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Journal Article
The news in financial asset returns
The notion that financial asset returns are predictors of future economic activity is widespread, but detailed analyses provide little support for financial markets? ability to reveal future economic activity. Even though the evidence on various indicators used by different researchers is mixed, the authors of this article explore the notion that financial markets reveal useful information about future economic activity. ; This article examines and answers two questions: First, what is a good way of extracting information about future economic activity from asset prices? Second, do financial ...
Journal Article
Financial market frictions
Market frictions, which exist even in efficient markets and change over time, impede trade but also offer profit opportunities. To provide a framework for understanding market frictions, the authors classify frictions into five categories.
Journal Article
Asset returns and economic risk
The capital asset pricing model (CAPM), favored by financial researchers and practitioners fifteen years ago, holds that the extra return on a risky asset comes from bearing market risk only. But newer evidence supports the intertemporal CAPM (I-CAPM) theory (Merton 1973), which suggests that the premium on any risky asset is related not only to market risk but also to additional economic variables. ; This article reviews and interprets recent advances in the asset pricing literature. The study seeks to shed light on the sources of economic risk that investors should track and hedge against ...
Working Paper
Too Good to Be True? Fallacies in Evaluating Risk Factor Models
This paper is concerned with statistical inference and model evaluation in possibly misspecified and unidentified linear asset-pricing models estimated by maximum likelihood and one-step generalized method of moments. Strikingly, when spurious factors (that is, factors that are uncorrelated with the returns on the test assets) are present, the models exhibit perfect fit, as measured by the squared correlation between the model's fitted expected returns and the average realized returns. Furthermore, factors that are spurious are selected with high probability, while factors that are useful are ...
Working Paper
On the Hansen-Jagannathan distance with a no-arbitrage constraint
We provide an in-depth analysis of the theoretical and statistical properties of the Hansen-Jagannathan (HJ) distance that incorporates a no-arbitrage constraint. We show that for stochastic discount factors (SDF) that are spanned by the returns on the test assets, testing the equality of HJ distances with no-arbitrage constraints is the same as testing the equality of HJ distances without no-arbitrage constraints. A discrepancy can exist only when at least one SDF is a function of factors that are poorly mimicked by the returns on the test assets. Under a joint normality assumption on the ...
Working Paper
Asymptotic variance approximations for invariant estimators in uncertain asset-pricing models
This paper derives explicit expressions for the asymptotic variances of the maximum likelihood and continuously updated GMM estimators under potentially misspecified models. The proposed misspecification-robust variance estimators allow the researcher to conduct valid inference on the model parameters even when the model is rejected by the data. Although the results for the maximum likelihood estimator are only applicable to linear asset-pricing models, the asymptotic distribution of the continuously updated GMM estimator is derived for general, possibly nonlinear, models. The large ...
Working Paper
Further results on the limiting distribution of GMM sample moment conditions
In this paper, we extend the results in Hansen (1982) regarding the asymptotic distribution of generalized method of moments (GMM) sample moment conditions. In particular, we show that the part of the scaled sample moment conditions that gives rise to degeneracy in the asymptotic normal distribution is T-consistent and has a nonstandard limiting distribution. We derive the asymptotic distribution for a given linear combination of the sample moment conditions and show how to conduct statistical inference. We demonstrate the finite-sample properties of the proposed asymptotic approximation ...
Working Paper
Robust inference in linear asset pricing models
We derive new results on the asymptotic behavior of the estimated parameters of a linear asset pricing model and their associated t-statistics in the presence of a factor that is independent of the returns. The inclusion of this "useless" factor in the model leads to a violation of the full rank (identification) condition and renders the inference nonstandard. We show that the estimated parameter associated with the useless factor diverges with the sample size but the misspecification-robust t-statistic is still well-behaved and has a standard normal limiting distribution. The asymptotic ...
Working Paper
Minimum-variance kernels, economic risk premia, and tests of multi-beta models
This paper uses minimum-variance (MV) admissible kernels to estimate risk premia associated with economic risk variables and to test multi-beta models. Estimating risk premia using MV kernels is appealing because it avoids the need to 1) identify all relevant sources of risk and 2) assume a linear factor model for asset returns. Testing multi-beta models in terms of restricted MV kernels has the advantage that 1) the candidate kernel has the smallest volatility and 2) test statistics are easy to interpret in terms of Sharpe ratios. The authors find that several economic variables command ...
Working Paper
Specification tests of asset pricing models using excess returns
We discuss the impact of different formulations of asset pricing models on the outcome of specification tests that are performed using excess returns. It is generally believed that when only excess returns are used for testing asset pricing models, the mean of the stochastic discount factor (SDF) does not matter. We show that the mean of the candidate SDF is only irrelevant when the model is correct. When the model is misspecified, the mean of the SDF can be a very important determinant of the specification test statistic, and it also heavily influences the relative rankings of competing ...