Heteroskedasticity in Stock Returns
AbstractThe authors use predictions of aggregate stock return variances from daily data to estimate time-varying monthly variances for size-ranked portfolios. The authors 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 are then documented. Accounting for heteroskedasticity increases the evidence that risk-adjusted returns are related to firm size. The authors also estimate a constant correlation model. Portfolio volatilities predicted by this model are similar to those predicated by more complex multivariate generalized autoregressive conditional heteroskedasticity procedures. Copyright 1990 by American Finance Association.
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Bibliographic InfoArticle provided by American Finance Association in its journal Journal of Finance.
Volume (Year): 45 (1990)
Issue (Month): 4 (September)
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