Handbook of Financial Time Series

Edited by Thomas Mikosch (), Jens-Peter Kreiß (), Richard A. Davis () and Torben Gustav Andersen ()

in Springer Books from Springer

Date: 2009
ISBN: 978-3-540-71297-8
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Citations: View citations in EconPapers (30)

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Chapters in this book:

Ch 1 An Introduction to Univariate GARCH Models

Timo Teräsvirta

Ch 2 Stationarity, Mixing, Distributional Properties and Moments of GARCH(p, q)–Processes

Alexander M. Lindner

Ch 3 ARCH(∞) Models and Long Memory Properties

Liudas Giraitis, Remigijus Leipus and Donatas Surgailis

Ch 4 A Tour in the Asymptotic Theory of GARCH Estimation

Christian Francq and Jean-Michel Zakoïan

Ch 5 Practical Issues in the Analysis of Univariate GARCH Models

Eric Zivot

Ch 6 Semiparametric and Nonparametric ARCH Modeling

Oliver Linton

Ch 7 Varying Coefficient GARCH Models

Pavel Čížek and Vladimir Spokoiny

Ch 8 Extreme Value Theory for GARCH Processes

Richard A. Davis and Thomas Mikosch

Ch 9 Multivariate GARCH Models

Annastiina Silvennoinen and Timo Teräsvirta

Ch 10 Stochastic Volatility: Origins and Overview

Neil Shephard and Torben Andersen

Ch 11 Probabilistic Properties of Stochastic Volatility Models

Richard A. Davis and Thomas Mikosch

Ch 12 Moment–Based Estimation of Stochastic Volatility Models

Eric Renault

Ch 13 Parameter Estimation and Practical Aspects of Modeling Stochastic Volatility

Borus Jungbacker and Siem Jan Koopman

Ch 14 Stochastic Volatility Models with Long Memory

Clifford Hurvich and Philippe Soulier

Ch 15 Extremes of Stochastic Volatility Models

Richard A. Davis and Thomas Mikosch

Ch 16 Multivariate Stochastic Volatility

Siddhartha Chib, Yasuhiro Omori and Manabu Asai

Ch 17 An Overview of Asset–Price Models

Peter J. Brockwell

Ch 18 Ornstein–Uhlenbeck Processes and Extensions

Ross A. Maller, Gernot Müller and Alex Szimayer

Ch 19 Jump–Type Lévy Processes

Ernst Eberlein

Ch 20 Lévy–Driven Continuous–Time ARMA Processes

Peter J. Brockwell

Ch 21 Continuous Time Approximations to GARCH and Stochastic Volatility Models

Alexander M. Lindner

Ch 22 Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance

Peter Phillips and Jun Yu

Ch 23 Parametric Inference for Discretely Sampled Stochastic Differential Equations

Michael Sørensen

Ch 24 Realized Volatility

Torben G. Andersen and Timo Teräsvirta

Ch 25 Estimating Volatility in the Presence of Market Microstructure Noise: A Review of the Theory and Practical Considerations

Yacine Aït-Sahalia and Per A. Mykland

Ch 26 Option Pricing

Jan Kallsen

Ch 27 An Overview of Interest Rate Theory

Tomas Bjork

Ch 28 Extremes of Continuous–Time Processes

Vicky Fasen

Ch 29 Cointegration: Overview and Development

Søren Johansen

Ch 30 Time Series with Roots on or Near the Unit Circle

Ngai Hang Chan

Ch 31 Fractional Cointegration

Willa W. Chen and Clifford Hurvich

Ch 32 Different Kinds of Risk

Paul Embrechts, Hansjörg Furrer and Roger Kaufmann

Ch 33 Value–at–Risk Models

Peter Christoffersen

Ch 34 Copula–Based Models for Financial Time Series

Andrew J. Patton

Ch 35 Credit Risk Modeling

David Lando

Ch 36 Evaluating Volatility and Correlation Forecasts

Andrew J. Patton and Kevin Sheppard

Ch 37 Structural Breaks in Financial Time Series

Elena Andreou and Eric Ghysels

Ch 38 An Introduction to Regime Switching Time Series Models

Theis Lange and Anders Rahbek

Ch 39 Model Selection

Hannes Leeb and Benedikt Pötscher

Ch 40 Nonparametric Modeling in Financial Time Series

Jürgen Franke, Jens-Peter Kreiss and Enno Mammen

Ch 41 Modelling Financial High Frequency Data Using Point Processes

Luc Bauwens and Nikolaus Hautsch

Ch 42 Resampling and Subsampling for Financial Time Series

Efstathios Paparoditis and Dimitris N. Politis

Ch 43 Markov Chain Monte Carlo

Michael Johannes and Nicholas Polson

Ch 44 Particle Filtering

Michael Johannes and Nicholas Polson

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DOI: 10.1007/978-3-540-71297-8

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