The research question
Does the text add information beyond price, and was that text genuinely available at the decision time?
A study of text-derived macro information and its potential role as a market feature or risk indicator.
The technical work
Text acquisition, feature extraction, event alignment and comparison with non-text baselines.
The challenge is to connect the economic idea to a precise, reviewable experiment. Data transformations, the moment of a decision and the interpretation of the resulting return series all belong to that specification.
What to challenge
These are evaluation considerations for this domain, not a checklist presented as already passed.
- Publication versus ingestion timestamps
- Model-training leakage
- Missing text and price-only proxy substitutions
- Execution horizon and signal decay
The data boundary
The original dated text stream and a correctly aligned market dataset; not just retrospectively reconstructed headlines.
Descriptions are intentionally high-level. Parameters, execution rules and non-public source data are not published here. Withholding an implementation is different from overstating its evidence.
The interesting question is not whether a backtest looks good. It is what would have to be true for the result to mean something.
For the broader framework, see validation. For the engineering context, see the research stack.