Inference for Conditionally Heteroscedastic Time Series Models PDF Download
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Author: Harinarayan Dutta
Publisher:
ISBN:
Category :
Languages : en
Pages : 238
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Author: Harinarayan Dutta
Publisher:
ISBN:
Category :
Languages : en
Pages : 238
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Author: Daniel Straumann
Publisher: Springer Science & Business Media
ISBN: 3540269789
Category : Business & Economics
Languages : en
Pages : 239
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Book Description
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatility. Engle showed that this model, which he called ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic). This monograph concentrates on mathematical statistical problems associated with fitting conditionally heteroscedastic time series models to data. This includes the classical statistical issues of consistency and limiting distribution of estimators. Particular attention is addressed to (quasi) maximum likelihood estimation and misspecified models, along to phenomena due to heavy-tailed innovations. The used methods are based on techniques applied to the analysis of stochastic recurrence equations. Proofs and arguments are given wherever possible in full mathematical rigour. Moreover, the theory is illustrated by examples and simulation studies.
Author: Chun-Kit Kwan
Publisher: Open Dissertation Press
ISBN: 9781374672666
Category :
Languages : en
Pages :
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Book Description
This dissertation, "Statistical Inference for Some Financial Time Series Models With Conditional Heteroscedasticity" by Chun-kit, Kwan, 關進傑, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b3979402 Subjects: Finance - Mathematical models Time-series analysis
Author: Yan Liu
Publisher: Springer Nature
ISBN: 9819908035
Category : Mathematics
Languages : en
Pages : 591
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Book Description
This book compiles theoretical developments on statistical inference for time series and related models in honor of Masanobu Taniguchi's 70th birthday. It covers models such as long-range dependence models, nonlinear conditionally heteroscedastic time series, locally stationary processes, integer-valued time series, Lévy Processes, complex-valued time series, categorical time series, exclusive topic models, and copula models. Many cutting-edge methods such as empirical likelihood methods, quantile regression, portmanteau tests, rank-based inference, change-point detection, testing for the goodness-of-fit, higher-order asymptotic expansion, minimum contrast estimation, optimal transportation, and topological methods are proposed, considered, or applied to complex data based on the statistical inference for stochastic processes. The performances of these methods are illustrated by a variety of data analyses. This collection of original papers provides the reader with comprehensive and state-of-the-art theoretical works on time series and related models. It contains deep and profound treatments of the asymptotic theory of statistical inference. In addition, many specialized methodologies based on the asymptotic theory are presented in a simple way for a wide variety of statistical models. This Festschrift finds its core audiences in statistics, signal processing, and econometrics.
Author: Raquel Prado
Publisher: CRC Press
ISBN: 1439882754
Category : Mathematics
Languages : en
Pages : 375
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Book Description
Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian t
Author: Liudas Giraitis
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
In this article, we introduce the general setting of a multivariate time series autoregressive model with stochastic time-varying coefficients and time-varying conditional variance of the error process. This allows modelling VAR dynamics for non-stationary time series and estimation of time-varying parameter processes by the well-known rolling regression estimation techniques. We establish consistency, convergence rates, and asymptotic normality for kernel estimators of the paths of coefficient processes and provide pointwise valid standard errors. The method is applied to a popular seven-variable dataset to analyse evidence of time variation in empirical objects of interest for the DSGE (dynamic stochastic general equilibrium) literature.
Author: Luc Bauwens
Publisher: OUP Oxford
ISBN: 0191588466
Category : Business & Economics
Languages : en
Pages : 370
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Book Description
This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.
Author: 黃香
Publisher:
ISBN: 9781374775435
Category :
Languages : en
Pages :
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Author: Ishwar V. Basawa
Publisher: IMS
ISBN: 9780940600515
Category : Mathematics
Languages : en
Pages : 370
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Book Description
Author: Michael S. Lo
Publisher:
ISBN:
Category : Heteroscedasticity
Languages : en
Pages : 0
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