<heading id="h1" level="1" implicit="yes" format="display">Abstract</heading>The empirical finance literature reveals that conditional models estimated with monthly data generally improve fund performance. Furthermore, it has been shown that using daily instead of monthly returns in an unconditional framework increases the proportion of abnormal performances...

This paper provides a comprehensive study of the syndicate structure and its relationship to information asymmetry and loan spread by using principal component analysis on a large set of 40 structure-related variables. A total of six structure components are identified and related to syndicate...

The estimation of multivariate GARCH time series models is a difficult task mainly due to the excessive parameterization exhibited by the problem, usually referred to as the "curse of dimensionality." For the VEC family, the number of parameters involved in the model grows as a polynomial of...

We show how to use asset market data to restrict the admissible region for the first-order autocorrelation of the stochastic discount factor (SDF). We interpret this statistic as a measure of a model's economic time variation across two periods. Estimating bounds for nominal and real SDFs at...

This paper develops a diagnostic tool for candidate performance measures that accounts for investor disagreement in mutual funds. We compare the evaluation for best clienteles, specified by an upper admissible performance bound, to the one for representative investors implicit in twelve models....

This paper investigates investor disagreement and clientele effects in performance evaluation by developing a measure that considers the best potential clienteles of mutual funds. In an incomplete market under law-of-one-price and no-good-deal conditions, we obtain an upper bound on admissible...

Asset returns implicitly contain information about the systematic and nonsystematic risks in an economy. Based solely on the law of one price condition, we extract this information by using a mean-variance frontier decomposition of returns, and exploit it to improve the assessment of...