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 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.