Empirical Dynamic Asset Pricing: Model Specification and Econometric Assessment

Empirical Dynamic Asset Pricing: Model Specification and Econometric Assessment

Empirical Dynamic Asset Pricing: Model Specification and Econometric Assessment

Empirical Dynamic Asset Pricing: Model Specification and Econometric Assessment

Synopsis

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.

Excerpt

This book explores the interplay among financial economic theory, the availability of relevant data, and the choice of econometric methodology in the empirical study of dynamic asset pricing models. Given the central roles of all of these ingredients, I have had to compromise on the depth of treatment that could be given to each of them. the end result is a book that presumes readers have had some Ph.D.-level exposure to basic probability theory and econometrics, and to discrete- and continuous-time asset pricing theory.

This book is organized into three blocks of chapters that, to a large extent, can be treated as separate modules. Chapters 1 to 6 of Part I provide an in-depth treatment of the econometric theory that is called upon in our discussions of empirical studies of dynamic asset pricing models. Readers who are more interested in the analysis of pricing models and wish to skip [ over this material may nevertheless find it useful to read Chapters 1 and 5. the former introduces many of the estimators and associated notation used throughout the book, and the latter introduces affine processes, which are central to much of the literature covered in the last module. the final chapter of Part I, Chapter 7, introduces a variety of parametric descriptive models for asset prices that accommodate stochastic volatility and jumps. Some of the key properties of the implied conditional distributions of these models are discussed, with particular attention given to the second through fourth moments of security returns. This material serves as background for our discussion of the econometric analysis of dynamic asset pricing models.

Part ii begins with a more formal introduction to the concept of a “pricing kernel” and relates this concept to both preference-based and noarbitrage models of asset prices. Chapter 9 examines the linear asset pricing relations—restrictions on the conditional means of returns—derived by restricting agents’ preferences or imposing distributional assumptions on the joint distributions of pricing kernels and asset returns. It is in this chapter that we discuss the vast literature on testing for serial correlation in asset returns.

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