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Brian,
thanks for your detailed answer!
>
> At page 91,in his book, (Entries and Exits chapter) Howard gives some
> very good (random entry) examples of how we can get an estimation for
> the 'standardized binomial expectancy' of any market i.e. you can get
> the mean expected wins for the actual market you are testing your
> system in and use that in the Z score calculation - I think you would
> be better to use random entries with an exit after a set number of
> days == the average time your system trades are in the market.
That's a good hint - thanks for that.
>
> I am still learning AB myself so I am not sure if we can implement
> Howards Z equation directly in AB - you will probably have to do it
> outside somewhere - I haven't figured out how we can get the SD of a
> trade series (from a backtest) in AB - anyway we don't have built in
> stats tables (I suppose you could manually plug in the typical Z
> scores).
>
> I'm exporting to Excel and doing my evaluations there, but I don't
> get that fancy.
I also think that it can only be done in Excel (or, perhaps,
OpenOffice).
> > > What do you think about this metric?
>
> I think it is a very conservative measure.
Obviously!
>
> One of the problems we have, in evaluation, is that 'academic'
> statistics filtered into freelance trading via institutional
> investing - nothing against academics or institutional traders but
> their focus is somewhat different to freelance traders.
You're probably right. On the other hand, Arthur Merrill wasn't a pure
academic. He was the long-time editor of "Technical Trends" and
considered a legendary market guru. I mean, he wouldn't have had that
reputation if his methods had been of merely academic or theoretical
value. ;-)
>
> Neither is absolutely true, so the stats we are using are
> approximations (of course the data we are using is only an
> approximation anyway) - hence the doubts about Merrill's Chi.
I think I inderstand what you're getting at, and I'm looking forward for
what you will present to us in the UKB some day ...
>
> Based on that work I am using PowerFactor, with sample error, to
> guestimate significance (I can quickly do that in my head).
... but I'm not sure what you mean with PowerFactor - isn't that a
concept in electrics?
>
> This problem is especially prevalent in mid - long term trading - say
> indicators with long lookbacks are used - then the number of signals
> available tends towards becoming a rare event and the trader then can
> only see a small part of the longterm (10000 plus) trades - the
> trader soon runs out of clean data and can't get high enough trade
> counts.
>
> That is why I like shorter term trading (intraday to 2-3 day cycles)
> where I can take advantage of statistical smoothing (I quickly
> approach my theoretical edge i.e. relative to the calendar days).
I agree. That's what I'm also heading to.
> As I said - please use 'my' theories at your own risk, at least until
> after I post on the topic, and the mathematicians in the forum have a
> chance to bash up my hypotheses.
I'm anxiously waiting for your results, and in the meantime I will
google for the "brian method" to get some deeper understanding. ;-)
Thanks again - it's always a pleasure to read your posts!
Best regards,
Thomas
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