By
Ramazan Gençay, University of Windsor, Ontario, Canada
Michel Dacorogna, Zurich Re, Switzerland
Ulrich Muller, Olsen& Associates, Switzerland
Olivier Pictet, Olse & Associates, Zurich, Switzerland
Richard Olsen, Olsen & Associates, Zurich, Switzerland
Description
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.
Audience:
Financial analysts and practitioners, as well as advanced undergraduate and graduate students in the areas of econometrics, applied economic
analysis, economic statistics, and probability and statistics.
