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.
