Important insights to keep in mind as you proceed to the practice of ML for trading include:
- Data is the single most important ingredient
- Domain expertise helps realize the potential value in the data, especially in finance
- ML offers tools for many use cases that should be further developed and combined to create solutions for new problems using data
- The choice of model objectives and performance diagnostics are key to productive iterations towards an optimal system
- Backtest overfitting is a huge challenge that requires significant attention
- Transparency around black-box models can help build confidence and facilitate adoption
We will elaborate a bit more on each of these ideas.
