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Devon McCormick <[email protected]> writes:

> Quantiles are a very useful way to compare stochastic models, e.g. what's
> the performance of bottom-decile PE stocks versus top-decile ones?  And if
> there is a consistent relation between the top and bottom deciles, does it
> also hold if we use 11-tiles or 9-tiles?

Note that Tukey, in Understanding Robust and Exploratory Data Analysis,
uses fourths instead of quartiles (perhaps someone mentioned it here,
but, if so, I missed it).

Devon, you bring up a question I've been puzzling about recently when
you mention stocks.  The Shannon Nyquist sampling theorem says one has
to sample at twice the highest frequency of energy in the signal we're
measuring, and (a little) research I've found by Hinich and by someone
else at the Federal Reserve building on that suggests that stocks have
significant energy at frequencies above daily.  Thus modeling unfiltered
closing prices would seem to give erroneous results.

It's not limited to stock prices, though; presumably quarterly business
results, economic indicators, and others could all suffer from the same
problem.

That's challenging, though.  In some domains, it's very expensive to
collect the data at a high enough frequency.  If you can gather the
fully sampled data, then you can filter and decimate it to reduce the
sample rate of the final data to that which you would like.  

Do you have insights to suggest how much this problem is known amongst
those who do model time series professionally?  I don't see mention of
it, for example, in my copy of the Box - Jenkins Time Series Analysis.

Bill
- -- 
Bill Harris                      http://facilitatedsystems.com/weblog/
Facilitated Systems                              Everett, WA 98208 USA
http://facilitatedsystems.com/                  phone: +1 425 374-1845
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