Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data
Title | Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data PDF eBook |
Author | Norman R. Swanson |
Publisher | MDPI |
Pages | 196 |
Release | 2021-08-31 |
Genre | Business & Economics |
ISBN | 303650852X |
Recently, considerable attention has been placed on the development and application of tools useful for the analysis of the high-dimensional and/or high-frequency datasets that now dominate the landscape. The purpose of this Special Issue is to collect both methodological and empirical papers that develop and utilize state-of-the-art econometric techniques for the analysis of such data.
Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data
Title | Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data PDF eBook |
Author | Norman R. Swanson |
Publisher | |
Pages | 196 |
Release | 2021 |
Genre | |
ISBN | 9783036508535 |
Recently, considerable attention has been placed on the development and application of tools useful for the analysis of the high-dimensional and/or high-frequency datasets that now dominate the landscape. The purpose of this Special Issue is to collect both methodological and empirical papers that develop and utilize state-of-the-art econometric techniques for the analysis of such data.
High-Frequency Financial Econometrics
Title | High-Frequency Financial Econometrics PDF eBook |
Author | Yacine Aït-Sahalia |
Publisher | Princeton University Press |
Pages | 684 |
Release | 2014-07-21 |
Genre | Business & Economics |
ISBN | 1400850320 |
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.
Handbook of Modeling High-Frequency Data in Finance
Title | Handbook of Modeling High-Frequency Data in Finance PDF eBook |
Author | Frederi G. Viens |
Publisher | John Wiley & Sons |
Pages | 468 |
Release | 2011-12-20 |
Genre | Business & Economics |
ISBN | 0470876883 |
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 Econometrics
Title | High Frequency Financial Econometrics PDF eBook |
Author | Luc Bauwens |
Publisher | Springer Science & Business Media |
Pages | 310 |
Release | 2007-12-31 |
Genre | Business & Economics |
ISBN | 3790819921 |
Shedding light on some of the most pressing open questions in the analysis of high frequency data, this volume presents cutting-edge developments in high frequency financial econometrics. Coverage spans a diverse range of topics, including market microstructure, tick-by-tick data, bond and foreign exchange markets, and large dimensional volatility modeling. The volume is of interest to graduate students, researchers, and industry professionals.
Modelling and Forecasting High Frequency Financial Data
Title | Modelling and Forecasting High Frequency Financial Data PDF eBook |
Author | Stavros Degiannakis |
Publisher | Springer |
Pages | 301 |
Release | 2016-04-29 |
Genre | Business & Economics |
ISBN | 1137396490 |
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.
Big and Complex Data Analysis
Title | Big and Complex Data Analysis PDF eBook |
Author | S. Ejaz Ahmed |
Publisher | Springer |
Pages | 390 |
Release | 2017-03-21 |
Genre | Mathematics |
ISBN | 3319415735 |
This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essential new developments in the field. The continued and rapid advancement of modern technology now allows scientists to collect data of increasingly unprecedented size and complexity. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data. Simultaneous variable selection and estimation is one of the key statistical problems involved in analyzing such big and complex data. The purpose of this book is to stimulate research and foster interaction between researchers in the area of high-dimensional data analysis. More concretely, its goals are to: 1) highlight and expand the breadth of existing methods in big data and high-dimensional data analysis and their potential for the advancement of both the mathematical and statistical sciences; 2) identify important directions for future research in the theory of regularization methods, in algorithmic development, and in methodologies for different application areas; and 3) facilitate collaboration between theoretical and subject-specific researchers.