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The purpose of this paper is to examine, whether or not, the residuals of the market model (MM) are conditionally heteroscedastic; to examine, whether or not, there exists an intervalling effect in conditional heteroscedasticity in the residuals of the MM; to propose a simple data‐driven conditional capital asset pricing model (CAPM); and to examine the effect of conditional heteroscedasticity on the estimation of systematic risk.

Systematic risk coefficients (betas) are estimated at first using data of various frequencies from the Athens stock exchange without taking into account conditional heteroscedasticity. The same procedure is repeated, but this time taking into consideration conditional heteroscedasticity, which is found to exist. The results of the two approaches are compared.

Empirical evidence is provided for the existence of: conditional heteroscedasticity in MM residuals; a pronounced intervalling effect on autoregressive conditional heteroscedasticity (ARCH) in MM residuals; and generalized autoregressive conditional heteroscedasticity in mean type of conditional heteroscedasticity for the majority of cases where ARCH was present in MM residuals. These findings are conducive to a conditional CAPM, which takes into account the effect of conditional variance on expected returns, rather than the standard CAPM.

Better estimates of financial risk.

The intervalling effect in ARCH in the residuals of the MM is examined for the first time.