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Gary Fritz wrote:
>The only way I know of to get results like that is to curve-fit
>to the entire data series. That is, each point is calculated
>with full knowledge of past AND future points. A polynomial fit,
>as Audrey mentioned, is one possibility.
Looks that way to me too, come to think of it.
>Of course, you couldn't use that to trade, since you have no
>knowledge of future data points (bummer!). If that's what those
>charts really are, then they're just dummied-up pretty sales
>tools that couldn't actually be used for trading.
Not necessarily. You don't need future points to fit a polynomial
to data. Furthermore, you don't need a polynomial with many degrees
of freedom either, if you're concerned with seasonal tendencies as
seems to be the case here. A 3rd or 5th degree polynomial should be
sufficient for getting trends on a year's worth of data. Simply fit
it to 250 days (approx 1 year) and re-fit on every new bar, plotting
only the most current endpoint of the polynomial. This is no more
valid or invalid than using a SMA or EMA or linear regression
projection to identify a trend.
>he couldn't be using a polynomial-fit curve for his trading
>decisions.
I think he could in this context. Think of it this way: for markets
with seasonal tendencies, the tendencies average out to a sinewave
having a period of 1 year. A sinewave for a single period can be
well-approximated by a polynomial.
--
,|___ Alex Matulich -- alex@xxxxxxxxxxxxxx
// +__> Director of Research and Development
// \
// __) Unicorn Research Corporation -- http://unicorn.us.com
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