The econometrics of financial markets /
John Y. Campbell, Andrew W. Lo, A. Craig MacKinlay.
- New Delhi : Princeton, N.J. ; New Age International, Princeton University Press, c1997.
- xviii, 611 p. : ill. ; 24 cm.
Includes bibliographical references (p. 541-585) and indexes.
List of Figures List of Tables Preface 1 Introduction 3 2 The Predictability of Asset Returns 27 3 Market Microstructure 83 4 Event-Study Analysis 149 5 The Capital Asset Pricing Model 181 6 Multifactor Pricing Models 219 7 Present-Value Relations 253 8 Intertemporal Equilibrium Models 291 9 Derivative Pricing Models 339 10 Fixed-Income Securities 395 11 Term-Structure Models 427 12 Nonlinearities in Financial Data 467 App. A.1 Linear Instrumental Variables 527 App. A.2 Generalized Method of Moments 532 App. A.3 Serially Correlated and Heteroskedastic Errors 534 App. A.4 GMM and Maximum Likelihood 536 References 541 Author Index 587 Subject Index 597
The past twenty years have seen an extraordinary growth in the use of quantitative methods in financial markets. Finance professionals now routinely use sophisticated statistical techniques in portfolio management, proprietary trading, risk management, financial consulting, and securities regulation. This graduate-level textbook is intended for PhD students, advanced MBA students, and industry professionals interested in the econometrics of financial modeling. The book covers the entire spectrum of empirical finance, including: the predictability of asset returns, tests of the Random Walk Hypothesis, the microstructure of securities markets, event analysis, the Capital Asset Pricing Model and the Arbitrage Pricing Theory, the term structure of interest rates, dynamic models of economic equilibrium, and nonlinear financial models such as ARCH, neural networks, statistical fractals, and chaos theory.
Each chapter develops statistical techniques within the context of a particular financial application. This exciting new text contains a unique and accessible combination of theory and practice, bringing state-of-the-art statistical techniques to the forefront of financial applications. Each chapter also includes a discussion of recent empirical evidence, for example, the rejection of the Random Walk Hypothesis, as well as problems designed to help readers incorporate what they have read into their own applications. taken from publisher's Site.