QT401: Applied Alpha Research and Quantitative Trading

Course curriculum

New Chapter
DISCLAIMER
Introduction to QT401
Artificial Intelligence is Search
Genetic Programs as Intelligent Systems
GP Iterations
Specifying the Primitive Set
Ephemeral Constant Generation
Brute Force Numerical Trees
Brute Force Boolean Trees
Simulating the Brute Force Alphas
Genetic Operators
Crossover Implementation
Mutation Implementation
GP Implementation Overview
Warm Start Initialization
Elitism
NaN Proof Marginal Significance
Evolution; Recombination
Evolution; Mutation
Simulation Walkthrough
Multi Objective Optimization
k-Pareto Optimality Measure
GP Bloat, Kruskal Wallis and Conover Iman tests
Covariant Parsimony Pressure
Verifying the Parsimony Coefficients
Adding Proprietary Datasets
Advanced GP Extensions
Support and Bug Fix Lecture

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