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Heteroskedasticity in Stock Returns

G. Schwert and Paul J. Seguin

No 2956, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We use predictions of aggregate stock return variances from daily data to estimate time varying monthly variances for size-ranked portfolios. We propose and estimate a single factor model of heteroskedasticity for portfolio returns. This model implies time-varying betas. Implications of heteroskedasticity and time-varying betas for tests of the capital asset pricing model (CAPM) are then documented. Accounting for heteroskedasticity increases the evidence that risk-adjusted returns are related to firm size. We also estimate a constant correlation model. Portfolio volatilities predicted by this model are similar to those predicted by more complex multivariate generalized-autoregressive- conditional- heteroskedasticity (GARCH) procedures.

Date: 1989-05
Note: ME
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Published as The Journal of Finance, Vol. XLV, No. 4, pp. 1129-1155, (September 1990).

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