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Quantitative Trading

Algorithms, Analytics, Data, Models, Optimization

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  • 357 pages
  • 13 hours of reading

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The book delves into algorithmic trading, covering institutions, mechanisms, market microstructure, high-frequency data, and trading strategies. It examines transaction costs, market impact, risk analysis, and management. The second section focuses on market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part addresses electronic market making, liquidity, systemic risk, and recent debates. Key topics include the evolution of trading infrastructure, quantitative strategies, statistical arbitrage, and the interdisciplinary nature of the subject. It discusses data analytics, models, and optimization techniques, along with statistical models for quantitative trading, including multifactor pricing models and Bayesian estimators. The text also explores active portfolio management, sources of alpha, transaction costs, and multiperiod portfolio management strategies. Further, it covers econometrics of transactions on electronic platforms, methods for high-frequency data analysis, and limit order book dynamics. Optimal execution strategies, market making, and smart order routing are also discussed, including control formulations and optimization problems. Finally, the book addresses informatics, regulation, risk management, and martingale theory, providing a comprehensive overview of quantitative trading and market behavior.

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Quantitative Trading, Howard Shek, Tze Leung Lai, Xin Guo

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Released
2016
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(Hardcover)
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