Quantitative Trading Algorithms, Analytics, Data, Models, Optimization

Introduction

Evolution of trading infrastructure

Quantitative strategies and time-scales

Statistical arbitrage and debates about EMH

Quantitative funds, mutual funds, hedge funds

Data, analytics, models, optimization, algorithms

Interdisciplinary nature of the subject and how the book can be used

Supplements and problems

Statistical Models and Methods for Quantitative Trading

Stylized facts on stock price data

Time series of low-frequency returns

Discrete price changes in high-frequency data

Brownian motion at the Paris Exchange and random walk down Wall Street

MPT as a \walking shoe" down Wall Street

Statistical underpinnings of MPT

Multifactor pricing models

Bayes, shrinkage, and Black-Litterman estimators

Bootstrapping and the resampled frontier

A new approach incorporating parameter uncertainty

Solution of the optimization problem

Computation of the optimal weight vector

Bootstrap estimate of performance and NPEB

From random walks to martingales that match stylized facts

From Gaussian to Paretian random walks

Random walks with optional sampling times

From random walks to ARIMA, GARCH

Neo-MPT involving martingale regression models

Incorporating time series e_ects in NPEB

Optimizing information ratios along e_cient frontier

An empirical study of neo-MPT

Statistical arbitrage and strategies beyond EMH

Technical rules and the statistical background

Time series, momentum, and pairs trading strategies

Contrarian strategies, behavioral _nance, and investors' cognitive biases

From value investing to global macro strategies

In-sample and out-of-sample evaluation

Supplements and problems

Active Por