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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
Product 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.
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Front Cover | Copyright | Table of Contents | Excerpt | Index
A famous climber, when asked why he was willing to put his life in danger to climb dangerous summits, answered: "Because they are there." Read the first page
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Most Helpful Customer Reviews
3 of 4 people found the following review helpful
Amazon Verified Purchase
I know a fair amount about finance (just finished a masters in finance and about to embark on a phd) but knew nothing about high-frequency.
After reading Olsen's book I feel I have had a great introduction and am very keen to know more.
The writing style is effortless and concise. One of those books that does what is necessary while making it look easy. It's only when I compare with some other textbooks that it's clear how well this is written.
The only criticisms could be that (1) the main asset class covered is FX, although for a good reason, which they cover. (2) the content could be slightly dated, this first (and only) edition is published back in 2001. However, it has aged very well.
I am now about to hunt down more information on this topic, having been inspired by Olsen. I only hope further books and papers are as well written.
After reading Olsen's book I feel I have had a great introduction and am very keen to know more.
The writing style is effortless and concise. One of those books that does what is necessary while making it look easy. It's only when I compare with some other textbooks that it's clear how well this is written.
The only criticisms could be that (1) the main asset class covered is FX, although for a good reason, which they cover. (2) the content could be slightly dated, this first (and only) edition is published back in 2001. However, it has aged very well.
I am now about to hunt down more information on this topic, having been inspired by Olsen. I only hope further books and papers are as well written.
4 of 12 people found the following review helpful
The book covers a wide range of topics related to
high-frequency data in Finance. There is a very detailed
approach to tackle a huge amount of data and to deal with
its based stylized facts. The book triggers the reader's
desire to update his knowledge in the field of finance.
high-frequency data in Finance. There is a very detailed
approach to tackle a huge amount of data and to deal with
its based stylized facts. The book triggers the reader's
desire to update his knowledge in the field of finance.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
9 reviews
33 of 39 people found the following review helpful
More Than An Introduction
28 May 2001
This one of the few books on high frequency finance is a most welcome to the literature. The book is useful not only for people who are new to the subject but also for researchers in the field since it is a most uniform treatment of many topics. From adaptive data cleaning (chapter 4) to intraday and weekly seasonality (chapter 6) and real time trading models (chapter 11), it covers a broad range of topics specific to high frequency financial time series analysis. Chapters on volatility modeling (Chapter 8), forecasting (chapter 9) and correlation and multivariate risk (chapter 10) are enlightening especially for risk exposure analysis and risk management purposes. Finally, the the extensive bibliography is a precious source for those who would like to explore certain topics in detail. I highly recommend it for practitioners as well as researchers in the field.
3 of 3 people found the following review helpful
Definitely mid-frequency in this day and age
5 July 2011
Amazon Verified Purchase
This book doesn't deal with true high-frequency trading, where it is more about execution than anything else. The book IS ten years old when I write this, so high frequency trading has taken on a different meaning, so no false advert here.
That said, it is a great treatment of the practical issues of handling large, heterogeneous financial data sets and their statistics. I haven't seen their methodology and framework anywhere else, although there are some really good treatments of irregularly spaced financial data (Hautsch, Engle).
The authors are prolific in this area, in particular, the use of tick data to build better volatility models and the use of seasonality (business time scale) and stochastic time (see intrinsic time). They also present a good way to use higher frequency homogeneous data to effectively filter historical volatility computations that makes them more robust when the data is interpolated or sparse. The best part is that they bring everything together for use in multivariate cases and for forecasting/trading.
Overall, this is a great book, that doesn't have many peers (if any). I can't recommend it enough.
Minor downsides:
(1) I also agree with the other reviewers on the notation, although it doesn't bother me that much personally.
(2) Would be nice to see some type of flowchart for an implementation of the methods in Ch. 6 and later, like they did in Ch. 4.
(3) No explicit mention of duration and/or point processes, although it is implicit in many of their techniques. This one might be a little unfair because one can't expect the authors to survey the entire body of literature.
That said, it is a great treatment of the practical issues of handling large, heterogeneous financial data sets and their statistics. I haven't seen their methodology and framework anywhere else, although there are some really good treatments of irregularly spaced financial data (Hautsch, Engle).
The authors are prolific in this area, in particular, the use of tick data to build better volatility models and the use of seasonality (business time scale) and stochastic time (see intrinsic time). They also present a good way to use higher frequency homogeneous data to effectively filter historical volatility computations that makes them more robust when the data is interpolated or sparse. The best part is that they bring everything together for use in multivariate cases and for forecasting/trading.
Overall, this is a great book, that doesn't have many peers (if any). I can't recommend it enough.
Minor downsides:
(1) I also agree with the other reviewers on the notation, although it doesn't bother me that much personally.
(2) Would be nice to see some type of flowchart for an implementation of the methods in Ch. 6 and later, like they did in Ch. 4.
(3) No explicit mention of duration and/or point processes, although it is implicit in many of their techniques. This one might be a little unfair because one can't expect the authors to survey the entire body of literature.
6 of 8 people found the following review helpful
modelling financial instruments
7 Mar 2007
The book gives an indepth statistical modelling of important financial events, that have time dependency. It is suitable for the financial analyst who wants a semi-empirical approach.
For some quantities, like foreign exchange data, there is a comparison between fully empirical results and various theoretical models. What is investigated are such behaviours like scaling laws, for the absolute returns as a function of frequency. Here, it has been empirically observed that scalings do exist for FX rates.
Whenever possible, the book gives rigorous results, often encapsulated in theorems relating to distributions of independently distributed random variables. The reader should have a background in statistics, with the equivalent of several years of undergraduate courses.
For some quantities, like foreign exchange data, there is a comparison between fully empirical results and various theoretical models. What is investigated are such behaviours like scaling laws, for the absolute returns as a function of frequency. Here, it has been empirically observed that scalings do exist for FX rates.
Whenever possible, the book gives rigorous results, often encapsulated in theorems relating to distributions of independently distributed random variables. The reader should have a background in statistics, with the equivalent of several years of undergraduate courses.
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