ADJUSTING FOR THE INTERVAL EFFECT BIAS IN BETA-COEFFICIENTS ON A THINSECURITY MARKET - APPLICATION OF A LAG DISTRIBUTION MODEL

The problems of measuring the systematic risk of a security are discus sed. 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 m arkets. A lag distribution model to estimate betas is introduced. In a ddition, the empirical properties of these betas are compared with sev eral alternative beta estimates using data from a thin security market . The empirical evidence suggests that the estimated betas based on th is model are less biased by infrequent trading than the betas based on several other estimation procedures proposed in the literature.