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: [email protected] [mailto:[EMAIL PROTECTED] On Behalf Of Paul Ho Sent: Tuesday, May 06, 2008 10:41 AM To: [email protected] 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.
