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Abstract
Our article analyzes the performance of different methods to adjust beta. Specifically, we compare the standard ordinary least squares (OLS) regression method with the Blume and t-distribution methods from the point of view of reference-day risk. Our results indicate that the t-distribution method minimizes the variation due to changes in the reference day.
Acknowledgments
The authors are grateful for useful comments from Thomas Boucher, Editor in Chief, an anonymous referee, as well as the participants of the brown bag seminars at the Faculty of Economics and Business of Universidad de Chile.
Additional information
Notes on contributors
Marcelo Gonzalez
Marcelo Gonzalez is an assistant professor at Universidad de Chile's Faculty of Economics and Business. Professor Gonzalez is the academic director of the executive Master of Finance program at this university (evening version). Marcelo is cofounder of MQA Ltda., a small consulting firm. He holds an M.A. from the Economics Department and a Ph.D(c) from the Business School, both at Tulane University. His research interests include corporate finance and behavioral finance.
Arturo Rodriguez
Arturo Rodriguez is an assistant professor at Universidad de Chile's Faculty of Economics and Business. Professor Rodriguez is the academic director of the executive Master of Finance program at this University (weekend version). He holds an M.A. from the Economics Department and a Ph.D. from the Business School, both at Tulane University. His research interests include corporate payout policy, market efficiency and pricing, and the use derivatives for bankruptcy prediction.
Roberto Stein
Roberto Stein is currently an assistant professor of finance at Universidad de Chile's Faculty of Economics and Business. He received a Ph.D. in finance from the A.B. Freeman School of Business at Tulane University, and has also received MBAs from Universidad de Chile and Tulane University, as well as a B.S. in civil engineering from Universidad Católica de Chile. Prior to pursuing an academic career, Roberto has worked in various capacities in logistics, natural gas engineering projects, and the financial services industry. His research interests include mutual fund analysis, empirical asset pricing, and the development and application of simulation-based numerical methodologies in statistics and econometrics.