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Full Description
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.
Contents
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
