Simulation Based Estimation of Stochastic Volatility Type Models

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis Simulation Based Estimation of Stochastic Volatility Type Models by : Christian Mücher

Download or read book Simulation Based Estimation of Stochastic Volatility Type Models written by Christian Mücher and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Simulation-based Estimation of Time Series and Stochastic Volatility Processes

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ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (111 download)

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Book Synopsis Simulation-based Estimation of Time Series and Stochastic Volatility Processes by : Thiago Do Rêgo Sousa

Download or read book Simulation-based Estimation of Time Series and Stochastic Volatility Processes written by Thiago Do Rêgo Sousa and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Parameter Estimation in Stochastic Volatility Models

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Publisher : Springer Nature
ISBN 13 : 3031038614
Total Pages : 634 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Parameter Estimation in Stochastic Volatility Models by : Jaya P. N. Bishwal

Download or read book Parameter Estimation in Stochastic Volatility Models written by Jaya P. N. Bishwal and published by Springer Nature. This book was released on 2022-08-06 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Simulation Estimation of a Stochastic Volatility Model

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (642 download)

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Book Synopsis Simulation Estimation of a Stochastic Volatility Model by : Giuseppe Maddaloni

Download or read book Simulation Estimation of a Stochastic Volatility Model written by Giuseppe Maddaloni and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Stochastic Volatility and Realized Stochastic Volatility Models

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Publisher : Springer Nature
ISBN 13 : 981990935X
Total Pages : 120 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Stochastic Volatility and Realized Stochastic Volatility Models by : Makoto Takahashi

Download or read book Stochastic Volatility and Realized Stochastic Volatility Models written by Makoto Takahashi and published by Springer Nature. This book was released on 2023-04-18 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Simulation and Parameter Estimation of Stochastic Volatility Models

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ISBN 13 :
Total Pages : 33 pages
Book Rating : 4.:/5 (938 download)

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Book Synopsis Simulation and Parameter Estimation of Stochastic Volatility Models by :

Download or read book Simulation and Parameter Estimation of Stochastic Volatility Models written by and published by . This book was released on 2006 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Volatility Models and Their Applications

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Publisher : John Wiley & Sons
ISBN 13 : 1118272056
Total Pages : 566 pages
Book Rating : 4.1/5 (182 download)

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Book Synopsis Handbook of Volatility Models and Their Applications by : Luc Bauwens

Download or read book Handbook of Volatility Models and Their Applications written by Luc Bauwens and published by John Wiley & Sons. This book was released on 2012-03-22 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modelling and Simulation of Stochastic Volatility in Finance

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Publisher : Universal-Publishers
ISBN 13 : 1581123833
Total Pages : 219 pages
Book Rating : 4.5/5 (811 download)

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Book Synopsis Modelling and Simulation of Stochastic Volatility in Finance by : Christian Kahl

Download or read book Modelling and Simulation of Stochastic Volatility in Finance written by Christian Kahl and published by Universal-Publishers. This book was released on 2008 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: The famous Black-Scholes model was the starting point of a new financial industry and has been a very important pillar of all options trading since. One of its core assumptions is that the volatility of the underlying asset is constant. It was realised early that one has to specify a dynamic on the volatility itself to get closer to market behaviour. There are mainly two aspects making this fact apparent. Considering historical evolution of volatility by analysing time series data one observes erratic behaviour over time. Secondly, backing out implied volatility from daily traded plain vanilla options, the volatility changes with strike. The most common realisations of this phenomenon are the implied volatility smile or skew. The natural question arises how to extend the Black-Scholes model appropriately. Within this book the concept of stochastic volatility is analysed and discussed with special regard to the numerical problems occurring either in calibrating the model to the market implied volatility surface or in the numerical simulation of the two-dimensional system of stochastic differential equations required to price non-vanilla financial derivatives. We introduce a new stochastic volatility model, the so-called Hyp-Hyp model, and use Watanabe's calculus to find an analytical approximation to the model implied volatility. Further, the class of affine diffusion models, such as Heston, is analysed in view of using the characteristic function and Fourier inversion techniques to value European derivatives.

Maximum Likelihood Estimation of Stochastic Volatility Models

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Publisher :
ISBN 13 :
Total Pages : 44 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Maximum Likelihood Estimation of Stochastic Volatility Models by : Yacine Ait-Sahalia

Download or read book Maximum Likelihood Estimation of Stochastic Volatility Models written by Yacine Ait-Sahalia and published by . This book was released on 2009 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood procedure, where an option price is inverted into the unobservable volatility state, to an approximate likelihood procedure where the volatility state is replaced by the implied volatility of a short dated at-the-money option. We find that the approximation results in a negligible loss of accuracy. We apply this method to market prices of index options for several stochastic volatility models, and compare the characteristics of the estimated models. The evidence for a general CEV model, which nests both the affine model of Heston (1993) and a GARCH model, suggests that the elasticity of variance of volatility lies between that assumed by the two nested models.

