This paper investigates nonlinear pricing kernels in which the risk factor is endogenously determined and preferences restrict the definition of the pricing kernel. These kernels potentially generate the empirical performance of nonlinear and multifactor models, while maintaining empirical power and avoiding ad hoc specifications of factors or functional form. Our test results indicate that preferencerestricted nonlinear pricing kernels are both admissible for the cross section of returns and are able to significantly improve upon linear single- and multifactor kernels. Further, the nonlinearities in the pricing kernel drive out the importance of the factors in the linear multi-factor model. A PRINCIPAL IMPLICATION OF THE Capital Asset Pricing Model ~CAPM! is that the pricing kernel is linear in a single factor, the portfolio of aggregate wealth. Numerous studies over the past two decades have documented violations of this restriction. 1 In response, researchers have examined the performance of alternative models of asset prices. These models have generally fallen into two classes: ~1! multifactor models such as Ross ’ APT or Merton’s ICAPM, in which factors in addition to the market return determine asset prices; or ~2! nonparametric models, such as Bansal et al. ~1993!, Bansal and Viswanathan ~1993!, and Chapman ~1997!, in which the pricing kernel is not

Existing studies of mutual fund market timing analyze monthly returns and find little evidence of timing ability. We show that daily tests are more powerful and that mutual funds exhibit significant timing ability more often in daily tests than in monthly tests. We construct a set of synthetic fund returns in order to control for spurious results. The daily timing coefficients of the majority of funds are significantly different from their synthetic counterparts. These results suggest that mutual funds may possess more timing ability than previously documented.

This paper shows how to evaluate the performance of managed portfolios using stochastic discount factors from continuous-time term structure models. These models imply empirical factors that include timeaverages of the underlying state variables. The approach addresses a performance measurement bias, described by Goetzmann, Ingersoll and Ivkovic (2000) and Ferson and Khang (2002), arising because fund managers may trade within the return measurement interval or hold positions in replicable options. The empirical factors contribute explanatory power in factor model regressions and reduce model pricing

In this paper we propose a nonparametric test for money managers ’ market timing ability and apply the analysis to a large sample of mutual funds that have different benchmark indices. The test (i) only requires the ex post returns of the funds and the benchmark portfolios; (ii) isolates timing from selectivity; (iii) separates the quality of timing information a money manager possesses from the aggressiveness with which she reacts to such information; and (iv) is robust to different information and incentive structures as well as underlying distributions. Theta—the parameter for timing ability—is on average below the neutral level (indexation) among actively managed domestic equity funds, and is very difficult to predict from observable fund characteristics. Overall, actively managed funds aiming at “timing the market ” in general fall short of just “riding with the market.”

I examine the stock market timing ability of two samples of hybrid mutual funds. I find that the inclusion of bond indices and a bond timing variable in a multi-factor Treynor and Mazuy model framework leads to substantially different conclusions concerning the stock market timing performance of these funds relative to the traditional Treynor Mazuy model. Coefficients from the traditional model are biased due to a strong correlation between various bond indices and the quadratic term used to measure timing ability in the model. Results from the multi-factor Treynor Mazuy model find less stock timing ability over the 1981-1991 time period than the Treynor Mazuy model and provide evidence of significant stock timing ability across the fund sample covering the 1992-2000 time period. A test designed to estimate stock portfolio changes during up and down stock markets provides some evidence that the results from the multi-factor Treynor Mazuy model are not spurious. 3

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The stochastic discount factor (SDF) method provides a unified general framework for econometric analysis of asset pricing models. There have been concerns that, compared to the classical beta method, the generality of the SDF method comes at the cost of efficiency in parameter estimation and power in specification tests. We establish the correct framework for comparing the two methods and show that the SDF method is as efficient as the beta method for estimating risk premiums. Also, the specification test based on the SDF method is as powerful as the one based on the beta method.

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Three concepts: stochastic discount factors, multi-beta pricing and mean variance efficiency, are at the core of modern empirical asset pricing. This paper reviews these paradigms and the relations among them, concentrating on conditional asset pricing models where lagged variables serve as instruments for publicly available information. The different paradigms are associated with different empirical methods. We review the variance bounds of Hansen and Jagannathan (1991), concentrating on extensions for conditioning information. Hansen's (1982) Generalized Method of Moments (GMM) is briefly reviewed as an organizing principle. Then, cross-sectional regression approaches as developed by Fama and MacBeth (1973) are reviewed and used to interpret empirical factors, such as those advocated by Fama and French (1993, 1996). Finally, we review the multivariate regression approach, popularized in the finance literature by Gibbons (1982) and others. A regression approach, with a beta pricing formulation, and a GMM approach with a stochastic discount factor formulation, may be considered competing paradigms for empirical work in asset pricing. This discussion clarifies the relations between the various approaches. Finally, we bring the models and methods together, with a review of the recent conditional performance evaluation literature, concentrating on mutual funds and

To measure the investment performance of a portfolio manager who may engage in market timing, it is necessary to consider both market level and volatility timing behavior as well as security selection ability. We develop and implement measures that accommodate all three components. A well specified measure of performance is the sum of the three components of ability. Estimating the measures on active US mutual funds, we find that allowing for market level and volatility timing, there is no evidence of investment ability at the level of broad groups of mutual funds, or when funds are sorted by expense ratio, return gap, active share or turnover. However, sorting by factor model R-squares confirms results in Amihud and Goyenko (2011), where the low R-square funds have better performance. * Ferson is the Ivadelle and Theodore Johnson Chair of Banking and Finance and a