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Expectancy as put forward by Tharp or Matulich makes sense. It expresses
the edge a system has. The expectancy score ignores the ratio of
transaction costs to average wins and therefore is somewhat biased in
favour of marginal systems.
IMHO. That's the maths, anyway.
I personally use a simpler rule: No more than 60% losers, and at least 2:1
avg win/avg loss. If a system fails either or both criteria I look elsewhere.
YMMV.
At 17:54 14/11/02 +0000, mark.keenan@xxxxxxxxxxxxxx wrote:
> What do people think of the following extract taken from the
> following website - Following on from my previous email on
> optimization I have been using to assess optimal parameters and the
> results seem good
>
>
> Has anyone had experience of the "expectancy ratio" and do you think
> it looks sound??
>
>
>
> http://unicorn.us.com/trading/expectancy.html
>
>
>
>
>
> Expectancy is how much you expect each trade to earn for every dollar
> you risk. Opportunity is how often your strategy trades. You want to
> maximize the product of both.
>
>
> Expectancy = (AW * PW + AL * PL) / |AL|
> (expected profit per dollar risked)
>
> Expectancy score = Expectancy * Opportunity
>
> where
> Opportunity = NST * (365 / studydays)
> (opportunities to trade in a year)
> AW = average winning trade (excluding maximum win)
> PW = probability of winning (total wins / opportunities)
> AL = average losing trade (negative, excluding scratch losses)
> |AL| = absolute value of AL
> PL = probability of losing (nonscratch losses/opportunities)
> NST = number of non-scratch trades during the period under test
> (a scratch trade loses commission+slippage or less)
> studydays = calendar days of history being tested
>
>
> It is important to have the |AL| in the denominator of expectancy
> because this converts the expectancy to "risk units" -- earnings per
> dollar risked.
>
>
>
>
>
>
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