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No it is not an academic pursuit.
I have tried to put it into the simplest terms possible.
I can't see any other way to do it .. that is why I am going into so much detail in the discussions .... to draw out all of the nuances in evaluation.
I am learning new things from the different opinions.
Cheers.
brian_z
--- In amibroker@xxxxxxxxxxxxxxx, "Mubashar Virk" <mvirk67@xxx> wrote:
>
> Hi Brian,
>
> Please understand that I intend no disrespect. I am a fan of yours (I have almost have all of your AFLs) and other friends who are engaged in this higher order discussion.
> It is just that I feel that an ordinary trader:
>
> 1. needs to study the market over time
> 2. have a couple of simple systems (trend lines, averages, chart or price patterns).
> 3. have a money management system (stop-loss, equity commitment & allocation rules, etc.)
>
> Optimization, forward testing, oosings and aasings, and expectancies are more of academic pursuits, and results have limited application because of the "market is stationary" assumption.
>
>
>
> From: brian_z111
> Sent: Sunday, May 10, 2009 6:10 AM
> To: amibroker@xxxxxxxxxxxxxxx
> Subject: [amibroker] Re: Expectancy - and related--specifically K-rato
>
>
>
>
>
> Hi Mubashar,
>
> I am pretty certain that you have had a better math education than moi.
>
> I am surprized that you didn't answer the question for the benefit of the forum yourself.
>
> On a case by case basis your frequency distribution is probably not normal.
>
> However cumulative distribution is asymptotic and so if you reference the CD, for any trading system, it will give you the prob of receiving any particular value on your next trade.
>
> (This assumes that the market is stationary).
>
> It is very hard to find any firm footing, anywhere, in system evaluation but the CD is one place were we can start to approach something akin to certainty (as N --> oo)
>
> oo infinity
>
> In fact my .xl file on BiSim, posted at the Zboard) relies on this principle to do a quite good job of predicting the distribution of equity outcomes for a trading system with a non-N dist of the trades.
>
> --- In amibroker@xxxxxxxxxxxxxxx, "Mubashar Virk" <mvirk67@> wrote:
> >
> > Sorry to barge in, if I make 100 points on a system after oosing and aasing, what is the probability that I will make 100 points in actual real life trade?
> >
> >
> > From: Howard B
> > Sent: Saturday, May 09, 2009 5:45 PM
> > To: amibroker@xxxxxxxxxxxxxxx
> > Subject: Re: [amibroker] Re: Expectancy - and related--specifically K-rato
> >
> >
> >
> >
> >
> > Hi Keith, and all --
> >
> > Exactly my point.
> >
> > Thanks,
> > Howard
> >
> >
> >
> >
> > On Fri, May 8, 2009 at 10:26 PM, Keith McCombs <kmccombs@> wrote:
> >
> >
> >
> >
> > I've been told that no question is a "dumb question". So here goes:
> > If I have a system with good OOS performance, why should I care what the IS performance is? And similarly, why should I care what the OOS/IS ratio is?
> >
> > Couldn't it be more important that I have a high OOS/BH (buy and hold) ratio, so that I don't "confuse brains with a bull market"? Or at least something that gives me confidence that I haven't just accidentally stumbled on a once in a lifetime event, that, of coarse, will disappear the minute I start trading real money? Does OOS/IS ratio somehow help?
> > -- Keith
> >
> >
> >
> > brian_z111 wrote:
> > > I also create a t-test of the ave returns.
> >
> > How do you do that?
> >
> > --- In amibroker@xxxxxxxxxxxxxxx, Rajiv Arya <rajivarya87@> wrote:
> > >
> > >
> > > I also create a t-test of the ave returns.
> > >
> > > The in-sample is almost always significant
> > >
> > > And try to have the out of sample t-test greater than 1.64, which happens for about 50% for the out-of sample results.
> > >
> > >
> > >
> > >
> > >
> > >
> > >
> > > To: amibroker@xxxxxxxxxxxxxxx
> > > From: dloyer123@
> > > Date: Sat, 9 May 2009 03:03:16 +0000
> > > Subject: [amibroker] Re: Expectancy - and related--specifically K-rato
> > >
> > >
> > >
> > >
> > >
> > >
> > >
> > > --- In amibroker@xxxxxxxxxxxxxxx, Rajiv Arya <rajivarya87@> wrote:
> > > >
> > > >
> > > > I like to compute a ratio of the out-sample metric and divide it by the in-sample metric.
> > > >
> > > > And I like to look for multiple runs of out-sample/in-sample ratio to be above 0.5 and with little fluctuation.
> > > >
> > >
> > > That is similar to Pardo's WFE (Walk forward efficiency), or a measure of how much curve fitting inflated test results. Pardo suggests taking the concatenated out of sample returns and divide by the result treating the entire combined data set as in sample. Anything below 0.65 will probably not trade well live. The higher, the better.
> > >
> > >
> > >
> > >
> > >
> > >
> > >
> > >
> > >
> > > __________________________________________________________
> > > Hotmail® has a new way to see what's up with your friends.
> > > http://windowslive.com/Tutorial/Hotmail/WhatsNew?ocid=TXT_TAGLM_WL_HM_Tutorial_WhatsNew1_052009
> > >
> >
>
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