Quantitative Trading: Algorithms, Analytics, Data, Models, Optimization [Paperback]

The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part covers market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part discusses electronic market making, liquidity, systemic risk, recent developments and debates on the subject.

 

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 modl%