Multivariate Stochastic Volatility Via Wishart Random Processes

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Multivariate Stochastic Volatility Via Wishart Random Processes

Author : Alexander Philipov
Publisher :
ISBN 13 :
Total Pages : 57 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Multivariate Stochastic Volatility Via Wishart Random Processes by : Alexander Philipov

Download or read book Multivariate Stochastic Volatility Via Wishart Random Processes written by Alexander Philipov and published by . This book was released on 2004 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial models for asset and derivatives pricing, risk management, portfolio optimization, and asset allocation rely on volatility forecasts. Time-varying volatility models, such as GARCH and Stochastic Volatility (SVOL), have been successful in improving forecasts over constant volatility models. We develop a new multivariate SVOL framework for modeling financial data that assumes covariance matrices stochastically varying through a Wishart process. In our formulation, scalar variances naturally extend to covariance matrices rather than vectors of variances as in traditional SVOL models. Model fitting is performed using Markov chain Monte Carlo simulation from the posterior distribution. Due to the complexity of the model, an efficiently designed Gibbs sampler is described that produces inferences with a manageable amount of computation. Our approach is illustrated on a multivariate time series of monthly industry portfolio returns. In a test of the economic value of our model, minimum-variance portfolios based on our SVOL covariance forecasts outperform out-of-sample portfolios based on alternative covariance models such as Dynamic Conditional Correlations and factor-based covariances.

Multivariate stochastic volatility via Wishart processes : a continuation

Author : Wolfgang Rinnergschwentner
Publisher :
ISBN 13 :
Total Pages : 36 pages
Book Rating : 4.:/5 (78 download)

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Book Synopsis Multivariate stochastic volatility via Wishart processes : a continuation by : Wolfgang Rinnergschwentner

Download or read book Multivariate stochastic volatility via Wishart processes : a continuation written by Wolfgang Rinnergschwentner and published by . This book was released on 2011 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Essays on Multivariate Stochastic Volatility Models Using Wishart Processes

Author : Yu-Cheng Ku
Publisher :
ISBN 13 :
Total Pages : 87 pages
Book Rating : 4.:/5 (69 download)

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Book Synopsis Essays on Multivariate Stochastic Volatility Models Using Wishart Processes by : Yu-Cheng Ku

Download or read book Essays on Multivariate Stochastic Volatility Models Using Wishart Processes written by Yu-Cheng Ku and published by . This book was released on 2010 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Matrix-State Particle Filter for Wishart Stochastic Volatility Processes

Author : Roberto Casarin
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Matrix-State Particle Filter for Wishart Stochastic Volatility Processes by : Roberto Casarin

Download or read book Matrix-State Particle Filter for Wishart Stochastic Volatility Processes written by Roberto Casarin and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work deals with multivariate stochastic volatility models, which account for a time-varying variance-covariance structure of the observable variables. We focus on a special class of models recently proposed in the literature and assume that the covariance matrix is a latent variable which follows an autoregressive Wishart process. We review two alternative stochastic representations of the Wishart process and propose Markov-Switching Wishart processes to capture different regimes in the volatility level. We apply a full Bayesian inference approach, which relies upon Sequential Monte Carlo (SMC) for matrix-valued distributions and allows us to sequentially estimate both the parameters and the latent variables.

Handbook of Financial Time Series

Author : Torben Gustav Andersen
Publisher : Springer Science & Business Media
ISBN 13 : 3540712976
Total Pages : 1045 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Handbook of Financial Time Series by : Torben Gustav Andersen

Download or read book Handbook of Financial Time Series written by Torben Gustav Andersen and published by Springer Science & Business Media. This book was released on 2009-04-21 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Bayesian Inference in the Social Sciences

Author : Ivan Jeliazkov
Publisher : John Wiley & Sons
ISBN 13 : 1118771125
Total Pages : 266 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Bayesian Inference in the Social Sciences by : Ivan Jeliazkov

Download or read book Bayesian Inference in the Social Sciences written by Ivan Jeliazkov and published by John Wiley & Sons. This book was released on 2014-11-04 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents new models, methods, and techniques and considers important real-world applications in political science, sociology, economics, marketing, and finance Emphasizing interdisciplinary coverage, Bayesian Inference in the Social Sciences builds upon the recent growth in Bayesian methodology and examines an array of topics in model formulation, estimation, and applications. The book presents recent and trending developments in a diverse, yet closely integrated, set of research topics within the social sciences and facilitates the transmission of new ideas and methodology across disciplines while maintaining manageability, coherence, and a clear focus. Bayesian Inference in the Social Sciences features innovative methodology and novel applications in addition to new theoretical developments and modeling approaches, including the formulation and analysis of models with partial observability, sample selection, and incomplete data. Additional areas of inquiry include a Bayesian derivation of empirical likelihood and method of moment estimators, and the analysis of treatment effect models with endogeneity. The book emphasizes practical implementation, reviews and extends estimation algorithms, and examines innovative applications in a multitude of fields. Time series techniques and algorithms are discussed for stochastic volatility, dynamic factor, and time-varying parameter models. Additional features include: Real-world applications and case studies that highlight asset pricing under fat-tailed distributions, price indifference modeling and market segmentation, analysis of dynamic networks, ethnic minorities and civil war, school choice effects, and business cycles and macroeconomic performance State-of-the-art computational tools and Markov chain Monte Carlo algorithms with related materials available via the book’s supplemental website Interdisciplinary coverage from well-known international scholars and practitioners Bayesian Inference in the Social Sciences is an ideal reference for researchers in economics, political science, sociology, and business as well as an excellent resource for academic, government, and regulation agencies. The book is also useful for graduate-level courses in applied econometrics, statistics, mathematical modeling and simulation, numerical methods, computational analysis, and the social sciences.

