Handbook of Financial Time Series - Livro de bolso

EAN (ISBN-13): 9783662518373
ISBN (ISBN-10): 3662518376
Livro de bolso
Ano de publicação: 2016
Editor/Editora: Torben Gustav Andersen

Livro na base de dados desde 2016-08-24T20:04:14-03:00 (Sao Paulo)
Página de detalhes modificada pela última vez em 2024-02-08T14:23:00-03:00 (Sao Paulo)
Número ISBN/EAN: 9783662518373

Número ISBN - Ortografia alternativa:
3-662-51837-6, 978-3-662-51837-3
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: peter anders, jens andersen, richard anders, thomas mikosch, kreiß, richard davis, peter kreis, gustav major, richard thoma, thomas gust, engle robert

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Dados da editora

Autor: Torben Gustav Andersen; Richard A. Davis; Jens-Peter Kreiß; Thomas V. Mikosch
Título: Handbook of Financial Time Series
Editora: Springer; Springer Berlin
1050 Páginas
Ano de publicação: 2016-08-23
Berlin; Heidelberg; DE
Impresso / Feito em
Língua: Inglês
406,59 € (DE)
417,99 € (AT)
448,50 CHF (CH)
POD
XXIX, 1050 p.

BC; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Wirtschaft; Econometrics; Finance; Financial Time Series; Markov Chain; Simulation; Statistics; Stochastic Differential Equations; Time Series; calculus; modeling; nonparametric methods; quantitative finance; Statistics in Business, Management, Economics, Finance, Insurance; Econometrics; Mathematics in Business, Economics and Finance; Statistics and Computing; Wirtschaftswissenschaft, Finanzen, Betriebswirtschaft und Management; Ökonometrie und Wirtschaftsstatistik; Angewandte Mathematik; Mathematische und statistische Software; BB

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.
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