A Simple Test Of Garch Against A Stochastic Volatility Model
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Author |
: Philip Hans Franses |
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: |
Total Pages |
: |
Release |
: 2010 |
ISBN-10 |
: OCLC:1290808608 |
ISBN-13 |
: |
Rating |
: 4/5 (08 Downloads) |
Synopsis A Simple Test for GARCH Against a Stochastic Volatility Model by : Philip Hans Franses
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.
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: |
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Total Pages |
: 17 |
Release |
: 2005 |
ISBN-10 |
: OCLC:836058548 |
ISBN-13 |
: |
Rating |
: 4/5 (48 Downloads) |
Synopsis A Simple Test of GARCH Against a Stochastic Volatility Model by :
Author |
: Arie Preminger |
Publisher |
: |
Total Pages |
: 28 |
Release |
: 2008 |
ISBN-10 |
: OCLC:1290311687 |
ISBN-13 |
: |
Rating |
: 4/5 (87 Downloads) |
Synopsis Deciding between GARCH and Stochastic Volatility Via Strong Decision Rules by : Arie Preminger
The GARCH and stochastic volatility (SV) models are two competing, well-known and often used models to explain the volatility of financial series. In this paper, we consider a closed form estimator for a stochastic volatility model and derive its asymptotic properties. We confirm our theoretical results by a simulation study. In addition, we propose a set of simple, strongly consistent decision rules to compare the ability of the GARCH and the SV model to fit the characteristic features observed in high frequency financial data such as high kurtosis and slowly decaying autocorrelation function of the squared observations. These rules are based on a number of moment conditions that is allowed to increase with sample size. We show that our selection procedure leads to choosing the best and simple model with probability one as the sample size increases. The finite sample size behaviour of our procedure is analyzed via simulations. Finally, we provide an application to stocks in the Dow Jones industrial average index.
Author |
: Raghu Nandan Sengupta |
Publisher |
: CRC Press |
Total Pages |
: 936 |
Release |
: 2016-11-30 |
ISBN-10 |
: 9781351727402 |
ISBN-13 |
: 1351727400 |
Rating |
: 4/5 (02 Downloads) |
Synopsis Decision Sciences by : Raghu Nandan Sengupta
This handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.
Author |
: Luc Bauwens |
Publisher |
: John Wiley & Sons |
Total Pages |
: 566 |
Release |
: 2012-04-17 |
ISBN-10 |
: 9780470872512 |
ISBN-13 |
: 0470872519 |
Rating |
: 4/5 (12 Downloads) |
Synopsis Handbook of Volatility Models and Their Applications by : Luc Bauwens
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.
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: |
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: |
Total Pages |
: 24 |
Release |
: 2013 |
ISBN-10 |
: OCLC:931479223 |
ISBN-13 |
: |
Rating |
: 4/5 (23 Downloads) |
Synopsis Discriminating Between GARCH and Stochastic Volatility Via Nonnested Hypotheses Testing by :
Author |
: Robert A. Meyers |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 919 |
Release |
: 2010-11-03 |
ISBN-10 |
: 9781441977007 |
ISBN-13 |
: 1441977007 |
Rating |
: 4/5 (07 Downloads) |
Synopsis Complex Systems in Finance and Econometrics by : Robert A. Meyers
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.
Author |
: Torben Gustav Andersen |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 1045 |
Release |
: 2009-04-21 |
ISBN-10 |
: 9783540712978 |
ISBN-13 |
: 3540712976 |
Rating |
: 4/5 (78 Downloads) |
Synopsis Handbook of Financial Time Series by : Torben Gustav Andersen
The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
Author |
: 李相烈 |
Publisher |
: |
Total Pages |
: 118 |
Release |
: 2013 |
ISBN-10 |
: OCLC:881611612 |
ISBN-13 |
: |
Rating |
: 4/5 (12 Downloads) |
Synopsis Goodness-of-fit Test for Continuous Time Stochastic Volatility Models by : 李相烈
Author |
: Marcus Anthony Cuda |
Publisher |
: |
Total Pages |
: 84 |
Release |
: 1997 |
ISBN-10 |
: UCAL:X56952 |
ISBN-13 |
: |
Rating |
: 4/5 (52 Downloads) |
Synopsis Forecasting Stochastic Volatility Using Kim, Shephard, and Chib's Mixture Simulator by : Marcus Anthony Cuda