About Course:
Access to QT101,QT201,QT301,QT401 lectures without waiting list or certificate of completion in prerequisites.
QT101 Introductory Lectures in Quantitative Trading
Course curriculum
- DISCLAIMER
- Introducing QT101 – Who Should be Interested?
- Retrieving OHLCV with the yfinance API
- Python Multithreading
- Python Object Pickling
- Implementing a Random Alpha Unit
- Implementing Alpha Unit 1
- Implementing Alpha Unit 2
- Implementing Alpha Unit 3
- Objected Oriented Programming and Implementing a Generic Alpha Unit
- Adapting the Code to the Generic Alpha Unit
- Relative Position Sizing – Instrument Volatility Targeting
- Absolute Position Sizing – Strategy Volatility Targeting
- Implementing the Portfolio
- Git for Version Tracking and Python Decorators
- Function Profiling
- Line Profiling
- Vectorization and Memory Locality
- Handling Non-Linearity with Vectorization
- Python Generators
- Vectorization of the Alpha Library
- Bit Masking and Manipulation
- Type Compatibility
- Alpha Units Refactorization
- Wrapping Up
- Support Lecture (Common Issues and Bug Fixes)
QT201: Statistical Methods in Quantitative Trading
Course curriculum
- DISCLAIMER
- Course Introduction
- Foundational Concepts
- Economics of Multiple Assets
- Portfolio Metrics
- Implementation of the Portfolio Metrics
- Implementation of the Portfolio Metrics
- Basics of Hypothesis Testing
- t-tests and sign tests for portfolio return mean/median
- Confidence Intervals and Signed Rank test
- Permutation of Price Data
- Permutation of OHLCV Bars
- Adjustments for Dynamic Universe of Assets
- Data Shuffle Implementation
- Introduction to the Monte Carlo Permutation Test
- Overfit Detection, Asset Timing and Asset Picking, Skill Hypothesis Tests
- Implementation of Non-Permutation Based Hypothesis Tests
- Decision Shuffling
- Decision Shuffling
- Implementation and Computation of the p-values
- Multiple Hypothesis Testing with FER Control
- Implementation of the Marginal Family Tests
QT301: Modern Techniques in Quantitative Trading
Course curriculum
- DISCLAIMER
- Introducing QT301
- Alpha Modelling
- Machine Encoding and Recursion
- Alpha String Parser
- Alpha String Deparsing
- Alpha Visualization
- Graph Traversal Algorithms
- Post-Order No-Code Evaluator
- Indexing for Dynamic Data
- Behavioural Polymorphism and Union Indexing Implementation
- Implementation of Further Primitives
- Time-Series Operations
- More Time Series Implementations
- Signal Transformations and Cross Sectional Operations
- Our First No-Code Backtest
- Branching and Specialised Logic
- Modelling Considerations
- Encoding our Alpha Set
- Compound Functions and Syntactic Sugar
- Computations with Alternative Data
- Support Lecture (Common Issues and Bug Fixes) set15
QT401: Applied Alpha Research and Quantitative Trading
Course curriculum
- 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