Estimating Beta
- 1 August 2016
- journal article
- research article
- Published by Cambridge University Press (CUP) in Journal of Financial and Quantitative Analysis
- Vol. 51 (4) , 1437-1466
Abstract
We conduct a comprehensive comparison of market beta estimation techniques. We study the performance of several historical, time-series model, and option-implied estimators for estimating realized market beta. Thereby, we find the hybrid methodology of Buss and Vilkov to consistently outperform all other approaches. In addition, all other approaches, including fully implied and dynamic conditional beta, based on generalized autoregressive conditional heteroskedasticity (GARCH) models, are dominated by a simple beta estimate based on historical (co-)variances and an approach based on the Kalman filter. Our conclusions remain unchanged after performing several robustness checks.Keywords
This publication has 53 references indexed in Scilit:
- Option-Implied Measures of Equity RiskReview of Finance, 2011
- Variance Risk PremiumsThe Review of Financial Studies, 2008
- Implied correlation index: A new measure of diversificationJournal of Futures Markets, 2004
- Dynamic Conditional CorrelationJournal of Business & Economic Statistics, 2002
- Spanning and derivative-security valuationJournal of Financial Economics, 2000
- The quality of market volatility forecasts implied by S&P 100 index option pricesJournal of Empirical Finance, 1998
- Predicting Volatility in the Foreign Exchange MarketThe Journal of Finance, 1995
- Modelling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized Arch ModelReview of Economics and Statistics, 1990
- Risk, Return, and Equilibrium: Empirical TestsJournal of Political Economy, 1973
- Equilibrium in a Capital Asset MarketEconometrica, 1966