A Note On The Wang Transform For Stochastic Volatility Pricing Models
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Author | : Alex Badescu |
Publisher | : |
Total Pages | : 14 |
Release | : 2016 |
Genre | : |
ISBN | : |
In this paper we study a conditional version of the Wang transform in the context of discrete GARCH models and their diffusion limits. Our first contribution shows that the conditional Wang transform and Duan's generalized local risk-neutral valuation relationship based on equilibrium considerations, lead to the same GARCH option pricing model. We derive the weak limit of an asymmetric GARCH model risk-neutralized via Wang's transform. The connection with stochastic volatility limits constructed using other standard pricing kernels, such as the conditional Esscher transform or the extended Girsanov principle, is further investigated by comparing the corresponding market prices of variance risk.
Author | : René Garcia |
Publisher | : |
Total Pages | : |
Release | : 1997 |
Genre | : |
ISBN | : |
Author | : Antoine Petrus Cornelius van der Ploeg |
Publisher | : Rozenberg Publishers |
Total Pages | : 358 |
Release | : 2006 |
Genre | : |
ISBN | : 9051705778 |
Author | : Garcia, René |
Publisher | : Montréal : CIRANO |
Total Pages | : 11 |
Release | : 1997 |
Genre | : |
ISBN | : |
Author | : Lishan Shi |
Publisher | : |
Total Pages | : |
Release | : 2006 |
Genre | : |
ISBN | : |
Author | : Mr.Noureddine Krichene |
Publisher | : International Monetary Fund |
Total Pages | : 30 |
Release | : 2003-06-01 |
Genre | : Business & Economics |
ISBN | : 1451854846 |
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 | : Luc Bauwens |
Publisher | : John Wiley & Sons |
Total Pages | : 566 |
Release | : 2012-04-17 |
Genre | : Business & Economics |
ISBN | : 0470872519 |
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.
Author | : Yizhi Zhang |
Publisher | : |
Total Pages | : 114 |
Release | : 2010 |
Genre | : |
ISBN | : |
Author | : Mikhail Chernov |
Publisher | : |
Total Pages | : |
Release | : 2012 |
Genre | : |
ISBN | : |
The paper complements the reviews on the stochastic volatility models and option pricing. We discuss recent advances in modeling and estimation techniques which allow to investigate models with latent factors and non-unique risk-neutral probability measures. The issues related to the optimal data utilization and volatility filtering are highlighted. We also discuss some of the future research in this area.
Author | : Robert A. Meyers |
Publisher | : Springer Science & Business Media |
Total Pages | : 919 |
Release | : 2010-11-03 |
Genre | : Business & Economics |
ISBN | : 1441977007 |
Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.