Handbook of Financial Time Series

The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.

The Handbook of Financial Time Series provides an up-to-date overview of the field and covers all relevant topics, both from a statistical and an econometrical point of view. Experts present, among others various aspects, the important GARCH and Stochastic Volatility classes, like for example distribution properties, estimation, forecasting and extreme value theory. The book also details processes in continuous time and cointegration since both play a very essential role in financial modeling. In addition, recent developments in nonparametric methods, copulas, structural breaks, high frequency data and many more topics are included in the handbook. Many outstanding authors have contributed to this encyclopedia, making the volume an excellent source of reference for scientists and researchers working in the field of financial time series.

Editors very well known in their area of research Many outstanding contributors Preamble by Nobel prize winner Robert F. Engle Includes supplementary material: sn.pub/extras

Texte du rabat

This handbook presents a collection of survey articles from a statistical as well as an econometric point of view on the broad and still rapidly developing field of financial time series. It includes most of the relevant topics in the field, from fundamental probabilistic properties of financial time series models to estimation, forecasting, model fitting, extreme value behavior and multivariate modeling for a wide range of GARCH, stochastic volatility, and continuous-time models. The latter are especially important for modeling high frequency and irregularly observed financial time series and provide the foundation for estimating realized volatility. Cointegration and unit roots, which are extremely important concepts for understanding and modeling nonstationary time series, and several further relevant topics in the field of financial time series (i.e. nonparametric methods, copulas, structural breaks, high frequency data, resampling and bootstrap methods, and model selection for financial time series among others) are included in detail. All contributions are clearly written and provide, in a pedagogical manner, a broad and detailed overview of the major topics within financial time series.

Contenu
Recent Developments in GARCH Modeling.- An Introduction to Univariate GARCH Models.- Stationarity, Mixing, Distributional Properties and Moments of GARCH(p, q)#x2013;Processes.- ARCH(#x221E;) Models and Long Memory Properties.- A Tour in the Asymptotic Theory of GARCH Estimation.- Practical Issues in the Analysis of Univariate GARCH Models.- Semiparametric and Nonparametric ARCH Modeling.- Varying Coefficient GARCH Models.- Extreme Value Theory for GARCH Processes.- Multivariate GARCH Models.- Recent Developments in Stochastic Volatility Modeling.- Stochastic Volatility: Origins and Overview.- Probabilistic Properties of Stochastic Volatility Models.- Moment#x2013;Based Estimation of Stochastic Volatility Models.- Parameter Estimation and Practical Aspects of Modeling Stochastic Volatility.- Stochastic Volatility Models with Long Memory.- Extremes of Stochastic Volatility Models.- Multivariate Stochastic Volatility.- Topics in Continuous Time Processes.- An Overview of AssetPrice Models.- OrnsteinUhlenbeck Processes and Extensions.- JumpType Lévy Processes.- LévyDriven ContinuousTime ARMA Processes.- Continuous Time Approximations to GARCH and Stochastic Volatility Models.- Maximum Likelihood and Gaussian Estimation of Continuous Time Models in Finance.- Parametric Inference for Discretely Sampled Stochastic Differential Equations.- Realized Volatility.- Estimating Volatility in the Presence of Market Microstructure Noise: A Review of the Theory and Practical Considerations.- Option Pricing.- An Overview of Interest Rate Theory.- Extremes of ContinuousTime Processes..- Topics in Cointegration and Unit Roots.- Cointegration: Overview and Development.- Time Series with Roots on or Near the Unit Circle.- Fractional Cointegration.- Special Topics Risk.- Different Kinds of Risk.- ValueatRisk Models.- CopulaBased Models for Financial Time Series.- Credit Risk Modeling.- Special Topics Time Series Methods.- Evaluating Volatility and Correlation Forecasts.- Structural Breaks in Financial Time Series.- An Introduction to Regime Switching Time Series Models.- Model Selection.- Nonparametric Modeling in Financial Time Series.- Modelling Financial High Frequency Data Using Point Processes.- Special Topics Simulation Based Methods.- Resampling and Subsampling for Financial Time Series.- Markov Chain Monte Carlo.- Particle Filtering.