Part 1
Foundation
Reader understands the ML4T workflow, has point-in-time-correct data infrastructure, and 9 case studies set up with proper evaluation protocols.
1
The Process Is Your Edge
- Why Process Discipline Matters
- Introducing the ML4T Workflow
- Causal Inference and Generative AI in the Workflow
- Market Regimes: Change Is the Constant
- In the Real World: Independent vs. Institutional
6 sections
1 notebooks
2
The Financial Data Universe
- A Modern Taxonomy of Financial Data
- The Asset-Class Market Data Landscape
- A Due Diligence Framework for Data Sourcing
- Storing Data
5 sections
16 notebooks
3
Market Microstructure
- Microstructure: The DNA of Price Formation
- The Anatomy of Modern Market Data Feeds
- From Raw Messages to the Limit Order Book
- The Art of Sampling: From Ticks to Bars
- Microstructure Data Quality and Sessionization
6 sections
17 notebooks
4
Fundamental and Alternative Data
- The Point-in-Time Pipeline
- Entity Resolution and Mapping
- Fundamentals Across the Asset-Class Spectrum
- Alternative Data: From Evaluation to Integration
- Case Study: Text Data for NLP Features
6 sections
13 notebooks
5
Synthetic Financial Data
- The Quant's Dilemma
- Classical Simulation Baselines
- Generative Model Taxonomy
- GANs for Financial Time Series
- Diffusion Models for Financial Time Series
8 sections
8 notebooks
6
Strategy Research Framework
- From Idea to Evidence with the ML4T Workflow
- Mapping Strategies and Sources of Edge
- Defining the Rules of the Trading Game
- Setting Objectives and Evaluation Metrics
- Evaluation Protocol for Time Series
8 sections
4 notebooks