The conditional relationship between beta and returns: recent evidence from international stock markets
β Scribed by Gordon Y.N. Tang; Wai C. Shum
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 93 KB
- Volume
- 12
- Category
- Article
- ISSN
- 0969-5931
No coin nor oath required. For personal study only.
β¦ Synopsis
The risk-return relationship is one of the fundamental concepts in finance that is most important to investors and portfolio managers. Finance theory argues that the beta or systematic risk is the only relevant risk measure for investors. However, many studies have showed that betas and returns are not related empirically, no matter in domestic markets or in international stock markets. This paper examines the conditional relationship between beta and returns in international stock markets for the period from January 1991 to December 2000. After recognizing the fact that while expected returns are always positive, realized returns could be positive or negative, we find a significant positive relationship between beta and returns in up market periods (positive market excess returns) but a significant negative relationship in down market periods (negative market excess returns). The results are robust for both monthly and weekly returns and for two different proxies of the world market portfolio. Our findings indicate that beta is still a useful risk measure for portfolio managers in making optimal investment decisions.
π SIMILAR VOLUMES
rading in financial fumes currently accounts for roughly 35% of all futures T contracts, and it promises to become an even larger share of the market. Among those assets in which futures contracts are now traded are stock indices. Futures contracts on the Vdue4he Composite Average opened on Februar
## Abstract We analyse the ability of the conditional asset pricing models to explain the crossβsectional variation in UK stock returns. We examine conditional versions of the SharpeβLinter CAPM and the FamaβFrench threeβfactor model. The results indicate that the conditional singleβfactor model is
## Abstract In this paper we present an exact maximum likelihood treatment for the estimation of a Stochastic Volatility in Mean (SVM) model based on Monte Carlo simulation methods. The SVM model incorporates the unobserved volatility as an explanatory variable in the mean equation. The same extens
## Abstract Current literature is inconclusive as to whether idiosyncratic risk influences future stock returns and the direction of the impact. Earlier studies are based on historical realized volatility. Implied volatilities from option prices represent the market's assessment of future risk and