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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.…mehr

Produktbeschreibung
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.
Autorenporträt
Ramazan Gençay is a professor in the economics department at the University of Windsor, Ontario, Canada. His areas of specialization are financial econometrics, nonlinear time series, nonparametric econometrics, and chaotic dynamics. His publications appear in finance, economics, statistics and physics journals. Some of his publications are published in the Journal of the American Statistical Association, Journal of Econometrics, Journal of International Economics, Journal of Nonparametric Statistics, Journal of Empirical Finance, Journal of Economic Dynamics and Control, Journal of Applied Econometrics, European Economic Review, Journal of Forecasting, Physica A, Physica D and Physics Letters A. He is co-editor of Studies in Nonlinear Dynamics and Econometrics and IEEE Transactions in Computational Finance. He is also a co-author of An Introduction to High-Frequency Finance (Academic Press, 2001).
Rezensionen
Prepublication Praise:
"The authors have shaped the field of high-frequency data in finance; the text provides an excellent summary of their pioneering work." --PAUL EMBRECHTS, Professor of Mathematics, ETH Zurich

"An Introduction to High-Frequency Finance by the research team from Olsen & Associates is an amazing presentation of their work over the last decade and a half examining high-frequency, primarily currency, data. The volume includes details of data handling, filtering methods, scaling procedures, volatility models, automatic market making and trading rules that for many years were proprietary information. I highly recommend the book for anyone using tick data." --ROBERT ENGLE, Department of Finance, Stern School, NYU and Department of Economics, University of California, San Diego

"At long last, the study of financial prices is moving beyond convenient oversimplifications. For providing much of the best data and an indispensable bridge between the financial and academic communities, this flowering is deeply indebted to the group led by Dr. Richard Olsen.
This group and its alumni have also analyzed their own data. That work, which I often quote, has now been collected and extended in a book. I shall wear it out by constant use and it is a delight to recommend it to the emerging rational finance community." --BENOIT B. MANDELBROT, Sterling Professor of Mathematical Sciences, Yale University