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Heteroskedasticity in Stock Returns

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  • G. William Schwert
  • Paul J. Seguin

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.

Suggested Citation

  • G. William Schwert & Paul J. Seguin, 1989. "Heteroskedasticity in Stock Returns," NBER Working Papers 2956, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:2956
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