Macroeconomic Forecasting in the Era of Big Data

Author : Peter Fuleky
Publisher : Springer Nature
ISBN 13 : 3030311503
Total Pages : 716 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Macroeconomic Forecasting in the Era of Big Data by : Peter Fuleky

Download or read book Macroeconomic Forecasting in the Era of Big Data written by Peter Fuleky and published by Springer Nature. This book was released on 2019-11-28 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.

Multivariate Wishart Stochastic Volatility Models

Author : Bastian Gribisch
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (837 download)

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Book Synopsis Multivariate Wishart Stochastic Volatility Models by : Bastian Gribisch

Download or read book Multivariate Wishart Stochastic Volatility Models written by Bastian Gribisch and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Multivariate Continuous Time Stochastic Volatility Models Driven by a Lévy Process

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (696 download)

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Book Synopsis Multivariate Continuous Time Stochastic Volatility Models Driven by a Lévy Process by :

Download or read book Multivariate Continuous Time Stochastic Volatility Models Driven by a Lévy Process written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Several multivariate stochastic models in continuous time are introduced and their probabilistic and statistical properties are studied in detail. All models are driven by Lévy processes and can generally be used to model multidimensional time series of observations. In this thesis the focus is on various stochastic volatility models for financial data. Firstly, multidimensional continuous-time autoregressive moving-average (CARMA) processes are considered and, based upon them, a multivariate continuous-time exponential GARCH model (ECOGARCH). Thereafter, positive semi-definite Ornstein-Uhlenbeck type processes are introduced and the behaviour of the square root (and similar transformations) of stochastic processes of finite variation, which take values in the positive semi-definite matrices and can be represented as the sum of an integral with respect to time and another integral with respect to an extended Poisson random measure, is analysed in general. The positive semi-definite Ornstein-Uhlenbeck type processes form the basis for the definition of a multivariate extension of the popular stochastic volatility model of Barndorff-Nielsen and Shephard. After a detailed theoretical study this model is estimated for some observed stock price series. As a further model with stochastic volatility multivariate continuous time GARCH (COGARCH) processes are introduced and their probabilistic and statistical properties are analysed.

Stochastic Volatility

Author : Neil Shephard
Publisher : OUP Oxford
ISBN 13 : 0191531421
Total Pages : 536 pages
Book Rating : 4.1/5 (915 download)

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Book Synopsis Stochastic Volatility by : Neil Shephard

Download or read book Stochastic Volatility written by Neil Shephard and published by OUP Oxford. This book was released on 2005-03-10 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic volatility is the main concept used in the fields of financial economics and mathematical finance to deal with time-varying volatility in financial markets. This book brings together some of the main papers that have influenced the field of the econometrics of stochastic volatility, and shows that the development of this subject has been highly multidisciplinary, with results drawn from financial economics, probability theory, and econometrics, blending to produce methods and models that have aided our understanding of the realistic pricing of options, efficient asset allocation, and accurate risk assessment. A lengthy introduction by the editor connects the papers with the literature.

Multivariate Stochastic Volatility with Co-heteroscedasticity

Author : Joshua Chan
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (118 download)

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Book Synopsis Multivariate Stochastic Volatility with Co-heteroscedasticity by : Joshua Chan

Download or read book Multivariate Stochastic Volatility with Co-heteroscedasticity written by Joshua Chan and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Conceptual Econometrics Using R

Author :
Publisher : Elsevier
ISBN 13 : 0444643125
Total Pages : 330 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Conceptual Econometrics Using R by :

Download or read book Conceptual Econometrics Using R written by and published by Elsevier. This book was released on 2019-08-20 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conceptual Econometrics Using R, Volume 41 provides state-of-the-art information on important topics in econometrics, including quantitative game theory, multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, productivity and financial market jumps and co-jumps, among others. Presents chapters authored by distinguished, honored researchers who have received awards from the Journal of Econometrics or the Econometric Society Includes descriptions and links to resources and free open source R, allowing readers to not only use the tools on their own data, but also jumpstart their understanding of the state-of-the-art

Bayesian Theory and Applications

Author : Paul Damien
Publisher : Oxford University Press
ISBN 13 : 0199695601
Total Pages : 717 pages
Book Rating : 4.1/5 (996 download)

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Book Synopsis Bayesian Theory and Applications by : Paul Damien

Download or read book Bayesian Theory and Applications written by Paul Damien and published by Oxford University Press. This book was released on 2013-01-24 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume guides the reader along a statistical journey that begins with the basic structure of Bayesian theory, and then provides details on most of the past and present advances in this field.

