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Author: Yacine Aït-Sahalia
Publisher: Princeton University Press
ISBN: 0691161437
Category : Business & Economics
Languages : en
Pages : 683
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Book Description
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.
Author: Yacine Aït-Sahalia
Publisher: Princeton University Press
ISBN: 0691161437
Category : Business & Economics
Languages : en
Pages : 683
Get Book Here
Book Description
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.
Author: David Schreindorfer
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 164
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Book Description
Author: Maria Elvira Mancino
Publisher:
ISBN:
Category :
Languages : en
Pages : 53
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Book Description
Availability of high frequency data has improved the capability of computing volatility in an efficient way. Nevertheless, measuring volatility/covariance from the observation of the asset price is challenging for two main reasons: observed asset prices are generally affected by noise microstructure effects and tick-by-tick returns are asynchronous across different assets. In this paper we review the definition and the statistical properties of the so called Fourier estimator of multivariate volatility, with particular focus on using high frequency data. Exploiting the fact that the method allows to compute both the integrated and the instantaneous volatility, we show how to obtain estimators of the volatility of the volatility and the leverage as well. Further, we study the performance of the estimator in forecasting and in terms of portfolio utility in the presence of microstructure noise contaminations.
Author: Nikolaus Hautsch
Publisher: Springer Science & Business Media
ISBN: 364221925X
Category : Business & Economics
Languages : en
Pages : 381
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Book Description
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.
Author: Abdul Rafay
Publisher: Business Science Reference
ISBN: 9781522586333
Category :
Languages : en
Pages : 328
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Book Description
"This book provides understanding and lessons learned in regard to all aspects of financial technology utilization and management in individual, organizational, and societal experiences. It examines the emergence of financial technology during the last decade. Including discussion on topics such as regulatory environments, technology infrastructures, public sector initiatives, and financial technology for the social sector"--
Author: Yucheng Sun
Publisher:
ISBN:
Category :
Languages : en
Pages : 125
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Book Description
Based on high-frequency price data, this thesis focuses on estimating the realized covariance and the integrated volatility of asset prices, and applying volatility estimation to price jump detection. The first chapter uses the LASSO procedure to regularize some estimators of high dimensional realized covariance matrices. We establish theoretical properties of the regularized estimators that show its estimation precision and the probability that they correctly reveal the network structure of the assets. The second chapter proposes a novel estimator of the integrated volatility which is the quadratic variation of the continuous part in the price process. This estimator is obtained by truncating the two-scales realized variance estimator. We show its consistency in the presence of market microstructure noise and finite or infinite activity jumps in the price process. The third chapter employs this estimator to design a test to explore the existence of price jumps with noisy price data.
Author: Maria Elvira Mancino
Publisher: Springer
ISBN: 3319509691
Category : Mathematics
Languages : en
Pages : 139
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Book Description
This volume is a user-friendly presentation of the main theoretical properties of the Fourier-Malliavin volatility estimation, allowing the readers to experience the potential of the approach and its application in various financial settings. Readers are given examples and instruments to implement this methodology in various financial settings and applications of real-life data. A detailed bibliographic reference is included to permit an in-depth study.
Author: Yacine Aït-Sahalia
Publisher: Princeton University Press
ISBN: 1400850320
Category : Business & Economics
Languages : en
Pages : 684
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Book Description
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.
Author: Stavros Degiannakis
Publisher: Springer
ISBN: 1137396490
Category : Business & Economics
Languages : en
Pages : 411
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Book Description
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.
Author: Wenhao Cui
Publisher:
ISBN: 9781529667844
Category : Finance
Languages : en
Pages : 0
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Book Description
The availability of high-frequency financial data in the last 20 years has led to a rich literature on its estimation and forecasting. Motivated by the challenges in utilizing high-frequency financial data, we decide to investigate the problem of estimating and forecasting return volatility, taking into account the presence of market microstructure noise, jump, and time endogeneity. With this target in mind, we solve the volatility estimation problem by combining several existing methods with our Laplace estimator of volatility. We also investigate the forecasting problem by employing linear regression models. Furthermore, we apply a standard data cleaning procedure to reduce the potential impact of outliers and errors. After trimming, we are able to draw a robust conclusion across a variety of different linear regression models. The process leads to a better understanding of utilizing high-frequency financial data and its application in volatility forecasting.
