Publisher's Synopsis
This book offers a comprehensive exploration of pairs trading and statistical arbitrage, emphasizing a rigorous quantitative approach. It systematically presents the core principles of quantitative finance, from foundational topics such as time value of money and portfolio theory to advanced statistical techniques and continuous-time finance. By intertwining theoretical insights with empirical data analysis, the text establishes a robust framework for understanding and applying quantitative trading strategies.
Designed for both academic researchers and industry practitioners, the work delves into the mechanics of identifying, testing, and implementing pairs trading strategies. Detailed discussions on cointegration, error correction models, and signal generation are provided, along with meticulous evaluations of risk management and performance metrics. Each section is supported by mathematical models and real-world examples, ensuring that readers can appreciate the practical relevance of each concept in diverse market environments. The book further explores the evolution of algorithmic trading by integrating elements of machine learning and optimization methods into strategy development. It critically examines challenges such as market inefficiencies, model overfitting, and data integrity, offering systematic approaches to mitigate potential risks. Overall, the text serves as a definitive guide for developing, backtesting, and executing sophisticated quantitative trading systems in today's dynamic financial markets.
