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Full Description
The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.
Contents
Preface; How to read this book; Part I. Microstructure and Empirical Facts: 1. Electronic markets and the limit order book; 2. A primer on the microstructure of financial markets; 3. Empirical and statistical evidence - prices and returns; 4. Empirical and statistical evidence - activity and market quality; Part II. Mathematical Tools: 5. Stochastic optimal control and stopping; Part III. Algorithmic and High-Frequency Trading: 6. Optimal execution with continuous trading I; 7. Optimal execution with continuous trading II; 8. Optimal execution with limit and market orders; 9. Targeting volume; 10. Market making; 11. Pairs trading and statistical arbitrage strategies; 12. Order imbalance; Appendix A. Stochastic calculus for finance; Bibliography; Glossary; Subject index.
