Volatility and Time Series Econometrics

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.

Introduction ; 1. Measuring Downside Risk- Realized Semivariance ; 2. Modelling UK Inflation Uncertainty, 1958-2006 ; 3. Glossary to ARCH ; 4. A Multifactor Nonlinear, Continuous-time Model of Interest Rate Volatility ; 5. Volatility Regimes and Global Equity Returns ; 6. The Long Run Shift-Share: Modelling the Sources of Metropolitan Sectoral Fluctuations ; 7. Macroeconomic Volatility and Stock Market Volatility, Worldwide ; 8. Estimating the Implied Risk Neutral Density for the U.S. Market Portfolio ; 9. Multivariate Autocontours for Specification Testing in Multivariate GARCH Models ; 10. A History of Econometrics at the University of California, San Diego, A Personal Viewpoint ; 11. Macroeconomics and ARCH ; 12. An Automatic test of Super Exogeneity ; 13. Changes in the Volatility of Residential Investment in the United States ; 14. Generalized Forecast Errors, A Change of Measure and Forecast Optimality Conditions ; 15. Trade by Trade, Financial Transaction Price Dynamics and Limit Order Placement ; 16. Modelling Autoregressive Conditional Skewness and Kurtosis with Multi-Quantile CAViaR