Financial econometrics : from basics to advanced modeling techniques created by Svetlozar T Rachev, Stefan Mittnik, Frank J Fabozzi, Sergio M Focardi, Teo Jašić;

Includes index

Chapter 1 - Financial econometrics: scope and methods 2 - Review of probability and statistics. concepts of probability, 3 - Regression analysis: theory and estimation, 4 - Selected topics in regression analysis, 5 - Regression applications in finance, 6 - Modeling univariate time series, 7 - Approaches to ARIMA modeling and forecasting, 8 - Autoregressive conditional heteroskedastic Models, 9 - Vector autoregressive models, 10 - Vector autoregressive models, 11 - Cointegration and state space models, 12 - Robust estimation, 13 - Principal components analysis and factor analysis, 14 - Heavy-Tailed and Stable Distributions in Financial Econometrics, 15 - ARMA and ARCH Models with Infinite-Variance Innovations.

Financial econometrics is a quest for models that describe financial time series such as prices, returns, interest rates, and exchange rates. In Financial Econometrics, readers will be introduced to this growing discipline and the concepts and theories associated with it, including background material on probability theory and statistics. The experienced author team uses real-world data where possible and brings in the results of published research provided by investment banking firms and journals. Financial Econometrics clearly explains the techniques presented and provides illustrative examples for the topics discussed.