Discriminating Between Garch And Stochastic Volatility Via Nonnested Hypotheses Testing
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Discriminating Between Garch And Stochastic Volatility Via Nonnested Hypotheses Testing
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Author :
language : en
Publisher:
Release Date : 2013
Discriminating Between Garch And Stochastic Volatility Via Nonnested Hypotheses Testing written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Deciding Between Garch And Stochastic Volatility Via Strong Decision Rules
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Author : Arie Preminger
language : en
Publisher:
Release Date : 2006
Deciding Between Garch And Stochastic Volatility Via Strong Decision Rules written by Arie Preminger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Analysis Of Stochastic And Non Stochastic Volatility Models
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Author :
language : en
Publisher:
Release Date : 2004
Analysis Of Stochastic And Non Stochastic Volatility Models written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
Changing in variance or volatility with time can be modeled as deterministic by using autoregressive conditional heteroscedastic (ARCH) type models, or as stochastic by using stochastic volatility (SV) models. This study compares these two kinds of models which are estimated on Turkish / USA exchange rate data. First, a GARCH(1,1) model is fitted to the data by using the package E-views and then a Bayesian estimation procedure is used for estimating an appropriate SV model with the help of Ox code. In order to compare these models, the LR test statistic calculated for non-nested hypotheses is obtained.
Stable Paretian Models In Finance
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Author : Svetlozar T. Rachev
language : en
Publisher:
Release Date : 2000-06-15
Stable Paretian Models In Finance written by Svetlozar T. Rachev and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-06-15 with Business & Economics categories.
The authors reconsider the problem of parametrically specifying distribution suitable for asset-return models. They describe alternative distributions, showing how they can be estimated and applied to stock-index and exchange-rate data. The implications for options pricing are also investigated.
High Frequency Financial Econometrics
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Author : Yacine Aït-Sahalia
language : en
Publisher: Princeton University Press
Release Date : 2014-07-21
High Frequency Financial Econometrics written by Yacine Aït-Sahalia and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-21 with Business & Economics categories.
A comprehensive introduction to the statistical and econometric methods for analyzing high-frequency financial data High-frequency trading is an algorithm-based computerized trading practice that allows firms to trade stocks in milliseconds. Over the last fifteen years, the use of statistical and econometric methods for analyzing high-frequency financial data has grown exponentially. This growth has been driven by the increasing availability of such data, the technological advancements that make high-frequency trading strategies possible, and the need of practitioners to analyze these data. This comprehensive book introduces readers to these emerging methods and tools of analysis. Yacine Aït-Sahalia and Jean Jacod cover the mathematical foundations of stochastic processes, describe the primary characteristics of high-frequency financial data, and present the asymptotic concepts that their analysis relies on. Aït-Sahalia and Jacod also deal with estimation of the volatility portion of the model, including methods that are robust to market microstructure noise, and address estimation and testing questions involving the jump part of the model. As they demonstrate, the practical importance and relevance of jumps in financial data are universally recognized, but only recently have econometric methods become available to rigorously analyze jump processes. Aït-Sahalia and Jacod approach high-frequency econometrics with a distinct focus on the financial side of matters while maintaining technical rigor, which makes this book invaluable to researchers and practitioners alike.
Forecasting Financial Time Series Using Model Averaging
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Author : Francesco Ravazzolo
language : en
Publisher: Rozenberg Publishers
Release Date : 2007
Forecasting Financial Time Series Using Model Averaging written by Francesco Ravazzolo and has been published by Rozenberg Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Believing in a single model may be dangerous, and addressing model uncertainty by averaging different models in making forecasts may be very beneficial. In this thesis we focus on forecasting financial time series using model averaging schemes as a way to produce optimal forecasts. We derive and discuss in simulation exercises and empirical applications model averaging techniques that can reproduce stylized facts of financial time series, such as low predictability and time-varying patterns. We emphasize that model averaging is not a "magic" methodology which solves a priori problems of poorly forecasting. Averaging techniques have an essential requirement: individual models have to fit data. In the first section we provide a general outline of the thesis and its contributions to previ ous research. In Chapter 2 we focus on the use of time varying model weight combinations. In Chapter 3, we extend the analysis in the previous chapter to a new Bayesian averaging scheme that models structural instability carefully. In Chapter 4 we focus on forecasting the term structure of U.S. interest rates. In Chapter 5 we attempt to shed more light on forecasting performance of stochastic day-ahead price models. We examine six stochastic price models to forecast day-ahead prices of the two most active power exchanges in the world: the Nordic Power Exchange and the Amsterdam Power Exchange. Three of these forecasting models include weather forecasts. To sum up, the research finds an increase of forecasting power of financial time series when parameter uncertainty, model uncertainty and optimal decision making are included.
Analysis Of Financial Time Series
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Author : Ruey S. Tsay
language : en
Publisher: Wiley-Interscience
Release Date : 2001-11-01
Analysis Of Financial Time Series written by Ruey S. Tsay and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-11-01 with Business & Economics categories.
Fundamental topics and new methods in time series analysis Analysis of Financial Time Series provides a comprehensive and systematic introduction to financial econometric models and their application to modeling and prediction of financial time series data. It utilizes real-world examples and real financial data throughout the book to apply the models and methods described. The author begins with basic characteristics of financial time series data before covering three main topics: analysis and application of univariate financial time series; the return series of multiple assets; and Bayesian inference in finance methods. Timely topics and recent results include: Value at Risk (VaR) High-frequency financial data analysis Markov Chain Monte Carlo (MCMC) methods Derivative pricing using jump diffusion with closed-form formulas VaR calculation using extreme value theory based on a non-homogeneous two-dimensional Poisson process Multivariate volatility models with time-varying correlations Ideal as a fundamental introduction to time series for MBA students or as a reference for researchers and practitioners in business and finance, Analysis of Financial Time Series offers an in-depth and up-to-date account of these vital methods.
Regression And Time Series Model Selection
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Author : Allan D. R. McQuarrie
language : en
Publisher: World Scientific
Release Date : 1998
Regression And Time Series Model Selection written by Allan D. R. McQuarrie and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Mathematics categories.
This important book describes procedures for selecting a model from a large set of competing statistical models. It includes model selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are discussed, and small sample and asymptotic properties are presented. The book also provides examples and large scale simulation studies comparing the performances of information-based model selection criteria, bootstrapping, and cross-validation selection methods over a wide range of models.
Unit Roots Cointegration And Structural Change
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Author : G. S. Maddala
language : en
Publisher: Cambridge University Press
Release Date : 1998
Unit Roots Cointegration And Structural Change written by G. S. Maddala and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Business & Economics categories.
A comprehensive review of unit roots, cointegration and structural change from a best-selling author.
Volatility
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Author : Robert A. Jarrow
language : en
Publisher:
Release Date : 1998
Volatility written by Robert A. Jarrow and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Derivative securities categories.
Written by a number of authors, this text is aimed at market practitioners and applies the latest stochastic volatility research findings to the analysis of stock prices. It includes commentary and analysis based on real-life situations.