Bugs For A Bayesian Analysis Of Stochastic Volatility Models PDF Download
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Author | : Renate Meyer |
Publisher | : |
Total Pages | : 17 |
Release | : 2013 |
Genre | : |
ISBN | : |
Download Bugs for a Bayesian Analysis of Stochastic Volatility Models Book in PDF, ePub and Kindle
This paper reviews the general Bayesian approach to parameter estimation in stochastic volatility models with posterior computations performed by Gibbs sampling. The main purpose is to illustrate the ease with which the Bayesian stochastic volatility model can now be studied routinely via BUGS (Bayesian Inference Using Gibbs Sampling), a recently developed, user-friendly, and freely available software package. It is an ideal software tool for the exploratory phase of model building as any modifications of a model including changes of priors and sampling error distributions are readily realized with only minor changes of the code. BUGS automates the calculation of the full conditional posterior distributions using a model representation by directed acyclic graphs. It contains an expert system for choosing an efficient sampling method for each full conditional. Furthermore, software for convergence diagnostics and statistical summaries is available for the BUGS output. The BUGS implementation of a stochastic volatility model is illustrated using a time series of daily Pound/Dollar exchange rates.
Author | : Renate Meyer |
Publisher | : |
Total Pages | : 20 |
Release | : 2000 |
Genre | : Bayesian statistical decision theory |
ISBN | : |
Download BUGS for a Bayesian Analysis of Stochastic Volatility Models Book in PDF, ePub and Kindle
Author | : Asma Graja |
Publisher | : |
Total Pages | : |
Release | : 2009 |
Genre | : |
ISBN | : |
Download Bayesian Analysis of Stochastic Volatility Models Book in PDF, ePub and Kindle
Time varying volatility is a characteristic of many financial series. An alternative to the popular ARCH framework is a Stochastic Volatility model which is harder to estimate than the ARCH family. In this paper we estimate and compare two classes of Stochastic Volatility models proposed in financial literature: the Log normal autoregressive model with some extensions and the Heston model. The basic univariate Stochastic Volatility model is extended to allow for the quot;leverage effectquot; via correlation between the volatility and the mean innovations and for fat tails in the mean equation innovation.A Bayesian Markov Chain Monte Carlo algorithm developed in Jacquier, Polson and Rossi 2004 is analyzed and applied to a large data base of the French financial market. Moreover, explicit expression for the parameter's estimators is found via Monte Carlo technique.
Author | : David Lunn |
Publisher | : CRC Press |
Total Pages | : 393 |
Release | : 2012-10-02 |
Genre | : Mathematics |
ISBN | : 1466586664 |
Download The BUGS Book Book in PDF, ePub and Kindle
Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide. Authored by the team that originally developed this software, The BUGS Book provides a practical introduction to this program and its use. The text presents
Author | : Joanne Jia Jia Wang |
Publisher | : |
Total Pages | : 468 |
Release | : 2012 |
Genre | : Bayesian statistical decision theory |
ISBN | : |
Download Bayesian Analysis of Stochastic Volatility Models Book in PDF, ePub and Kindle
Author | : Eric Jacquier |
Publisher | : |
Total Pages | : 41 |
Release | : 1993 |
Genre | : Bayesian statistical decision theory |
ISBN | : |
Download Bayesian Analysis of Stochastic Volatility Models Book in PDF, ePub and Kindle
Author | : C. A. Abanto-Valle |
Publisher | : |
Total Pages | : 42 |
Release | : 2008 |
Genre | : Bayesian statistical decision theory |
ISBN | : |
Download Robust Bayesian Analysis of Heavy-tailed Stochastic Volatility Models Using Scale Mixtures of Normal Distributions Book in PDF, ePub and Kindle
Author | : David Insua |
Publisher | : John Wiley & Sons |
Total Pages | : 315 |
Release | : 2012-04-02 |
Genre | : Mathematics |
ISBN | : 1118304039 |
Download Bayesian Analysis of Stochastic Process Models Book in PDF, ePub and Kindle
Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models. Key features: Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. Provides a thorough introduction for research students. Computational tools to deal with complex problems are illustrated along with real life case studies Looks at inference, prediction and decision making. Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR, stochastic modelling and applied statistics will also find this book useful.
Author | : Pawel J. Szerszen |
Publisher | : |
Total Pages | : |
Release | : 2009 |
Genre | : |
ISBN | : |
Download Bayesian Analysis of Stochastic Volatility Models with Lévy Jumps Book in PDF, ePub and Kindle
Author | : Toshiaki Watanabe |
Publisher | : |
Total Pages | : 64 |
Release | : 2001 |
Genre | : Bayesian statistical decision theory |
ISBN | : |
Download Stochastic Volatility Models with Heavy-tailed Distributions Book in PDF, ePub and Kindle