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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. 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.
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