Beta Regression Tendencies: Statistical and Real Causes

Elgers, Pieter T.; Haltiner, James R.; Hawthorne, William H.

doi:10.2307/2327160

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1982

1999

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Cited by 4 publications

(3 citation statements)

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“…Elgers, Haltiner, and Hawthorne (1979), and Elton, Gruber, and Urich (E‐G‐U) (1978) confirm the general results with updated data. In this paper we broaden the investigation through four avenues.…”

Section: Introductionsupporting

confidence: 85%

See 1 more Smart Citation

Investment Horizon, Diversification, and the Efficiency of Alternative Beta Forecasts

Hawawini

Vora

1982

J of Financial Research

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Section: Introductionsupporting

confidence: 85%

“…The proxy for the market portfolio is a value‐weighted index of 3950 securities appearing on the CRSP tape. The data used in this study cover a wider range of securities compared to those employed by Blume (1971, Blume 1975, and Blume 1979), Elgers, Haltiner, and Hawthorne (1979), Eubank and Zumwalt (1979), and Klemkosky and Martin (1975).…”

Section: Methodsmentioning

confidence: 99%

Investment Horizon, Diversification, and the Efficiency of Alternative Beta Forecasts

Hawawini

Vora

1982

J of Financial Research

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“…Elgers, Haltiner, and Hawthorne (1979) present evidence suggesting that the distribution of betas exhibits a tendency to collapse toward 1.0, although that conclusion is challenged by Blume (1979), based on an examination of a longer period. Results here show that the distribution is approximately stationary, supporting Blume.…”

mentioning

confidence: 77%

Is the Distribution of Betas Stationary?

Kolb

Rodríguez

1990

J of Financial Research

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The stationarity of the beta distribution for 1926-1985 is rejected for the entire period as a single sample. However, results for pairs of five-year estimation periods are more consistent with stationarity. Over all possible pairs of five-year periods, stationarity in the pair-wise tests is rejected more often than expected merely by chance. However, excluding two aberrant periods, the number of rejections of stationarity is consistent with chance. Therefore, the distribution of betas is nearly stationary in both the short run and long run. For practical purposes the distribution of betas may be regarded as stationary.

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