Quantitative Trading : Algorithms, Analytics, Data, Models, Optimization

Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- List of Figures -- List of Tables -- 1 Introduction -- 1.1 Evolution of trading infrastructure -- 1.2 Quantitative strategies and time-scales -- 1.3 Statistical arbitrage and debates about EMH -- 1.4 Quantitative funds, mutual funds, hedge funds -- 1.5 Data, analytics, models, optimization, algorithms -- 1.6 Interdisciplinary nature of the subject and how the book can be used -- 1.7 Supplements and problems -- 2 Statistical Models and Methods for Quantitative Trading -- 2.1 Stylized facts on stock price data -- 2.1.1 Time series of low-frequency returns -- 2.1.2 Discrete price changes in high-frequency data -- 2.2 Brownian motion models for speculative prices -- 2.3 MPT as a "walking shoe" down Wall Street -- 2.4 Statistical underpinnings of MPT -- 2.4.1 Multifactor pricing models -- 2.4.2 Bayes, shrinkage, and Black-Litterman estimators -- 2.4.3 Bootstrapping and the resampled frontier -- 2.5 A new approach incorporating parameter uncertainty -- 2.5.1 Solution of the optimization problem -- 2.5.2 Computation of the optimal weight vector -- 2.5.3 Bootstrap estimate of performance and NPEB -- 2.6 From random walks to martingales that match stylized facts -- 2.6.1 From Gaussian to Paretian random walks -- 2.6.2 Random walks with optional sampling times -- 2.6.3 From random walks to ARIMA, GARCH -- 2.7 Neo-MPT involving martingale regression models -- 2.7.1 Incorporating time series effects in NPEB -- 2.7.2 Optimizing information ratios along efficient frontier -- 2.7.3 An empirical study of neo-MPT -- 2.8 Statistical arbitrage and strategies beyond EMH -- 2.8.1 Technical rules and the statistical background -- 2.8.2 Time series, momentum, and pairs trading strategies -- 2.8.3 Contrarian strategies, behavioral finance, and investors' cognitive biases