Minimum sum regression as the optimum robust algorithm in the computation of financial beta

Abstract

In the world of finance and portfolio management, "beta" refers to the sensitivity of a security's return to the sensitivity of the "market" portfolio and is an indication of the level of systematic risk, i.e. the amount of risk that a company's equity shares with the entire market. Portfolio managers must have accurate estimates of beta so as to adequately control risk in the portfolio. Typically, beta is estimated using Ordinary Least Squares, but OLS is reliant on some very stringent assumptions. Here, betas are computed and compared using OLS and four robust regression algorithms. Minimum sum regression is identified as the superior robust regression algorithm to estimate beta.