Heteroskedasticity in Stock Returns

34 Pages Posted: 15 Jan 2007 Last revised: 18 Apr 2022

See all articles by G. William Schwert

G. William Schwert

University of Rochester - Simon Business School; National Bureau of Economic Research (NBER)

Paul J. Seguin

University of Minnesota - Twin Cities - Carlson School of Management

Date Written: May 1989

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

Schwert, G. William and Seguin, Paul J., Heteroskedasticity in Stock Returns (May 1989). NBER Working Paper No. w2956, Available at SSRN: https://ssrn.com/abstract=461389

G. William Schwert (Contact Author)

University of Rochester - Simon Business School ( email )

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Paul J. Seguin

University of Minnesota - Twin Cities - Carlson School of Management ( email )

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