Modeling Stock Volatility with Stochastic ARCH, GARCH and Stochastic Volatility Model

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Publisher :
ISBN 13 :
Total Pages : 96 pages
Book Rating : 4.:/5 (973 download)

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Book Synopsis Modeling Stock Volatility with Stochastic ARCH, GARCH and Stochastic Volatility Model by : Chang Sun (M.S. in Statistics)

Download or read book Modeling Stock Volatility with Stochastic ARCH, GARCH and Stochastic Volatility Model written by Chang Sun (M.S. in Statistics) and published by . This book was released on 2016 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling volatility within the log stock return is key to the stock price prediction. Despite numerous researches that modeled the volatility with conditional heavy-tailed error distributions, the unconditional distribution remains unknown. In this report, we use and follow the method introduced by Pitt and Walker (2005) by assigning a Student-t distribution for the marginal density of log return and constructing three models respectively, with similar structures to Autoregressive Conditional Heteroskedasticity (ARCH), Generalized ARCH (GARCH) and Stochastic Volatility model in a Bayesian way. We demonstrate the capability of the three models for stock price prediction with S&P 500 index and show that all our models outperform the standard GARCH model (Bollerslev, 1986).

Modeling Stochastic Volatility with Application to Stock Returns

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Publisher : International Monetary Fund
ISBN 13 : 1451854846
Total Pages : 30 pages
Book Rating : 4.4/5 (518 download)

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Book Synopsis Modeling Stochastic Volatility with Application to Stock Returns by : Mr.Noureddine Krichene

Download or read book Modeling Stochastic Volatility with Application to Stock Returns written by Mr.Noureddine Krichene and published by International Monetary Fund. This book was released on 2003-06-01 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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.

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.

Modelling Stock Market Volatility

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Publisher : Elsevier
ISBN 13 : 0080511872
Total Pages : 505 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Modelling Stock Market Volatility by : Peter H. Rossi

Download or read book Modelling Stock Market Volatility written by Peter H. Rossi and published by Elsevier. This book was released on 1996-11-19 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This essay collection focuses on the relationship between continuous time models and Autoregressive Conditionally Heteroskedastic (ARCH) models and applications. For the first time, Modelling Stock Market Volatility provides new insights about the links between these two models and new work on practical estimation methods for continuous time models. Featuring the pioneering scholarship of Daniel Nelson, the text presents research about the discrete time model, continuous time limits and optimal filtering of ARCH models, and the specification and estimation of continuous time processes. This work will lead to a rapid growth in their empirical application as they are increasingly subjected to routine specification testing. Provides for the first time new insights on the links between continuous time and ARCH models Collects seminal scholarship by some of the most renowned researchers in finance and econometrics Captures complex arguments underlying the approximation and proper statistical modelling of continuous time volatility dynamics

Stochastic Volatility

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Publisher : Oxford University Press, USA
ISBN 13 : 0199257205
Total Pages : 534 pages
Book Rating : 4.1/5 (992 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 Oxford University Press, USA. This book was released on 2005 with total page 534 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 work brings together some of the main papers that have influenced this field, andshows that the development of this subject has been highly multidisciplinary.

Econometric Modelling of Stock Market Intraday Activity

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Publisher : Springer Science & Business Media
ISBN 13 : 147573381X
Total Pages : 192 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Econometric Modelling of Stock Market Intraday Activity by : Luc Bauwens

Download or read book Econometric Modelling of Stock Market Intraday Activity written by Luc Bauwens and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past 25 years, applied econometrics has undergone tremen dous changes, with active developments in fields of research such as time series, labor econometrics, financial econometrics and simulation based methods. Time series analysis has been an active field of research since the seminal work by Box and Jenkins (1976), who introduced a gen eral framework in which time series can be analyzed. In the world of financial econometrics and the application of time series techniques, the ARCH model of Engle (1982) has shifted the focus from the modelling of the process in itself to the modelling of the volatility of the process. In less than 15 years, it has become one of the most successful fields of 1 applied econometric research with hundreds of published papers. As an alternative to the ARCH modelling of the volatility, Taylor (1986) intro duced the stochastic volatility model, whose features are quite similar to the ARCH specification but which involves an unobserved or latent component for the volatility. While being more difficult to estimate than usual GARCH models, stochastic volatility models have found numerous applications in the modelling of volatility and more particularly in the econometric part of option pricing formulas. Although modelling volatil ity is one of the best known examples of applied financial econometrics, other topics (factor models, present value relationships, term structure 2 models) were also successfully tackled.

A Practical Guide to Forecasting Financial Market Volatility

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Publisher : John Wiley & Sons
ISBN 13 : 0470856157
Total Pages : 236 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis A Practical Guide to Forecasting Financial Market Volatility by : Ser-Huang Poon

Download or read book A Practical Guide to Forecasting Financial Market Volatility written by Ser-Huang Poon and published by John Wiley & Sons. This book was released on 2005-08-19 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.

