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Handbook of Financial Time Series / edited by Torben Gustav Andersen, Richard A. Davis, Jens-Peter Kreiß, Thomas V. Mikosch
版 | 1st ed. 2009. |
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出版者 | Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer |
出版年 | 2009 |
本文言語 | 英語 |
大きさ | XXIX, 1050 p : online resource |
著者標目 | Andersen, Torben Gustav editor Davis, Richard A editor Kreiß, Jens-Peter editor Mikosch, Thomas V editor SpringerLink (Online service) |
件 名 | LCSH:Statistics LCSH:Econometrics LCSH:Social sciences -- Mathematics 全ての件名で検索 LCSH:Mathematical statistics -- Data processing 全ての件名で検索 FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Econometrics FREE:Mathematics in Business, Economics and Finance FREE:Statistics and Computing |
一般注記 | 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 Asset–Price Models -- Ornstein–Uhlenbeck Processes and Extensions -- Jump–Type Lévy Processes -- Lévy–Driven Continuous–Time 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 Continuous–Time 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 -- Value–at–Risk Models -- Copula–Based 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 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 HTTP:URL=https://doi.org/10.1007/978-3-540-71297-8 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9783540712978 |
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EB00238846 |
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