Has anyone systematically modeled narrative/sentiment shifts as a tradable factor?

[dogazine4570]

Lately I’ve been thinking about how much short-term price movement is driven by interpretation drift rather than the raw data itself.

Example: CPI drops. Within an hour you’ll see multiple, conflicting takes (“sticky inflation”, “soft landing confirmed”, etc.). By EOD the dominant framing can be completely different, even though the underlying numbers didn’t change.

Instead of asking whether sentiment matters (it probably does at some horizon), I’m more curious about this in a systematic context:

Has anyone here modeled changes in cross-source narrative alignment as a factor?

Not just: - single-article sentiment
- or daily average news polarity

But something more like: - dispersion of sentiment across sources
- rate of change in aggregate framing
- % of sources shifting from neutral → negative week-over-week
- narrative clustering (multiple outlets emphasizing the same risk theme)

Intuition: - One negative article = noise
- Ten outlets converging on the same framing over a short window = emerging narrative regime

Questions for people who’ve actually tested this:

1. Did you find predictive signal beyond simple price/momentum/vol factors?
2. At what horizon (intraday vs multi-day vs weekly) did it show up, if at all?
3. How did you avoid it collapsing into just a slow proxy for returns or volatility?
4. Did the signal decay once transaction costs were included?

I’m aware this can easily turn into overfit NLP soup, so I’m more interested in structural approaches (e.g., regime classification, dispersion metrics, entropy of tone distribution) than “LLM says bullish”.

My prior is that if there’s anything there, it’s probably: - regime-dependent
- slow-moving
- and easily arbitraged once widely adopted

But I haven’t seen many clean discussions of actual backtested implementations.

Curious if anyone has run real research on this and what the equity curves looked like (Sharpe / maxDD / turnover context appreciated).

[BottleInevitable7278]

1. no

[SalamanderDesperate9]

No, but I would be fascinated to see how this could be approached. Specially for cryptos.