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This paper estimates and tests consumption-based pricing kernels used in common equilibrium interest rate term structure models. In contrast to previous papers that use return orthogonality conditions, estimation in this paper is accomplished using moment conditions from a consumption-based option pricing equation and market prices of interest rate options. Thismethodology is more sensitive to preference misspecification over states associated with large changes in consumption than previous techniques. In addition, this methodology provides a large set of natural moment conditions to use in estimation and testing compared to an arbitrary choiceof return orthogonality conditions (e.g. instruments selected) used in GMM estimation. Eurodollar futures option prices and an estimated joint model of quarterly aggregate consumption and three month Eurodollar rates suggest are used to estimate and test pricing kernels based on logarithmic, power, and exponential utility functions. Using the market prices ofinterest rate options, evidence is found which is consistent with the equity premium puzzle; very high levels of risk aversion are needed to justify the observed premium associated with an investment position positively correlated with aggregate consumption. In addition, evidence isfound which is consistent with the riskfree rate puzzle: at high levels of risk-aversion for power or exponential utility, negative rates of time preference are needed to fit the observed low risklessinterest rates. These results suggest that typical term structure models are misspecified in terms of assumed preferences. This may have deleterious effects on model estimates of the interest rate term structure estimates and interest rate option prices.
A basic tenet of lognormal asset pricing models is that a risky currency is associated with a low pricing kernel volatility. Empirical evidence implies that a risky currency is associated with a relatively high interest rate. Taken together, these two statements associate high-interest-rate currencies with low pricing kernel volatility. We document evidence suggesting that the opposite is true. We approximate the volatility of the pricing kernel with the volatility of the short-term interest rate. We find that, across currencies, relatively high interest rate volatility is associated with relatively high interest rates. This contradicts the prediction of lognormal models. One possible reason is that our approximation of the volatility of the pricing kernel is inadequate. We argue that this is unlikely, in particular for questions involving currencies. We conclude that lognormal models of the pricing kernel are inadequate for explaining currency risk.
An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.
Written by one of the leading experts in the field, this book focuses on the interplay between model specification, data collection, and econometric testing of dynamic asset pricing models. The first several chapters provide an in-depth treatment of the econometric methods used in analyzing financial time-series models. The remainder explores the goodness-of-fit of preference-based and no-arbitrage models of equity returns and the term structure of interest rates; equity and fixed-income derivatives prices; and the prices of defaultable securities. Singleton addresses the restrictions on the joint distributions of asset returns and other economic variables implied by dynamic asset pricing models, as well as the interplay between model formulation and the choice of econometric estimation strategy. For each pricing problem, he provides a comprehensive overview of the empirical evidence on goodness-of-fit, with tables and graphs that facilitate critical assessment of the current state of the relevant literatures. As an added feature, Singleton includes throughout the book interesting tidbits of new research. These range from empirical results (not reported elsewhere, or updated from Singleton's previous papers) to new observations about model specification and new econometric methods for testing models. Clear and comprehensive, the book will appeal to researchers at financial institutions as well as advanced students of economics and finance, mathematics, and science.