Signal Research

Read these first

1. 01Where Alpha Ideas Come From

   Nobody wakes up with a profitable signal fully formed, real ideas come from a handful of repeatable sources (economic mechanisms, market microstructure, other people's published research, and plain observation of what breaks), and knowing which source you're drawing from tells you how to test the idea.

2. 02Combining Signals

   Once a desk has several signals, the question shifts from 'is each one good' to 'how should they be weighted together', and the honest answer sits between naive equal-weighting and a fully optimized regression, because the optimizer's extra precision is bought with extra noise from a short, overlapping history.

3. 03Incremental Alpha of a New Signal

   A new signal's raw information coefficient is close to meaningless on its own, what matters is how much of its predictive power survives after you control for every signal already in the book, because a signal that duplicates an existing one adds cost and complexity without adding return.

Then the rest

1. 04Alpha Model vs Risk Model Alignment
2. 05Automated Alpha Search
3. 06Conditional and Interaction Signals
4. 07Cross-Sectional Signal Normalization
5. 08Nonlinear Signal Transformations
6. 09Pruning Redundant Signals
7. 10The Break-Even Transaction Cost of a Signal
8. 11The Economic Rationale Behind a Signal
9. 12Turning Information Coefficient Into PnL
10. 13Holding Period and Turnover Optimization
11. 14Signal Health Monitoring