Estimating and Adjusting for the Intervalling-Effect Bias in Beta
提出并实证检验了两种方法，用于纠正普通最小二乘法估计贝塔时因交易摩擦导致的区间效应偏差，帮助更准确地估计公司资本成本。
The concept of beta as the measure of systematic risk has been widely accepted in the academic and financial community. Increasingly, betas are being used to estimate the cost of capital for corporations. Despite this, however, biases are generally present in ordinary least squares (OLS) estimates of beta. In particular, empirical estimates of beta are affected by friction in the trading process which delays the adjustment of a security's price to informational change and hence leads to an “intervalling-effect” bias. In this paper, we present and empirically test two procedures for correcting this bias. The first is to estimate the asymptotic value that OLS beta approaches as the differencing interval is lengthened without bound. The second procedure is to infer the value of beta by adjusting OLS beta for cross-sectional differences in the intervalling effect as a function of the depth of the market for a security (as measured by its value of shares outstanding). Our results suggest that a substantial correction is needed to get “true” beta estimates from short differencing interval data.