Beta (finance) - Estimation of Beta

Estimation of Beta

To estimate beta, one needs a list of returns for the asset and returns for the index; these returns can be daily, weekly or any period. Then one uses standard formulas from linear regression. The slope of the fitted line from the linear least-squares calculation is the estimated Beta. The y-intercept is the alpha.

Myron Scholes and Joseph Williams (1977) provided a model for estimating betas from nonsynchronous data.

Beta specifically gives the volatility ratio multiplied by the correlation of the plotted data. To take an extreme example, something may have a beta of zero even though it is highly volatile, provided it is uncorrelated with the market. Tofallis (2008) provides a discussion of this, together with a real example involving AT&T Inc. The graph showing monthly returns from AT&T is visibly more volatile than the index and yet the standard estimate of beta for this is less than one.

The relative volatility ratio described above is actually known as Total Beta (at least by appraisers who practice business valuation). Total Beta is equal to the identity: Beta/R or the standard deviation of the stock/standard deviation of the market (note: the relative volatility). Total Beta captures the security's risk as a stand-alone asset (because the correlation coefficient, R, has been removed from Beta), rather than part of a well-diversified portfolio. Because appraisers frequently value closely held companies as stand-alone assets, Total Beta is gaining acceptance in the business valuation industry. Appraisers can now use Total Beta in the following equation: Total Cost of Equity (TCOE) = risk-free rate + Total Beta*Equity Risk Premium. Once appraisers have a number of TCOE benchmarks, they can compare/contrast the risk factors present in these publicly traded benchmarks and the risks in their closely held company to better defend/support their valuations.