Complex Systems in Finance and Econometrics

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Publisher : Springer Science & Business Media
ISBN 13 : 1441977007
Total Pages : 919 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Complex Systems in Finance and Econometrics by : Robert A. Meyers

Download or read book Complex Systems in Finance and Econometrics written by Robert A. Meyers and published by Springer Science & Business Media. This book was released on 2010-11-03 with total page 919 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Maximum Likelihood Estimation of Stochastic Volatility Models

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ISBN 13 :
Total Pages : 42 pages
Book Rating : 4.:/5 (249 download)

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Book Synopsis Maximum Likelihood Estimation of Stochastic Volatility Models by : Yacine Aït-Sahalia

Download or read book Maximum Likelihood Estimation of Stochastic Volatility Models written by Yacine Aït-Sahalia and published by . This book was released on 2004 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: We develop and implement a new method for maximum likelihood estimation in closed-form of stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood procedure, where an option price is inverted into the unobservable volatility state, to an approximate likelihood procedure where the volatility state is replaced by the implied volatility of a short dated at-the-money option. We find that the approximation results in a negligible loss of accuracy. We apply this method to market prices of index options for several stochastic volatility models, and compare the characteristics of the estimated models. The evidence for a general CEV model, which nests both the affine model of Heston (1993) and a GARCH model, suggests that the elasticity of variance of volatility lies between that assumed by the two nested models.

Simulation Estimation of a Stochastic Volatility

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (642 download)

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Book Synopsis Simulation Estimation of a Stochastic Volatility by : Giuseppe Maddaloni

Download or read book Simulation Estimation of a Stochastic Volatility written by Giuseppe Maddaloni and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Stochastic Volatility Modeling

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Publisher : CRC Press
ISBN 13 : 1482244071
Total Pages : 520 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Stochastic Volatility Modeling by : Lorenzo Bergomi

Download or read book Stochastic Volatility Modeling written by Lorenzo Bergomi and published by CRC Press. This book was released on 2015-12-16 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising in the modeling of derivatives, including:Which trading issues do we tackle with stochastic volatility? How do we design models and assess their relevance? How do we tell which models are usable and when does c

Asymmetric Stable Stochastic Volatility Models

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ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (141 download)

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Book Synopsis Asymmetric Stable Stochastic Volatility Models by : Francisco Blasques

Download or read book Asymmetric Stable Stochastic Volatility Models written by Francisco Blasques and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper considers a stochastic volatility model featuring an asymmetric stable error distribution and a novel way of accounting for the leverage effect. We adopt simulation-based methods to address key challenges in parameter estimation, the filtering of time-varying volatility, and volatility forecasting. Specifically, we make use of the indirect inference method to estimate the static parameters, and the extremum Monte Carlo method to extract latent volatility. Both methods can be easily adapted to modifications of the model, such as having other distributions for the errors and other dynamic specifications for the volatility process. Illustrations are presented for a simulated dataset and for an empirical application to a time series of Bitcoin returns.

Inferences in Volatility Models

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ISBN 13 :
Total Pages : 220 pages
Book Rating : 4.:/5 (768 download)

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Book Synopsis Inferences in Volatility Models by : Vickneswary Tagore

Download or read book Inferences in Volatility Models written by Vickneswary Tagore and published by . This book was released on 2010 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Efficient Simulation of the Heston Stochastic Volatility Model

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Publisher :
ISBN 13 :
Total Pages : 38 pages
Book Rating : 4.:/5 (129 download)

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Book Synopsis Efficient Simulation of the Heston Stochastic Volatility Model by : Leif B. G. Andersen

Download or read book Efficient Simulation of the Heston Stochastic Volatility Model written by Leif B. G. Andersen and published by . This book was released on 2007 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic volatility models are increasingly important in practical derivatives pricing applications, yet relatively little work has been undertaken in the development of practical Monte Carlo simulation methods for this class of models. This paper considers several new algorithms for time-discretization and Monte Carlo simulation of Heston-type stochastic volatility models. The algorithms are based on a careful analysis of the properties of affine stochastic volatility diffusions, and are straightforward and quick to implement and execute. Tests on realistic model parameterizations reveal that the computational efficiency and robustness of the simulation schemes proposed in the paper compare very favorably to existing methods.

A Simple Approach to the Estimation of Continuous Time CEV Stochastic Volatility Models of the Short-term Rate

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Publisher :
ISBN 13 :
Total Pages : 76 pages
Book Rating : 4.X/5 (6 download)

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Book Synopsis A Simple Approach to the Estimation of Continuous Time CEV Stochastic Volatility Models of the Short-term Rate by : Fabio Fornari

Download or read book A Simple Approach to the Estimation of Continuous Time CEV Stochastic Volatility Models of the Short-term Rate written by Fabio Fornari and published by . This book was released on 2001 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: