Parameter Estimation For A Stochastic Volatility Model With Coupled Additive And Multiplicative Noise PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Parameter Estimation For A Stochastic Volatility Model With Coupled Additive And Multiplicative Noise PDF full book. Access full book title Parameter Estimation For A Stochastic Volatility Model With Coupled Additive And Multiplicative Noise.
Author | : Ibukun O.O. Amusan |
Publisher | : |
Total Pages | : 0 |
Release | : 2013 |
Genre | : |
ISBN | : |
Download Parameter estimation for a stochastic volatility model with coupled additive and multiplicative noise Book in PDF, ePub and Kindle
Author | : Jaya P. N. Bishwal |
Publisher | : Springer Nature |
Total Pages | : 634 |
Release | : 2022-08-06 |
Genre | : Mathematics |
ISBN | : 3031038614 |
Download Parameter Estimation in Stochastic Volatility Models Book in PDF, ePub and Kindle
This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.
Author | : Mr.Noureddine Krichene |
Publisher | : International Monetary Fund |
Total Pages | : 30 |
Release | : 2003-06-01 |
Genre | : Business & Economics |
ISBN | : 1451854846 |
Download Modeling Stochastic Volatility with Application to Stock Returns Book in PDF, ePub and Kindle
A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities. Volatility persistence being close to one was consistent with both volatility clustering and mean reversion. Filtering showed highly volatile markets, reflecting frequent pertinent news. Diagnostics showed no model failure, although specification improvements were always possible. The model corroborated stylized findings in volatility modeling and has potential value for market participants in asset pricing and risk management, as well as for policymakers in the design of macroeconomic policies conducive to less volatile financial markets.
Author | : Makoto Takahashi |
Publisher | : Springer Nature |
Total Pages | : 120 |
Release | : 2023-04-18 |
Genre | : Business & Economics |
ISBN | : 981990935X |
Download Stochastic Volatility and Realized Stochastic Volatility Models Book in PDF, ePub and Kindle
This treatise delves into the latest advancements in stochastic volatility models, highlighting the utilization of Markov chain Monte Carlo simulations for estimating model parameters and forecasting the volatility and quantiles of financial asset returns. The modeling of financial time series volatility constitutes a crucial aspect of finance, as it plays a vital role in predicting return distributions and managing risks. Among the various econometric models available, the stochastic volatility model has been a popular choice, particularly in comparison to other models, such as GARCH models, as it has demonstrated superior performance in previous empirical studies in terms of fit, forecasting volatility, and evaluating tail risk measures such as Value-at-Risk and Expected Shortfall. The book also explores an extension of the basic stochastic volatility model, incorporating a skewed return error distribution and a realized volatility measurement equation. The concept of realized volatility, a newly established estimator of volatility using intraday returns data, is introduced, and a comprehensive description of the resulting realized stochastic volatility model is provided. The text contains a thorough explanation of several efficient sampling algorithms for latent log volatilities, as well as an illustration of parameter estimation and volatility prediction through empirical studies utilizing various asset return data, including the yen/US dollar exchange rate, the Dow Jones Industrial Average, and the Nikkei 225 stock index. This publication is highly recommended for readers with an interest in the latest developments in stochastic volatility models and realized stochastic volatility models, particularly in regards to financial risk management.
Author | : Jean-Pierre Fouque |
Publisher | : Cambridge University Press |
Total Pages | : 222 |
Release | : 2000-07-03 |
Genre | : Business & Economics |
ISBN | : 9780521791632 |
Download Derivatives in Financial Markets with Stochastic Volatility Book in PDF, ePub and Kindle
This book, first published in 2000, addresses pricing and hedging derivative securities in uncertain and changing market volatility.
Author | : Jaya P. N. Bishwal |
Publisher | : Springer |
Total Pages | : 268 |
Release | : 2007-09-26 |
Genre | : Mathematics |
ISBN | : 3540744487 |
Download Parameter Estimation in Stochastic Differential Equations Book in PDF, ePub and Kindle
Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.
Author | : Simo Särkkä |
Publisher | : Cambridge University Press |
Total Pages | : 327 |
Release | : 2019-05-02 |
Genre | : Business & Economics |
ISBN | : 1316510085 |
Download Applied Stochastic Differential Equations Book in PDF, ePub and Kindle
With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.
Author | : |
Publisher | : |
Total Pages | : 948 |
Release | : 1999 |
Genre | : Mathematical statistics |
ISBN | : |
Download Current Index to Statistics, Applications, Methods and Theory Book in PDF, ePub and Kindle
The Current Index to Statistics (CIS) is a bibliographic index of publications in statistics, probability, and related fields.
Author | : Jianqing Fan |
Publisher | : |
Total Pages | : 64 |
Release | : 2003 |
Genre | : Parameter estimation |
ISBN | : |
Download Semiparametric Estimation of Value-at-risk Book in PDF, ePub and Kindle
Author | : Luc Bauwens |
Publisher | : John Wiley & Sons |
Total Pages | : 566 |
Release | : 2012-03-22 |
Genre | : Business & Economics |
ISBN | : 1118272056 |
Download Handbook of Volatility Models and Their Applications Book in PDF, ePub and Kindle
A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.