5

32

 

Princeton University Press (Visit publisher website)

2006

English

 

 

 

Advanced

 

 

Quantitative analysis, probability, statistics, estimation, stochastic processes, affine processes, Markov process, conditional characteristic function (CCF), conditional moment generating function (CMGF), continuous-time affine process, jump-diffusion process, standard Brownian motion, mean reversion, higher order moments, benchmark model, discrete-time affine process, transforms of affine jump processes, transforms of discrete-time affine processes, GMM estimation, ML estimation with known conditional density, simulated ML estimation using small time steps, approximate likelihood functions, characteristic function-based estimators, ML estimation by Fourier inversion, GMM estimation based on the CCF

 

Excerpt from Book - Among the most widely studied time-series processes in the empirical finance literature is the family of affine processes. Their popularity is attributable to their accommodation of stochastic volatility, jumps, and correlations among the risk factors driving asset returns, while leading to computationally tractable pricing relations and moment equations that can be used in estimation. In this chapter we overview some of the key properties of affine processes, in both their discrete- and continuous-time formulations.

 

5.1. Affine Processes: Overview
5.2. Continuous-Time Affine Processes
5.3. Discrete-Time Affine Processes
5.4. Transforms for Affine Processes
5.5. GMM Estimation of Affine Processes
5.6. ML Estimation of Affine Processes
5.7. Characteristic Function-Based Estimators

 

If you are interested in purchasing the book, please click here.

 

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.