Empirical Properties Of Functional Regression Models And Application To High Frequency Financial Data
DOWNLOAD
Download Empirical Properties Of Functional Regression Models And Application To High Frequency Financial Data PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Empirical Properties Of Functional Regression Models And Application To High Frequency Financial Data book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Empirical Properties Of Functional Regression Models And Application To High Frequency Financial Data
DOWNLOAD
Author : Zhang, Xi
language : en
Publisher:
Release Date : 2013
Empirical Properties Of Functional Regression Models And Application To High Frequency Financial Data written by Zhang, Xi 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.
Functional data analysis (FDA) has grown into a substantial field of statistical research, with new methodology, numerous useful applications and interesting novel theoretical developments. My dissertation focuses on the empirical properties of functional regression models and their application to financial data. We start from testing the empirical properties of forecasts with the functional autoregressive models based on simulated and real data. We define intraday returns and consider their prediction from such returns on a market index. This is an extension to intraday data of the Capital Asset Pricing model. Finally we investigate multifactor functional models and assess their suitability for the prediction of intraday returns for various financial assets, including stock and commodity futures.
Handbook Of Modeling High Frequency Data In Finance
DOWNLOAD
Author : Frederi G. Viens
language : en
Publisher: John Wiley & Sons
Release Date : 2011-11-16
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 2011-11-16 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.
Functional Data Based Inference For High Frequency Financial Data
DOWNLOAD
Author : Bahaeddine Taoufik
language : en
Publisher:
Release Date : 2016
Functional Data Based Inference For High Frequency Financial Data written by Bahaeddine Taoufik and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
This thesis is concerned with developing new functional data techniques for high frequency financial applications. Chapter 1 of the thesis introduces Functional Data Analysis (FDA) with examples of application to real data. In this chapter, we provide some theoretical foundations for FDA. We also present a general theory and basic properties of reproducing kernel Hilbert spaces (RKHS). Chapter 2 of the thesis explores the relationship between market returns and a number of financial factors by fitting functional regression models. We establish two estimation procedures based on the least squares and generalized least squares methods. We also present four hypothesis testing procedures on the functional regression coefficients based on the squared integral $L^2$ approach and the PCA approach for both least squares and generalized least squares methods. New asymptotic results are established allowing for minor departures from stationarity, to ensure convergence and asymptotic normality of our estimates. Our functional regression model is applied to cross-section returns data. Our data application results indicate a positive correlation between the volatility factor ``FVIX" and the higher returns and a negative correlation between the volatility factor ``FVIX" and the low and middle returns.Chapter 3 of the thesis develops a nonlinear function-on-function model using RKHS for real-valued functions. We establish the minimax rate of convergence of the excess prediction risk. Our simulation studies faced computational challenges due to the complexity of the estimation procedure. We examine the prediction performance accuracy of our model through a simulation study. Our nonlinear function-function model is applied to Cumulative intraday return (CIDR) data in order to investigate the prediction performance of Standard \& Poor's 500 Index (S\&P 500) and the Dow Jones Industrial Average (DJIA) for General Electric Company (GE) and International Business Machines Corp.(IBM) for the three periods defining the crisis: ``Before," `` During," and `` After''.
High Frequency Financial Econometrics
DOWNLOAD
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.
Handbook Of High Frequency Trading And Modeling In Finance
DOWNLOAD
Author : Ionut Florescu
language : en
Publisher: John Wiley & Sons
Release Date : 2016-04-05
Handbook Of High Frequency Trading And Modeling In Finance written by Ionut Florescu 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 2016-04-05 with Business & Economics categories.
