Paul,
Sensitivity analysis during in sample optimization is not directly related to finding a new fitness high. That would be too restrictive and might well preclude finding solutions that have better fitness after being adjusted for sensitivity. _____ From: amibroker@yahoogroups.com [mailto:[EMAIL PROTECTED] On Behalf Of Paul Ho Sent: Wednesday, May 07, 2008 8:37 AM To: amibroker@yahoogroups.com Subject: [amibroker] Re: Fitness Criteria that incorporates Walk Forward Result Hi Fred Yes, I want to use the composite fitness to compare different systems and or use it as a feedback in deciding on different parameter sets of the same system, This is not too dissimilar to how sensitivity analysis is incorporated into the fitness criteria. The only difference is that sensitivity analysis during optimization, and walk forward is done after a new fitness high is found. Instead of using the insample fitness as the selection criteria for the best fit system, the composite is criteria is used to choose among the various peak values in one system or in different systems. What you said "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" is particularly interesting. Because you are addressing a similar problem but using a different method, in your case, you change the time frame and reoptimize. In my case, I am looking at refining my fitness criteria so I might end up in choosing a different optimized parameter set in the same time frame. Paul. --- In [EMAIL PROTECTED] <mailto:amibroker%40yahoogroups.com> ps.com, Fred Tonetti <[EMAIL PROTECTED]> wrote: > > 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:amibroker%40yahoogroups.com> ps.com [mailto:[EMAIL PROTECTED] <mailto:amibroker%40yahoogroups.com> ps.com] On Behalf > Of Paul Ho > Sent: Tuesday, May 06, 2008 10:41 AM > To: [EMAIL PROTECTED] <mailto:amibroker%40yahoogroups.com> ps.com > 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. >
