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Risk Estimation On High Frequency Financial Data


Risk Estimation On High Frequency Financial Data
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Risk Estimation On High Frequency Financial Data


Risk Estimation On High Frequency Financial Data
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Author : Florian Jacob
language : en
Publisher: Springer
Release Date : 2015-03-28

Risk Estimation On High Frequency Financial Data written by Florian Jacob and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-28 with Mathematics categories.


By studying the ability of the Normal Tempered Stable (NTS) model to fit the statistical features of intraday data at a 5 min sampling frequency, Florian Jacobs extends the research on high frequency data as well as the appliance of tempered stable models. He examines the DAX30 returns using ARMA-GARCH NTS, ARMA-GARCH MNTS (Multivariate Normal Tempered Stable) and ARMA-FIGARCH (Fractionally Integrated GARCH) NTS. The models will be benchmarked through their goodness of fit and their VaR and AVaR, as well as in an historical Backtesting.



Handbook Of Modeling High Frequency Data In Finance


Handbook Of Modeling High Frequency Data In Finance
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Author : Frederi G. Viens
language : en
Publisher: John Wiley & Sons
Release Date : 2011-12-20

Handbook Of Modeling High Frequency Data In Finance written by Frederi G. Viens 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 2011-12-20 with Business & Economics categories.


CUTTING-EDGE DEVELOPMENTS IN HIGH-FREQUENCY FINANCIAL ECONOMETRICS In recent years, the availability of high-frequency data and advances in computing have allowed financial practitioners to design systems that can handle and analyze this information. Handbook of Modeling High-Frequency Data in Finance addresses the many theoretical and practical questions raised by the nature and intrinsic properties of this data. A one-stop compilation of empirical and analytical research, this handbook explores data sampled with high-frequency finance in financial engineering, statistics, and the modern financial business arena. Every chapter uses real-world examples to present new, original, and relevant topics that relate to newly evolving discoveries in high-frequency finance, such as: Designing new methodology to discover elasticity and plasticity of price evolution Constructing microstructure simulation models Calculation of option prices in the presence of jumps and transaction costs Using boosting for financial analysis and trading The handbook motivates practitioners to apply high-frequency finance to real-world situations by including exclusive topics such as risk measurement and management, UHF data, microstructure, dynamic multi-period optimization, mortgage data models, hybrid Monte Carlo, retirement, trading systems and forecasting, pricing, and boosting. The diverse topics and viewpoints presented in each chapter ensure that readers are supplied with a wide treatment of practical methods. Handbook of Modeling High-Frequency Data in Finance is an essential reference for academics and practitioners in finance, business, and econometrics who work with high-frequency data in their everyday work. It also serves as a supplement for risk management and high-frequency finance courses at the upper-undergraduate and graduate levels.



High Frequency Financial Market Data


High Frequency Financial Market Data
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Author : Owain Ap Gwilym
language : en
Publisher:
Release Date : 1999

High Frequency Financial Market Data written by Owain Ap Gwilym and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Capital market categories.


A consideration of the sources, management, manipulation and uses of high-frequency financial market data. It applies HFD to model development for data analysis, trading, forecasting and risk management. Future trends are covered, and there is a bibliography of the literature.



Estimation And Forecast Evaluation Of Risk Measures With High Frequency Financial Data


Estimation And Forecast Evaluation Of Risk Measures With High Frequency Financial Data
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Author : Colin Tormod Bowers
language : en
Publisher:
Release Date : 2015

Estimation And Forecast Evaluation Of Risk Measures With High Frequency Financial Data written by Colin Tormod Bowers and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computer algorithms categories.


This thesis contrbutes to the financial econometric literature in the areas of estimation, forecasting, and forecast evaluation, using high frequency financial data.



High Frequency Financial Econometrics


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.



An Introduction To High Frequency Finance


An Introduction To High Frequency Finance
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Author : Ramazan Gençay
language : en
Publisher: Elsevier
Release Date : 2001-05-29

An Introduction To High Frequency Finance written by Ramazan Gençay and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-05-29 with Business & Economics categories.


Liquid markets generate hundreds or thousands of ticks (the minimum change in price a security can have, either up or down) every business day. Data vendors such as Reuters transmit more than 275,000 prices per day for foreign exchange spot rates alone. Thus, high-frequency data can be a fundamental object of study, as traders make decisions by observing high-frequency or tick-by-tick data. Yet most studies published in financial literature deal with low frequency, regularly spaced data. For a variety of reasons, high-frequency data are becoming a way for understanding market microstructure. This book discusses the best mathematical models and tools for dealing with such vast amounts of data. This book provides a framework for the analysis, modeling, and inference of high frequency financial time series. With particular emphasis on foreign exchange markets, as well as currency, interest rate, and bond futures markets, this unified view of high frequency time series methods investigates the price formation process and concludes by reviewing techniques for constructing systematic trading models for financial assets.



Econometrics Of Financial High Frequency Data


Econometrics Of Financial High Frequency Data
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Author : Nikolaus Hautsch
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-10-12

Econometrics Of Financial High Frequency Data written by Nikolaus Hautsch 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 2011-10-12 with Business & Economics categories.


The availability of financial data recorded on high-frequency level has inspired a research area which over the last decade emerged to a major area in econometrics and statistics. The growing popularity of high-frequency econometrics is driven by technological progress in trading systems and an increasing importance of intraday trading, liquidity risk, optimal order placement as well as high-frequency volatility. This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis.



Modelling And Forecasting High Frequency Financial Data


Modelling And Forecasting High Frequency Financial Data
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Author : Stavros Degiannakis
language : en
Publisher: Springer
Release Date : 2016-04-29

Modelling And Forecasting High Frequency Financial Data written by Stavros Degiannakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-29 with Business & Economics categories.


The global financial crisis has reopened discussion surrounding the use of appropriate theoretical financial frameworks to reflect the current economic climate. There is a need for more sophisticated analytical concepts which take into account current quantitative changes and unprecedented turbulence in the financial markets. This book provides a comprehensive guide to the quantitative analysis of high frequency financial data in the light of current events and contemporary issues, using the latest empirical research and theory. It highlights and explains the shortcomings of theoretical frameworks and provides an explanation of high-frequency theory, emphasising ways in which to critically apply this knowledge within a financial context. Modelling and Forecasting High Frequency Financial Data combines traditional and updated theories and applies them to real-world financial market situations. It will be a valuable and accessible resource for anyone wishing to understand quantitative analysis and modelling in current financial markets.



High Frequency Financial Econometrics


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.



Volatility Analysis For High Frequency Financial Data


Volatility Analysis For High Frequency Financial Data
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Author : Xiaohua Zheng
language : en
Publisher:
Release Date : 2009

Volatility Analysis For High Frequency Financial Data written by Xiaohua Zheng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Electronic dissertations categories.


Measuring and modeling financial volatility are key steps for derivative pricing and risk management. In financial markets, there are two kinds of data: low-frequency financial data and high-frequency financial data. Most research has been done based on low-frequency data. In this dissertation we focus on high-frequency data. In theory, the sum of squares of log returns sampled at high frequency estimates their variance. For log price data following a diffusion process without noise, the realized volatility converges to its quadratic variation. When log price data contain market microstructure noise, the realized volatility explodes as the sampling interval converges to 0. In this dissertation, we generalize the fundamental Ito isometry and analyze the speed with which stochastic processes approach to their quadratic variations. We determine the difference between realized volatility and quadratic variation under mean square constraints for Brownian motion and general case. We improve the estimation for quadratic variation. The estimators found by us converge to quadratic variation at a higher rate.