- Provides for the first time new insights on the links between continuous time and ARCH models
- Collects seminal scholarship by some of the most renowned researchers in finance and econometrics
- Captures complex arguments underlying the approximation and proper statistical modelling of continuous time volatility dynamics
Continuous Time Limits And Optimal Filtering For ARCH Models:D.B. Nelson, ARCH Models as Diffusion Approximations.D.B. Nelson, Filtering and Forecasting with Misspecified ARCH Models I: Getting the Right Variance with the Wrong Model.D.B. Nelson and D.P. Foster, Filtering and Forecasting with Misspecified ARCH Models II: Making the Right Forecast with the Wrong Model.D.B. Nelson and D.P. Foster, Asymptotic Filtering Theory for Univariate ARCH Models.D.B. Nelson, Asymptotic Filtering Theory for Multivariate ARCH Models.D.B. Nelson and D.B. Nelson, Continuous Record Asymptotics for Rolling Sample Variance Estimators.
Specification and Estimation of Continuous Time Processes:R.F. Engle and G.G.J. Lee, Estimating Diffusion Models of Stochastic Volatility.A.R. Gallant and G. Tauchen, Specification Analysis of Continuous Time Models in Finance.L.P. Hansen and J.A. Scheinkman, Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes.Y.Ait-Sahalia, Nonparametric Pricing of Interest Rate Derivative Securities.
Professor of Econometrics, Marketing, and Statistics at the University of Chicago's Graduate School of Business, Peter Rossi has made significant contributions to the fields of finance, microeconomics, and econometrics. Dr. Rossi held the Kellogg Research Chair at Northwestern University, was the IBM Scholar in the Graduate School of Business at Chicago, and has won a number of awards for his work.