QT101,QT201 (no waitlist, no prereq)

QT101 Introductory Lectures in Quantitative Trading

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

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

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