Evaluating asset‐pricing models using the Hansen–Jagannathan bound: a Monte Carlo investigation
利用基于Hansen-Jagannathan边界的统计检验，计算真实模型的拒绝率，发现风险中性情况下的有限样本检验统计量分布极端，基于该分布的临界值能控制第一类错误，且对非可分偏好也适用，同时第二类错误率可接受。
Abstract We use recent statistical tests, based on a ‘distance’ between the model and the Hansen–Jagannathan bound, to compute the rejection rates of true models. For asset‐pricing models with time‐separable preferences, the finite‐sample distribution of the test statistic associated with the risk‐neutral case is extreme, in the sense that critical values based on this distribution deliver type I errors no larger than intended—regardless of risk aversion or the rate of time preference. We also show that these maximal‐type‐I‐error critical values are appropriate for both time and state non‐separable preferences and that they yield acceptably small type II error rates. Copyright © 2002 John Wiley & Sons, Ltd.