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.
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number
2956.
Length: Date of creation: Feb 1991 Date of revision: Publication status: published as The Journal of Finance, Vol. XLV, No. 4, pp. 1129-1155, (September 1990). Handle: RePEc:nbr:nberwo:2956
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