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Statistical Surveillance Of Volatility Forecasting Models


Statistical Surveillance Of Volatility Forecasting Models
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Statistical Surveillance Of Volatility Forecasting Models


Statistical Surveillance Of Volatility Forecasting Models
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Author : Vasyl Golosnoy
language : en
Publisher:
Release Date : 2011

Statistical Surveillance Of Volatility Forecasting Models written by Vasyl Golosnoy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.


This paper elaborates sequential procedures for monitoring the validity of a volatility model. A state space representation describes dynamics of daily integrated volatility. The observation equation relates the integrated volatility to its measures such as the realized volatility or bipower variation. On-line control procedures, based on volatility forecasting errors, allow us to decide whether the chosen representation remains correctly specified. A signal indicates that the assumed volatility model may no longer be valid. The performance of our approach is analyzed within a Monte Carlo simulation study and illustrated in an empirical application for selected US stocks.



Financial Surveillance


Financial Surveillance
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Author : Marianne Frisen
language : en
Publisher: John Wiley & Sons
Release Date : 2008-02-28

Financial Surveillance written by Marianne Frisen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-28 with Mathematics categories.


This is the first book-length treatment of statistical surveillance methods used in financial analysis. It contains carefully selected chapters written by specialists from both fields and strikes a balance between the financial and statistical worlds, enhancing future collaborations between the two areas, and enabling more successful prediction of financial market trends. The book discusses, in detail, schemes for different control charts and different linear and nonlinear time series models and applies methods to real data from worldwide markets, as well as including simulation studies.



Online Surveillance Of Volatility Forecasting Models


Online Surveillance Of Volatility Forecasting Models
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Author : Vasyl Golosnoy
language : en
Publisher:
Release Date : 2010

Online Surveillance Of Volatility Forecasting Models written by Vasyl Golosnoy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.




Forecasting High Frequency Volatility Shocks


Forecasting High Frequency Volatility Shocks
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Author : Holger Kömm
language : en
Publisher: Springer
Release Date : 2016-02-08

Forecasting High Frequency Volatility Shocks written by Holger Kömm and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-08 with Business & Economics categories.


This thesis presents a new strategy that unites qualitative and quantitative mass data in form of text news and tick-by-tick asset prices to forecast the risk of upcoming volatility shocks. Holger Kömm embeds the proposed strategy in a monitoring system, using first, a sequence of competing estimators to compute the unobservable volatility; second, a new two-state Markov switching mixture model for autoregressive and zero-inflated time-series to identify structural breaks in a latent data generation process and third, a selection of competing pattern recognition algorithms to classify the potential information embedded in unexpected, but public observable text data in shock and nonshock information. The monitor is trained, tested, and evaluated on a two year survey on the prime standard assets listed in the indices DAX, MDAX, SDAX and TecDAX.



Volatility Forecasting In Futures Markets


Volatility Forecasting In Futures Markets
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Author : Theo Athanasiadis
language : en
Publisher:
Release Date : 2015

Volatility Forecasting In Futures Markets written by Theo Athanasiadis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.


Volatility forecasting has paramount importance in position sizing and risk management of CTAs. In this paper we examine the out-of-sample forecasts of widely used volatility estimators for the S&P 500 and the 10-Year US Note from a statistical and Value-at-Risk perspective. Although we do not find evidence for a volatility estimator that is statistically superior, we show that the volatility process of each asset is different with asymmetric GARCH models generating superior forecasts for the S&P 500, whereas symmetric GARCH, the Yang-Zhang estimator along with the implied volatility forecasting better the 10-Year US Note volatility. We also show that the volatility of the 10-Year US Note is more forecastable than that of the S&P 500 producing smaller errors. More importantly, we find that improving the volatility forecast can generate superior VaR estimates that can be accurate under the normal distribution failing only at the lowest quantiles mainly because the distribution is mispecified and badly approximated by the normal. Semi-parametric QML-GARCH models that use the empirical quantiles of the distribution along with GARCH forecasts address that issue and generate superior VaR estimates outperforming all other methods.



Introduction To Statistical Methods For Biosurveillance


Introduction To Statistical Methods For Biosurveillance
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Author : Ronald D. Fricker
language : en
Publisher: Cambridge University Press
Release Date : 2013-02-25

Introduction To Statistical Methods For Biosurveillance written by Ronald D. Fricker 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 2013-02-25 with Mathematics categories.


