Econometrics of Financial High-Frequency Data
Econometrics of Financial High-Frequency Data

Author: Nikolaus Hautsch

Publisher: Springer Science & Business Media

Published: 2011-10-12

Total Pages: 381

ISBN-13: 364221925X

DOWNLOAD EBOOK

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.

High-Frequency Financial Econometrics
High-Frequency Financial Econometrics

Author: Yacine Aït-Sahalia

Publisher: Princeton University Press

Published: 2014-07-21

Total Pages: 683

ISBN-13: 0691161437

DOWNLOAD EBOOK

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

Author: Ramazan Gençay

Publisher: Elsevier

Published: 2001-05-29

Total Pages: 411

ISBN-13: 008049904X

DOWNLOAD EBOOK

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.

Handbook of Financial Time Series
Handbook of Financial Time Series

Author: Torben Gustav Andersen

Publisher: Springer Science & Business Media

Published: 2009-04-21

Total Pages: 1045

ISBN-13: 3540712976

DOWNLOAD EBOOK

The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.

Econometric Modelling of Stock Market Intraday Activity
Econometric Modelling of Stock Market Intraday Activity

Author: Luc Bauwens

Publisher: Springer Science & Business Media

Published: 2001-08-31

Total Pages: 214

ISBN-13: 9780792374244

DOWNLOAD EBOOK

The recent widespread availability of intraday tick-by-tick databases for stocks, options and currencies has had an important impact on research in applied financial econometrics and market microstructure. Econometric Modelling of Stock Market Intraday Activity focuses on the econometric modelling of intraday tick-by-tick transaction data (trades and quote) for stock traded on the New York Stock Exchange (NYSE). Recent quantitative modelling tools such as intraday duration models and GARCH modes are presented. A survey of trading mechanisms in financial markets and a review of market microstructure issues is also included, which allows to gain a better understanding of the motivation underlying the use of the quantitative models. In the empirical applications, the link is made with the models of the market microstructure literature that have proposed an explicit treatment of time in the trading process. Other empirical applications deal with the modelling of intraday volatility and intraday Value-at-Risk. Although the models are applied to data for stock traded on the NYSE, they are not specific to this exchange and could be used to analyze other existing trading mechanisms. Accordingly, this book should be of interest to academics and graduate students involved in empirical finance and applied econometrics, regulators working for exchanges, and practitioners in banks or brokerage firms.

Financial, Macro and Micro Econometrics Using R
Financial, Macro and Micro Econometrics Using R

Author:

Publisher: North Holland

Published: 2020-01-20

Total Pages: 350

ISBN-13: 0128202505

DOWNLOAD EBOOK

Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.

Modeling Financial Time Series with S-PLUS
Modeling Financial Time Series with S-PLUS

Author: Eric Zivot

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 632

ISBN-13: 0387217630

DOWNLOAD EBOOK

The field of financial econometrics has exploded over the last decade This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This Second Edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments. Eric Zivot is an associate professor and Gary Waterman Distinguished Scholar in the Economics Department, and adjunct associate professor of finance in the Business School at the University of Washington. He regularly teaches courses on econometric theory, financial econometrics and time series econometrics, and is the recipient of the Henry T. Buechel Award for Outstanding Teaching. He is an associate editor of Studies in Nonlinear Dynamics and Econometrics. He has published papers in the leading econometrics journals, including Econometrica, Econometric Theory, the Journal of Business and Economic Statistics, Journal of Econometrics, and the Review of Economics and Statistics. Jiahui Wang is an employee of Ronin Capital LLC. He received a Ph.D. in Economics from the University of Washington in 1997. He has published in leading econometrics journals such as Econometrica and Journal of Business and Economic Statistics, and is the Principal Investigator of National Science Foundation SBIR grants. In 2002 Dr. Wang was selected as one of the "2000 Outstanding Scholars of the 21st Century" by International Biographical Centre.

High Frequency Data and Volatility, in Foreign Exchange Rates
High Frequency Data and Volatility, in Foreign Exchange Rates

Author: Bin Zhou

Publisher: Forgotten Books

Published: 2015-06-02

Total Pages: 32

ISBN-13: 9781330265826

DOWNLOAD EBOOK

Excerpt from High Frequency Data and Volatility, in Foreign Exchange Rates Exchange rates, like many other financial time series, display substantial heteroscedasticity. This poses obstacles in detecting trends and changes. Understanding volatility becomes extremely important in studying financial time series. Unfortunately, estimating volatility from low frequency data, such as daily, weekly, or monthly observations, is very difficult. The recent availability of ultra-high frequency observations, such as tick-by-tick data, to large financial institutions creates a new possibility for the analysis of volatile time series. This article uses tick-by-tick Deutsche Mark and US Dollar (DM/$) exchange rates to explore this new type of data. Unlike low frequency data, high frequency data have extremely high negative first order autocorrelation in their return. A model explaining the negative autocorrelation and volatility estimators using the high frequency data are proposed. Daily and hourly volatility of the DM/$ exchange rates are estimated and the behaviors of the volatility are discussed. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

Market Microstructure Theory
Market Microstructure Theory

Author: Maureen O'Hara

Publisher: John Wiley & Sons

Published: 1998-03-06

Total Pages: 310

ISBN-13: 0631207619

DOWNLOAD EBOOK

Written by one of the leading authorities in market microstructure research, this book provides a comprehensive guide to the theoretical work in this important area of finance.

The Econometrics of Sequential Trade Models
The Econometrics of Sequential Trade Models

Author: Stefan Kokot

Publisher: Springer Science & Business Media

Published: 2004-02-09

Total Pages: 218

ISBN-13: 9783540208143

DOWNLOAD EBOOK

This clearly structured and well-written reference work examines the consequences of speculative trading based on private information about financial asset markets. It presents an extensive and thorough discussion of theoretical and empirical methods used in previous studies on sequential trade models. The text also introduces a new framework for estimation and hypothesis testing that substantially advances earlier work in the field. The results that are necessary for understanding the introduced empirical framework are derived step-by-step. The text is ideally suited as a reference work on old and new results as well as a textbook for graduate courses on market microstructure theory, empirical methods in finance or econometrics.