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 Series Advanced 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.

Mark Watson is the Howard Harrison and Gabrielle Snyder Beck Professor of Economics and Public Affairs at Princeton University and a research associate at the National Bureau of Economic Research. He is a fellow of the American Academy of Arts and Sciences and of the Econometric Society. His research focuses on time-series econometrics, empirical macroeconomics, and macroeconomic forecasting. He has published articles in these areas and is the author (with James Stock) of Introduction to Econometrics, a leading undergraduate textbook. Watson has served on the editorial board of several journals including the American Economic Review, Journal of Applied Econometrics, Econometrica, the Journal of Business and Economic Statistics, the Journal of Monetary Economics, and Macroeconomic Dynamics. He currently serves as a Co-Editor of the Review of Economics and Statistics. He has served as a consultant for the Federal Reserve Banks of Chicago and Richmond. Tim Bollerslev is the first Juanita and Clifton Kreps Distinguished Professor of Economics at Duke University, and Professor of Finance at the Fuqua School of Business at Duke University. He is an elected Fellow of the Econometric Society, a Fellow of the Journal of Econometrics, and a long time Research Associate at the National Bureau of Economic Research. He is also affiliated with the Center for Research in Econometric Analysis of Time Series at the University of Aarhus, Denmark. Bollerslev is particularly well-known for his invention of the GARCH model and his work on financial market volatility and high-frequency financial data. He is a co-editor for the Journal of Applied Econometrics, and has previously served on the editorial board for more than ten other academic journals. Professor Bollerslev received his M.S. degree in economics and mathematics from the University from the University of Aarhus, Denmark, and his Ph.D. degree in economics from the University of California, San Diego.

Jeffrey R. Russell is Professor of Econometrics and Statistics at the University of Chicago Booth School of Economics. He conducts research on financial econometrics, time series, applied econometrics, empirical market microstructure, and high-frequency financial data. Russell's recent research has focused on using intraday price data to measure and predict financial asset volatility. His work has appeared in the Review of Economic Studies, Journal of Financial Economics and Econometrica. His research is supported by a Morgan Stanley Equity Microstructure Grant and he is the recipient of an Alfred P. Sloan Doctoral Dissertation Fellowship. In addition to teaching and research, Russell is an associate editor of the Journal of Applied Econometrics and the Journal of Financial Econometrics and he also serves on the NASDAQ Board of Economic Advisors.

Introduction1. Measuring Downside Risk- Realized Semivariance, Ole E. Barndorff-Nielsen, Solja Kinnebrock and Neil Shephard2. Modelling UK Inflation Uncertainty, 1958-2006, Gianna Boero, Jeremy Smith and Kenneth F. Wallis3. Glossary to ARCH, Tim Bollerslev4. A Multifactor Nonlinear, Continuous-time Model of Interest Rate Volatility, Jacob Boudoukh, Christopher Downing, Matthew Richardson, Richard Stanton and Robert F. Whitelaw5. Volatility Regimes and Global Equity Returns, Luis Catão and Allan Timmerman6. The Long Run Shift-Share: Modelling the Sources of Metropolitan Sectoral Fluctuations, N. Edward Coulson7. Macroeconomic Volatility and Stock Market Volatility, Worldwide, Francis X. Diebold and Kamil Yilmaz8. Estimating the Implied Risk Neutral Density for the U.S. Market Portfolio, Stephen Figlewski9. Multivariate Autocontours for Specification Testing in Multivariate GARCH Models, Gloria González-Rivera and Emre Yoldas10. A History of Econometrics at the University of California, San Diego, A Personal Viewpoint, Clive W.J. Granger11. Macroeconomics and ARCH, James D. Hamilton12. An Automatic test of Super Exogeneity, David F. Hendry and Carlos Santos13. Changes in the Volatility of Residential Investment in the United States, James H. Stock and Mark W. Watson14. Generalized Forecast Errors, A Change of Measure and Forecast Optimality Conditions, Andrew J. Patton and Allan Timmerman15. Trade by Trade, Financial Transaction Price Dynamics and Limit Order Placement, Jeffrey Russell16. Modelling Autoregressive Conditional Skewness and Kurtosis with Multi-Quantile CAViaR, Halbert White, Tae-Hwan Kim and Simone Manganelli