fitness
or goodness of the system is judged, and is used as an objective
criteria to compare different systems, as a score in optimization.
My currrent question is - So why not incorporate the fitness in walk
forward analysis into our fitness criteria? What I am talking about
is to formalise the visual inspection process. I am not proposing to
use out of sample data for optimization purposes. Rather the
parameter set that has been previously optimized is forward tested
and a fitness is obtained and incorporated into the original criteria
to form a composite fitness.
For example. My current composite fitness is the geometric average of
In sample fitness and Out of sample fitness divided by the standard
deviation (?) of In sample and out of sample fitness.
Are there anybody doing something is this area? What are your
thoughts?
If you are wondering why not use visual inspection. My plan is to use
the computer to do most of the work and thats why I need a fitness
criteria.
Cheers
Paul.
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