A Note On Regression Analysis And Its Misinterpretations

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A Note On Regression Analysis And Its Misinterpretations
Peer Peer Olav Soelberg
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A similar argument holds, of course, for averages (or volatility differences) of High versus Low prices in a given time period.
Page 4.
If strong autocorrelation exists in X the least squares regression estimators will still be unbiased, but the standard error of estimate and the sample variance of the regression coefficients will be seriously (2") underestimated, i. E. Standard t-test and F-test tables are no longer valid.
Diagnosisj.
A test for the presence of autocorrelated disturbances is a
...vailable in form of the Durbin Watson d-statistic: n y n d = L ((y. - y. ) - (y. , - y. , )) /L. (y - y ); i = 1, 2, ,n .
i=2 ^ ^ ^'^ ^'^ i=l ^ ^ Adjusted for the number of explanatory variablesj tables are available for critical upper (significant autocorrelation) and lower (no significant auto- correlation) bounds of d. However, for intermediate values of d the Durbin Watson test is inconclusive, i. E. Can neither accept nor reject a hypothesis of independence among the regression disturbances.


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