Adjusting for the interval effect bias in beta coefficients on a thin security market: application of a lag distribution model

Abstract

The problems of measuring the systematic risk of a security are discussed. Prior research indicates that estimates for systematic risk, i.e. beta coefficients, are greatly affected by infrequent trading and the selected return interval. This is the case especially in thin stock markets. A lag distribution model to estimate betas is introduced. In addition, the empirical properties of these betas are compared with several alternative beta estimates using data from a thin security market. The empirical evidence suggests that the estimated betas based on this model are less biased by infrequent trading than the betas based on several other estimation procedures proposed in the literature.