STATISTICS
Measuring Autocorrelation
Come Here Quick, Durbin Watson
by Ron McEwan
Here's how you can use the Durbin Watson statistic to measure the
autocorrelation of two securities.
One of the most powerful statistical tools
traders have at their disposal is the ability to measure the correlation
between two sets of time series data. There are many approaches to this.
One is to measure the relationship of stock prices (usually the closing
prices). Another method, common among portfolio analysts, is to measure
the correlation of the returns (daily, weekly, or monthly) of the underlying
data. The idea is that you would not want too many securities in the portfolio
that are highly correlated with each other (you do not want the same kind
of eggs in your basket). Yet another method is to measure the correlation
of the residuals of a regression line that has been applied to the data.
This is referred to as autocorrelation.
FIGURE 1: PEARSON CORRELATION. Here is the 60-day Pearson
correlation coefficient for 10 stocks selected from Market Topology as
having the highest 12-month correlation to AMAT.
...Continued in the April issue of Technical Analysis
of STOCKS & COMMODITIES
Excerpted from an article originally published in the April 2004
issue of Technical Analysis of STOCKS & COMMODITIES magazine. All rights
reserved. © Copyright 2004, Technical Analysis, Inc.
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