Presents basic and advanced methods with a focus on demonstrated added value for a broad class of public health surveillance problems.



Issues In Finance Business And Economics Research 2013 Edition


Issues In Finance Business And Economics Research 2013 Edition
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Author :
language : en
Publisher: ScholarlyEditions
Release Date : 2013-05-01

Issues In Finance Business And Economics Research 2013 Edition written by and has been published by ScholarlyEditions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-01 with Business & Economics categories.


Issues in Finance, Business, and Economics Research: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Additional Research. The editors have built Issues in Finance, Business, and Economics Research: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Additional Research in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Finance, Business, and Economics Research: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.



Financial Risk Management With Bayesian Estimation Of Garch Models


Financial Risk Management With Bayesian Estimation Of Garch Models
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Author : David Ardia
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-05-08

Financial Risk Management With Bayesian Estimation Of Garch Models written by David Ardia and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-05-08 with Business & Economics categories.


This book presents in detail methodologies for the Bayesian estimation of sing- regime and regime-switching GARCH models. These models are widespread and essential tools in n ancial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach o ers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The author is indebted to numerous individuals for help in the preparation of this study. Primarily, I owe a great debt to Prof. Dr. Philippe J. Deschamps who inspired me to study Bayesian econometrics, suggested the subject, guided me under his supervision and encouraged my research. I would also like to thank Prof. Dr. Martin Wallmeier and my colleagues of the Department of Quantitative Economics, in particular Michael Beer, Roberto Cerratti and Gilles Kaltenrieder, for their useful comments and discussions. I am very indebted to my friends Carlos Ord as Criado, Julien A. Straubhaar, J er ^ ome Ph. A. Taillard and Mathieu Vuilleumier, for their support in the elds of economics, mathematics and statistics. Thanks also to my friend Kevin Barnes who helped with my English in this work. Finally, I am greatly indebted to my parents and grandparents for their support and encouragement while I was struggling with the writing of this thesis.



Statistical Surveillance


Statistical Surveillance
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Author : David Bock
language : en
Publisher:
Release Date : 2004

Statistical Surveillance written by David Bock and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Business & Economics categories.


This is a Ph.D. dissertation. Statistical surveillance is used to repeatedly evaluate the amount of information contained in observations which are achieved continuously. This makes it possible to quickly and safely detect changes in the way economic and financial time series evolve through time. Thus, the optimal time for decisions can be determined. The thesis treats systems for early warnings of turns in economic processes. In papers I & II it is demonstrated how such systems can be used to predict the turning points of the general business cycle, by detecting turns in leading indicators. In papers III & IV some strategies for timely transactions in the financial market are analyzed by means of the theory of statistical surveillance.



Financial Risk Forecasting


Financial Risk Forecasting
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Author : Jon Danielsson
language : en
Publisher: John Wiley & Sons
Release Date : 2011-04-20

Financial Risk Forecasting written by Jon Danielsson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-20 with Business & Economics categories.


Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes on to present volatility forecasting with both univatiate and multivatiate methods, discussing the various methods used by industry, with a special focus on the GARCH family of models. The evaluation of the quality of forecasts is discussed in detail. Next, the main concepts in risk and models to forecast risk are discussed, especially volatility, value-at-risk and expected shortfall. The focus is both on risk in basic assets such as stocks and foreign exchange, but also calculations of risk in bonds and options, with analytical methods such as delta-normal VaR and duration-normal VaR and Monte Carlo simulation. The book then moves on to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes by focussing on the forecasting of risk in very large and uncommon events with extreme value theory and considering the underlying assumptions behind almost every risk model in practical use – that risk is exogenous – and what happens when those assumptions are violated. Every method presented brings together theoretical discussion and derivation of key equations and a discussion of issues in practical implementation. Each method is implemented in both MATLAB and R, two of the most commonly used mathematical programming languages for risk forecasting with which the reader can implement the models illustrated in the book. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. The second and third introduce R and MATLAB, providing a discussion of the basic implementation of the software packages. And the final looks at the concept of maximum likelihood, especially issues in implementation and testing. The book is accompanied by a website - www.financialriskforecasting.com – which features downloadable code as used in the book.