Multivariate Stochastic Volatility Models with Correlated Errors

Author : David X. Chan
Publisher :
ISBN 13 :
Total Pages : 31 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Multivariate Stochastic Volatility Models with Correlated Errors by : David X. Chan

Download or read book Multivariate Stochastic Volatility Models with Correlated Errors written by David X. Chan and published by . This book was released on 2008 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop a Bayesian approach for parsimoniously estimating the correlation structure of the errors in a multivariate stochastic volatility model. Since the number of parameters in the joint correlation matrix of the return and volatility errors is potentially very large, we impose a prior that allows the off-diagonal elements of the inverse of the correlation matrix to be identically zero. The model is estimated using a Markov chain simulation method that samples from the posterior distribution of the volatilities and parameters. We illustrate the approach using both simulated and real examples. In the real examples, the method is applied to equities at three levels of aggregation: returns for firms within the same industry, returns for different industries and returns aggregated at the index level. We find pronounced correlation effects only at the highest level of aggregation.

Handbook of the Economics of Finance SET:Volumes 2A & 2B

Author : George M. Constantinides
Publisher : Newnes
ISBN 13 : 0444594655
Total Pages : 1732 pages
Book Rating : 4.4/5 (445 download)

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Book Synopsis Handbook of the Economics of Finance SET:Volumes 2A & 2B by : George M. Constantinides

Download or read book Handbook of the Economics of Finance SET:Volumes 2A & 2B written by George M. Constantinides and published by Newnes. This book was released on 2013-01-21 with total page 1732 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set of 23 articles authoritatively describes recent scholarship in corporate finance and asset pricing. Volume 1 concentrates on corporate finance, encompassing topics such as financial innovation and securitization, dynamic security design, and family firms. Volume 2 focuses on asset pricing with articles on market liquidity, credit derivatives, and asset pricing theory, among others. Both volumes present scholarship about the 2008 financial crisis in contexts that highlight both continuity and divergence in research. For those who seek insightful perspectives and important details, they demonstrate how corporate finance studies have interpreted recent events and incorporated their lessons. Covers core and newly-developing fields Explains how the 2008 financial crises affected theoretical and empirical research Exposes readers to a wide range of subjects described and analyzed by the best scholars

Bayesian Multivariate Time Series Methods for Empirical Macroeconomics

Author : Gary Koop
Publisher : Now Publishers Inc
ISBN 13 : 160198362X
Total Pages : 104 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Bayesian Multivariate Time Series Methods for Empirical Macroeconomics by : Gary Koop

Download or read book Bayesian Multivariate Time Series Methods for Empirical Macroeconomics written by Gary Koop and published by Now Publishers Inc. This book was released on 2010 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Multivariate Time Series Methods for Empirical Macroeconomics provides a survey of the Bayesian methods used in modern empirical macroeconomics. These models have been developed to address the fact that most questions of interest to empirical macroeconomists involve several variables and must be addressed using multivariate time series methods. Many different multivariate time series models have been used in macroeconomics, but Vector Autoregressive (VAR) models have been among the most popular. Bayesian Multivariate Time Series Methods for Empirical Macroeconomics reviews and extends the Bayesian literature on VARs, TVP-VARs and TVP-FAVARs with a focus on the practitioner. The authors go beyond simply defining each model, but specify how to use them in practice, discuss the advantages and disadvantages of each and offer tips on when and why each model can be used.

Multivariate Stochastic Volatility Models and Large Deviation Principles

Author : Archil Gulisashvili
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Multivariate Stochastic Volatility Models and Large Deviation Principles by : Archil Gulisashvili

Download or read book Multivariate Stochastic Volatility Models and Large Deviation Principles written by Archil Gulisashvili and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We establish a comprehensive sample path large deviation principle (LDP) for log-price processes associated with multivariate time-inhomogeneous stochastic volatility models. Examples of models for which the new LDP holds include Gaussian models, non-Gaussian fractional models, mixed models, models with reflection, and models in which the volatility process is a solution to a Volterra type stochastic integral equation. The sample path and small-noise LDPs for log-price processes are used to obtain large deviation style asymptotic formulas for the distribution function of the first exit time of a log-price process from an open set, multidimensional binary barrier options, call options, Asian options, and the implied volatility. Such formulas capture leading order asymptotics of the above-mentioned important quantities arising in the theory of stochastic volatility models. We also prove a sample path LDP for solutions to Volterra type stochastic integral equations with predictable coefficients depending on auxiliary stochastic processes.