Essentials in Quantitative Trading (QT*01)
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  • Essentials in Quantitative Trading (QT*01)

Essentials in Quantitative Trading (QT*01)

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Description

Essentials in Quantitative Trading (QT*01)

Essentials in Quantitative Trading (QT*01)

Essentials in Quantitative Trading (QT*01)

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