Waston M., Bollerslev T., Rusell J.(eds.) Volatility and Time Series Econometrics: Essays in Honor of Robert Engle

Oxford, Oxford University Press, 2010. - 432p.
Robert Engle received the Nobel Prize for Economics in 2003 for his work in time series econometrics. This book contains 16 original research contributions by some the leading academic researchers in the fields of time series econometrics, forecasting, volatility modelling, financial econometrics and urban economics, along with historical perspectives related to field of time series econometrics more generally. Engle's Nobel Prize citation focuses on his path-breaking work on autoregressive conditional heteroskedasticity (ARCH) and the profound effect that this work has had on the field of financial econometrics. Several of the chapters focus on conditional heteroskedasticity, and develop the ideas of Engle's Nobel Prize winning work. Engle's work has had its most profound effect on the modelling of financial variables and several of the chapters use newly developed time series methods to study the behavior of financial variables. Each of the 16 chapters may be read in isolation, but they all importantly build on and relate to the seminal work by Nobel Laureate Robert F. Engle.About the SeriesAdvanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.A History of Econometrics at the University of California, San Diego: A Personal Viewpoint.The Founding Years:
The Middle Years:
The Changing Years:
Visitors.
The way the world of econometrics has changed.
Visitors and students.
The Long Run Shift-Share: Modeling the Sources of Metropolitan Sectoral Fluctuations.A general model and some specializations.
Data and evidence.
Summary and conclusions.
The Evolution of National and Regional Factors in US Housing Construction.The state building permits data set.
The DFM-SV model.
Empirical results.
Discussion and conclusions.
Modeling UK Inflation Uncertainty, 1958–2006.UK inflation and the policy environment.
Re-estimating the original ARCH model.
The nonstationary behavior of UK inflation.
Measures of inflation forecast uncertainty.
Uncertainty and the level of inflation.Macroeconomics and ARCH.GARCH and inference about the mean.
Application : Measuring market expectations of what the Federal Reserve is going to do next.
Application : Using the Taylor Rule to summarize changes in Federal Reserve policy.
Conclusions.
Macroeconomic Volatility and Stock Market Volatility, World-Wide.Data.
Empirical results.
Variations and extensions.
Concluding remark.
Measuring Downside Risk – Realized Semivariance.Econometric theory.
More empirical work.
Additional remarks.
Conclusions.
Glossary to ARCH (GARCH).
An Automatic Test of Super Exogeneity.Detectable shifts.
Super exogeneity in a regression context.
Impulse saturation.
Null rejection frequency of the impulse-based test.
Potency at stage.
Super-exogeneity failure.
Simulating the potencies of the automatic super-exogeneity test.
Testing super exogeneity in UK money demand.Generalized Forecast Errors, a Change of Measure, and Forecast Optimality.Testable implications under general loss functions.
Properties under a change of measure.
Numerical example and an application to US inflation.Multivariate Autocontours for Specification Testing in Multivariate GARCH Models.Testing methodology.
Monte Carlo simulations.
Empirical applications.
Concluding remarks.
Modeling Autoregressive Conditional Skewness and Kurtosis with Multi-Quantile CAViaR.The MQ-CAViaR process and model.
MQ-CAViaR estimation: Consistency and asymptotic normality.
Consistent covariance matrix estimation.
Quantile-based measures of conditional skewness and kurtosis.
Application and simulation.Volatility Regimes and Global Equity Returns.
Volatility Regimes and Global Equity Returns.
Econometric methodology.
Data.
Global stock return dynamics.
Variance decompositions.
Economic interpretation: Oil, money, and tech shocks.
Implications for global portfolio allocation.A Multifactor, Nonlinear, Continuous-Time Model of Interest Rate Volatility Introduction.
The stochastic behavior of interest rates: Some evidence.
Estimation of a continuous-time multifactor diffusion process.
A generalized Longsta and Schwartz () model.Estimating the Implied Risk-Neutral Density for the US Market Portfolio.Review of the literature.
Extracting the risk-neutral density from options prices, in theory.
Extracting a risk-neutral density from options market prices, in practice.
Adding tails to the risk-neutral density.
Estimating the risk-neutral density for the S&P from S&P index options.
Concluding comments.
New Model for Limit Order Book Dynamics.The model.
Data.
Results.
Conclusions.