Halls-Moore M. Advanced Algorithmic Trading: Bayesian Statistics, Time Series Analysis and Machine Learning for Profitable Trading Strategies

New York: QuantStart, 2017. — 504 p.Introduction
Introduction To Advanced Algorithmic Trading
Bayesian Statistics
Introduction to Bayesian Statistics
Bayesian Inference of a Binomial Proportion
Markov Chain Monte Carlo
Bayesian Linear Regression
Bayesian Stochastic Volatility Model
Time Series Analysis
Introduction to Time Series Analysis
Serial Correlation
Random Walks and White Noise Models
Autoregressive Moving Average Models
Autoregressive Integrated Moving Average and Conditional Heteroskedastic Models
Cointegrated Time Series
State Space Models and the Kalman Filter
Hidden Markov Models
Statistical Machine Learning
Introduction to Machine Learning
Supervised Learning
Linear Regression
Tree-Based Methods
Support Vector Machines
Model Selection and Cross-Validation
Unsupervised Learning
Clustering Methods
Natural Language Processing
Quantitative Trading Techniques
Introduction to QSTrader
Introductory Portfolio Strategies
ARIMA+GARCH Trading Strategy on Stock Market Indexes Using R
Cointegration-Based Pairs Trading using QSTrader
Kalman Filter-Based Pairs Trading using QSTrader
Supervised Learning for Intraday Returns Prediction using QSTrader
Sentiment Analysis via Sentdex Vendor Sentiment Data with QSTrader
Market Regime Detection with Hidden Markov Models using QSTrader
Strategy Decay