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

Forecasting Volatility in the Financial Markets

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Publisher : Elsevier
ISBN 13 : 0080471420
Total Pages : 428 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Forecasting Volatility in the Financial Markets by : Stephen Satchell

Download or read book Forecasting Volatility in the Financial Markets written by Stephen Satchell and published by Elsevier. This book was released on 2011-02-24 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting Volatility in the Financial Markets, Third Edition assumes that the reader has a firm grounding in the key principles and methods of understanding volatility measurement and builds on that knowledge to detail cutting-edge modelling and forecasting techniques. It provides a survey of ways to measure risk and define the different models of volatility and return. Editors John Knight and Stephen Satchell have brought together an impressive array of contributors who present research from their area of specialization related to volatility forecasting. Readers with an understanding of volatility measures and risk management strategies will benefit from this collection of up-to-date chapters on the latest techniques in forecasting volatility. Chapters new to this third edition:* What good is a volatility model? Engle and Patton* Applications for portfolio variety Dan diBartolomeo* A comparison of the properties of realized variance for the FTSE 100 and FTSE 250 equity indices Rob Cornish* Volatility modeling and forecasting in finance Xiao and Aydemir* An investigation of the relative performance of GARCH models versus simple rules in forecasting volatility Thomas A. Silvey Leading thinkers present newest research on volatility forecasting International authors cover a broad array of subjects related to volatility forecasting Assumes basic knowledge of volatility, financial mathematics, and modelling

Volatility Prediction

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

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Book Synopsis Volatility Prediction by : Harry M. Kat

Download or read book Volatility Prediction written by Harry M. Kat and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Future volatility is a key input for pricing and hedging derivatives and for quantitative investment strategies in general. There are many different approaches. This article investigates whether random walk, GARCH (1,1), EGARCH (1,1) and stochastic volatility models of return volatility behavior differ in their ability to predict the volatility of stock index and currency returns over horizons ranging from 2 to 100 trading days. We use close-to-close return data for 7 indices and 5 currencies over the period 1980-1992. The results show that the forecast performance of the different models depends on the specific asset class in question. For stock indices the best volatility predictions are generated by the stochastic volatility model. For currencies on the other hand, the best forecasts come from the GARCH (1,1) model.

Sign- and Volatility-switching ARCH Models

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Publisher :
ISBN 13 :
Total Pages : 58 pages
Book Rating : 4.3/5 ( download)

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Book Synopsis Sign- and Volatility-switching ARCH Models by : Fabio Fornari

Download or read book Sign- and Volatility-switching ARCH Models written by Fabio Fornari and published by . This book was released on 1995 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Simple Test for GARCH Against a Stochastic Volatility Model

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

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Book Synopsis A Simple Test for GARCH Against a Stochastic Volatility Model by : Philip Hans Franses

Download or read book A Simple Test for GARCH Against a Stochastic Volatility Model written by Philip Hans Franses and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: GARCH models and Stochastic Volatility (SV) models can both be used to describe unobserved volatility in asset returns. We consider the issue of testing a GARCH model against an SV model. For that purpose, we propose a new and parsimonious GARCH-t model with an additional restricted moving average term, which can capture SV model properties. We discuss model representation, parameter estimation, and our simple test for model selection. Furthermore, we derive the theoretical moments and the autocorrelation function of our new model. We illustrate our model and test for nine daily stock-return series.

Aggregations and marginalization of GARCH and stochastic volatility models

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (535 download)

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Book Synopsis Aggregations and marginalization of GARCH and stochastic volatility models by : Nour Meddahi

Download or read book Aggregations and marginalization of GARCH and stochastic volatility models written by Nour Meddahi and published by . This book was released on 1998 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Forecasting Volatility in the Financial Markets

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Publisher : Butterworth-Heinemann
ISBN 13 :
Total Pages : 376 pages
Book Rating : 4.:/5 (321 download)

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Book Synopsis Forecasting Volatility in the Financial Markets by : John Knight

Download or read book Forecasting Volatility in the Financial Markets written by John Knight and published by Butterworth-Heinemann. This book was released on 1998 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: An aid to understanding the significance of volatility in the financial market, this text details modelling/forecasting techniques and uses a technical survey to define the models of volatility and return and explain the ways to measure risk. Applications in the financial markets are then detailed.

Multivariate Continuous Time Stochastic Volatility Models Driven by a Lévy Process

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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.

Empirical Studies on Volatility in International Stock Markets

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Publisher : Springer Science & Business Media
ISBN 13 : 147575129X
Total Pages : 168 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Empirical Studies on Volatility in International Stock Markets by : Eugenie M.J.H. Hol

Download or read book Empirical Studies on Volatility in International Stock Markets written by Eugenie M.J.H. Hol and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empirical Studies on Volatility in International Stock Markets describes the existing techniques for the measurement and estimation of volatility in international stock markets with emphasis on the SV model and its empirical application. Eugenie Hol develops various extensions of the SV model, which allow for additional variables in both the mean and the variance equation. In addition, the forecasting performance of SV models is compared not only to that of the well-established GARCH model but also to implied volatility and so-called realised volatility models which are based on intraday volatility measures. The intended readers are financial professionals who seek to obtain more accurate volatility forecasts and wish to gain insight about state-of-the-art volatility modelling techniques and their empirical value, and academic researchers and students who are interested in financial market volatility and want to obtain an updated overview of the various methods available in this area.