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Hi Rudolf
Excellent email ... there's so much to think about and try to piece
together.
Best regards
Walter
----- Original Message -----
From: "rudolf stricker" <lists@xxxxxxxxxxx>
To: <metastock@xxxxxxxxxxxxx>
Sent: Friday, February 04, 2000 7:49 AM
Subject: Re: Seasonals and technical analysis
|
| Hi Walter
|
| On Sat, 29 Jan 2000 09:02:28 -0500, you wrote:
|
| > ... fat tails are where the money is, therefore leptokurtosis reduction
| >removes the money.
|
| This, imo, is not true as a general statement, and I'll come back to
| this later.
|
| >The search for market inefficiencies is the search for
| >the money.
|
| This is ok for me, but has not to do necessarily anything with
| leptokurtosis.
|
| >One possible approach to take account of sets of outliers may now be to
use
| >the methods described in the previous chapter to remove the impact of
these
| >aberrant data in order to have a clearer view on the pattern of the
| >underlying time series.
|
| So this is a well recognized way to go, especially if I look at high
| volatile markets (like options), where even the detection of a rather
| small systematical main-stream "market inefficiency" will lead to
| reasonable profit, even if a trading system can only make e.g. 1% of
| the profit from MetaStock's "Maximum Profit System".
|
| >However, in empirical finance we tend to be less interested in the level
of
| >the asset price or stock market index since it is widely assumed that
such
| >time series can be best described as random walks.
|
| Imo, this is a more traditional view (like e.g. the "Efficient Market
| Hypothesis") and is not true in general.
| To give an example: First numerical tests that I did on weekly data of
| the german main index dax showed, that there is definitely an
| attractor with about 10 dimensions, and that the phase space can be
| represented with about 16 parameters. This is in strong disagreement
| with "random walk" (which I also tested for comparison).
| Ergo: There is plenty of room for TA-work directed to systematical
| "market inefficiencies", as long as enough people think e.g. the dax
| to be a "random walk" function.
| (BTW: Are there any comparable results from complexity analysis
| around?)
|
| >Therefore, another
| >approach is to exploit the fact that outliers emerge in clusters by
trying
| >to construct a time series model for the outliers themselves.
|
| Concentrating on outliers may be another kind of "market inefficiency"
| to look at for the construction of trading systems, especially if I
| had to deal with low volatile markets. But because of the nature of
| outliers, the statistical basis normally would be much more smaller,
| compared to the basis for main-stream "market inefficiencies", leading
| to corresponding problems in terms of generalization and consistency
| of profits.
|
| In short: Concentrating on outliers & tails is more like poker, and
| working on main-stream "market inefficiencies" is more like
| "Schafkopfen" (a bavarian version of skat).
|
| Therefore, for me it makes much more sense to concentrate on
| main-stream "market inefficiencies", because there are lots of
| high-volatile markets, lots of people believing in "random walk
| prices", and the generalization problem can be worked-out much better
| on a broad statistical basis.
|
| So the objective in system tests could be to
| => maximize profit,
| => minimizes the tail-area of the probability distribution of losses,
| => etc.
|
| This way money is not at all addressed by leptokurtosis (of the loss
| distribution) but rather by the integrals of the distributions of wins
| and losses. That is,
|
| > ... fat tails are where the money is, therefore leptokurtosis reduction
| >removes the money.
|
| is not valid in general, if the systems deal with main-stream "market
| inefficiencies".
|
| mfg rudolf stricker
| | Disclaimer: The views of this user are strictly his own.
|
|