Handbook of Volatility Models and Their Applications

Name: Handbook of Volatility Models and Their Applications
Price: 164.11 USD
Availability: InStock
ISBN: 9780470872512

ISBN-10: 0470872519

ISBN-13: 9780470872512

Edition: 2012

Authors: Luc Bauwens, Christian M. Hafner, Sebastien Laurent

List price: $318.95

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Description:

The main purpose of this handbook is to illustrate the mathematically fundamental implementation of various volatility models in the banking and financial industries, both at home and abroad, through use of real-world, time-sensitive applications. Conceived and written by over two-dozen experts in the field, the focus is to cohesively demonstrate how "volatile" certain statistical decision-making techniques can be when solving a range of financial problems. By using examples derived from consulting projects, current research and course instruction, each chapter in the book offers a systematic understanding of the recent advances in volatility modeling related to real-world situations. Every…

Book details

List price: $318.95
Copyright year: 2012
Publisher: John Wiley & Sons, Limited
Publication date: 3/30/2012
Binding: Hardcover
Pages: 576
Size: 6.40" wide x 9.60" long x 1.35" tall
Weight: 2.024
Language: English

Luc Bauwens is Professor of Economics at the UniversitÃ© catholique de Louvain, Belgium where he chairs the Department of Economics, and has been co-director of the Center for Operations Research and Econometrics (CORE) from 1992 to 1998. He has published several books and papers in the fields of Bayesian inference, time series methods, simulation and numerical methods in econometrics, as well as empirical finance and international trade.Pierre Giot is Professor of Econometrics and Quantitative Finance at Maastricht University in The Netherlands, and he is a member of CORE in Belgium. After graduating as a Civil Engineer (Polytechnique) in Electronics, he got his Ph.D. in Economics at the…




Volatility Models



Introduction



GARCH



Stochastic Volatility



Realized Volatility



ARCH and SV



Nonlinear ARCH Models



Introduction



Standard GARCH model



Predecessors to Nonlinear GARCH



Nonlinear ARCH and GARCH



Testing



Estimation



Forecasting



Multiplicative Decomposition



Conclusion



Mixture and Regime-switching GARCH Models



Introduction



Regime-switching GARCH models



Stationarity and Moment Structure



Regime Inference, Likelihood Functions, and Volatility Forecasting



Application of Mixture GARCH Models



Conclusion



Forecasting High Dimensional Covariance Matrices



Introduction



Notation



Rolling-Window Forecasts



Dynamic Models



High-Frequency Based Forecasts



Forecast Evaluation



Conclusion



Mean, Volatility and Skewness Spillovers in Equity Markets



Introduction



Data and Summary Statistics



Empirical Results



Conclusion



Relating Stochastic Volatility Estimation Methods



Introduction



Theory and Methodology



Comparison of Methods



Estimating Volatility Models in Practice



Conclusion



Multivariate Stochastic Volatility Models



Introduction



MSV model



Factor MSV model



Applications to Stock Indices Returns



Conclusion



Model Selection and Testing of Volatility Models



Introduction



Model Selection and Testing



Empirical Example



Conclusion



Other models and methods



Multiplicative Error Models



Introduction



Theory and Methodology



MEM Application



MEM Extensions



Conclusion



Locally Stationary Volatility Modeling



Introduction



Empirical evidences



Locally Stationary Processes



Locally Stationary Volatility Models



Multivariate Models for Locally Stationary Volatility



Conclusion



Nonparametric and Semiparametric Volatility Models



Introduction



Nonparametric and Semiparametric Univariate Models



Nonparametric and Semiparametric Multivariate Volatility Models



Empirical Analysis



Conclusion



Copula-based Volatility Models



Introduction



Definition and Properties of Copulas



Estimation



Dynamic Copulas



Value-at-Risk



Multivariate Static copulas



Conclusion



Realized Volatility



Realized Volatility: Theory and Applications



Introduction



Modelling Framework



Issues in Handling Intra-day Transaction Databases



Realized Variance and Covariance



Modelling and Forecasting



Asset Pricing



Estimating Continuous Time Models



Likelihood-Based Volatility Estimators



Introduction



Volatility Estimation



Covariance Estimation



Empirical Application



Conclusion



HAR Modeling for Realized Volatility Forecasting



Introduction



Stylized Facts



Heterogeneity and Volatility Persistence



HAR Extensions



Multivariate Models



Applications



Conclusion



Forecasting volatility with MIDAS



Introduction



MIDAS Regression Models and Volatility Forecasting



Likelihood-based Methods



Multivariate Models



Conclusion



Jumps



Introduction



Estimators of Integrated Variance and Integrated Covariance



Testing for the Presence of Jumps



Conclusion



Jumps, Periodicity and Microstructure Noise



Introduction



Model



Price Jump Detection Method



Simulation Study



Comparison on NYSE-Stock Prices



Conclusion



Volatility Forecasts Evaluation and Comparison



Introduction



Notation



Single Forecast Evaluation



Loss Functions and the Latent Variable Problem



Pairwise Comparison



Multiple Comparison



Consistency of the Ordering and Inference on Forecast Performances



Conclusion


Index


Bibliography