Reflecting the fast pace and ever-evolving nature of the financial industry, the Handbook of High-Frequency Trading and Modeling in Finance details how high-frequency analysis presents new systematic approaches to implementing quantitative activities with high-frequency financial data. Introducing new and established mathematical foundations necessary to analyze realistic market models and scenarios, the handbook begins with a presentation of the dynamics and complexity of futures and derivatives markets as well as a portfolio optimization problem using quantum computers. Subsequently, the handbook addresses estimating complex model parameters using high-frequency data. Finally, the handbook focuses on the links between models used in financial markets and models used in other research areas such as geophysics, fossil records, and earthquake studies. The Handbook of High-Frequency Trading and Modeling in Finance also features: • Contributions by well-known experts within the academic, industrial, and regulatory fields • A well-structured outline on the various data analysis methodologies used to identify new trading opportunities • Newly emerging quantitative tools that address growing concerns relating to high-frequency data such as stochastic volatility and volatility tracking; stochastic jump processes for limit-order books and broader market indicators; and options markets • Practical applications using real-world data to help readers better understand the presented material The Handbook of High-Frequency Trading and Modeling in Finance is an excellent reference for professionals in the fields of business, applied statistics, econometrics, and financial engineering. The handbook is also a good supplement for graduate and MBA-level courses on quantitative finance, volatility, and financial econometrics. Ionut Florescu, PhD, is Research Associate Professor in Financial Engineering and Director of the Hanlon Financial Systems Laboratory at Stevens Institute of Technology. His research interests include stochastic volatility, stochastic partial differential equations, Monte Carlo Methods, and numerical methods for stochastic processes. Dr. Florescu is the author of Probability and Stochastic Processes, the coauthor of Handbook of Probability, and the coeditor of Handbook of Modeling High-Frequency Data in Finance, all published by Wiley. Maria C. Mariani, PhD, is Shigeko K. Chan Distinguished Professor in Mathematical Sciences and Chair of the Department of Mathematical Sciences at The University of Texas at El Paso. Her research interests include mathematical finance, applied mathematics, geophysics, nonlinear and stochastic partial differential equations and numerical methods. Dr. Mariani is the coeditor of Handbook of Modeling High-Frequency Data in Finance, also published by Wiley. H. Eugene Stanley, PhD, is William Fairfield Warren Distinguished Professor at Boston University. Stanley is one of the key founders of the new interdisciplinary field of econophysics, and has an ISI Hirsch index H=128 based on more than 1200 papers. In 2004 he was elected to the National Academy of Sciences. Frederi G. Viens, PhD, is Professor of Statistics and Mathematics and Director of the Computational Finance Program at Purdue University. He holds more than two dozen local, regional, and national awards and he travels extensively on a world-wide basis to deliver lectures on his research interests, which range from quantitative finance to climate science and agricultural economics. A Fellow of the Institute of Mathematics Statistics, Dr. Viens is the coeditor of Handbook of Modeling High-Frequency Data in Finance, also published by Wiley.
Modelling And Forecasting High Frequency Financial Data
DOWNLOAD
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.
An Introduction To Analysis Of Financial Data With R
DOWNLOAD
Author : Ruey S. Tsay
language : en
Publisher: John Wiley & Sons
Release Date : 2014-08-21
An Introduction To Analysis Of Financial Data With R written by Ruey S. Tsay 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 2014-08-21 with Business & Economics categories.
A complete set of statistical tools for beginning financial analysts from a leading authority Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research. The author supplies a hands-on introduction to the analysis of financial data using the freely available R software package and case studies to illustrate actual implementations of the discussed methods. The book begins with the basics of financial data, discussing their summary statistics and related visualization methods. Subsequent chapters explore basic time series analysis and simple econometric models for business, finance, and economics as well as related topics including: Linear time series analysis, with coverage of exponential smoothing for forecasting and methods for model comparison Different approaches to calculating asset volatility and various volatility models High-frequency financial data and simple models for price changes, trading intensity, and realized volatility Quantitative methods for risk management, including value at risk and conditional value at risk Econometric and statistical methods for risk assessment based on extreme value theory and quantile regression Throughout the book, the visual nature of the topic is showcased through graphical representations in R, and two detailed case studies demonstrate the relevance of statistics in finance. A related website features additional data sets and R scripts so readers can create their own simulations and test their comprehension of the presented techniques. An Introduction to Analysis of Financial Data with R is an excellent book for introductory courses on time series and business statistics at the upper-undergraduate and graduate level. The book is also an excellent resource for researchers and practitioners in the fields of business, finance, and economics who would like to enhance their understanding of financial data and today's financial markets.
Analysis Of Financial Time Series
DOWNLOAD
Author : Ruey S. Tsay
language : en
Publisher: John Wiley & Sons
Release Date : 2010-08-30
Analysis Of Financial Time Series written by Ruey S. Tsay 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 2010-08-30 with Mathematics categories.
This book provides a broad, mature, and systematic introduction to current financial econometric models and their applications 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 Bayesian inference in finance methods Key features of the new edition include additional coverage of modern day topics such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth transition from S-Plus to R; and expanded empirical financial data sets. The overall objective of the book is to provide some knowledge of financial time series, introduce some statistical tools useful for analyzing these series and gain experience in financial applications of various econometric methods.
Recent Advances In Theory And Methods For The Analysis Of High Dimensional And High Frequency Financial Data
DOWNLOAD
Author : Norman R. Swanson
language : en
Publisher: MDPI
Release Date : 2021-08-31
Recent Advances In Theory And Methods For The Analysis Of High Dimensional And High Frequency Financial Data written by Norman R. Swanson and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-31 with Business & Economics categories.
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.
Regression Models For Ordinal Valued Time Series With Application To High Frequency Financial Data
DOWNLOAD
Author : Gernot Müller
language : en
Publisher:
Release Date : 2002
Regression Models For Ordinal Valued Time Series With Application To High Frequency Financial Data written by Gernot Müller and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.