On the Intertemporal Risk-Return Relation: A Bayesian Model Comparison Perspective
The existing empirical studies indicate that inferences on the intertemporal relation between expected return and volatility are highly sensitive to empirical specifications of return dynamics. Glosten, Jagannathan, and Runkle (1993) attempt to resolve this confusing situation by examining several generalizations of the standard GARCH-M model. They conclude a negative risk-return relation solely based on the models that are identified through a variety of diagnostic tests as relatively “better models. It has not been shown, however, whether those selected models outperform the alternatives decisively or only marginally. To the extent the strength of sample evidences supporting those selected models is unclear, the inference that is made solely based on those selected models remain questionable because of model uncertainty concern. Our paper propose a Bayesian model comparison approach to explicitly assess the strength of the evidence in support of the models that typically indicate a negative risk-return relation. The empirically computed Bayes factors show that those models indeed outperform, at a decisive degree, the alternative models that suggest a contrary result. Further, with priors that slightly favor return nonpredictability, evidence still indicates a negative relation after model uncertainty is accounted for. Our study, therefore, complements the work of Glosten, Jagannathan, and Runkle (1993).
Leping Wang
School of Business, Singapore Management University, 469 Bukit Timah Road, Singapore 259756
国际会议
西安
英文
1-36
2006-07-17（万方平台首次上网日期，不代表论文的发表时间）