| Description |
1 online resource (411 pages) |
| Contents |
Front Cover; AN INTRODUCTION TO HIGH-FREQUENCY FINANCE; Copyright Page; CONTENTS; LIST OF FIGURES; LIST OF TABLES; PREFACE; ACKNOWLEDGMENTS; CHAPTER 1. INTRODUCTION; CHAPTER 2. MARKETS AND DATA; CHAPTER 3. TIME SERIES of INTEREST; CHAPTER 4. ADAPTIVE DATA CLEANING; CHAPTER 5. BASIC STYLIZED FACTS; CHAPTER 6. MODELING SEASONAL VOLATILITY; CHAPTER 7. REALIZED VOLATILITY DYNAMICS; CHAPTER 8. VOLATILITY PROCESSES; CHAPTER 9. FORECASTING RISK AND RETURN; CHAPTER 10. CORRELATION AND MULTIVARIATE RISK; CHAPTER 11. TRADING MODELS; CHAPTER 12. TOWARD A THEORY of HETEROGENEOUS MARKETS; BIBLIOGRAPHY |
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INDEX |
| Summary |
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. T |
| Bibliography |
Includes bibliographical references (pages 356-375) and index |
| Notes |
English |
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Print version record |
| Subject |
Finance -- Econometric models
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Time-series analysis.
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Finance -- Econometric models.
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Finance -- Econometric models
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Time-series analysis
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| Form |
Electronic book
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| Author |
Dacorogna, Michel M
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Muller, Ulrich
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Pictet, Olivier
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Olsen, Richard
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| ISBN |
9780080499048 |
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008049904X |
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0122796713 |
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9780122796715 |
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