Strategy #0000000107 · Financial text and event signals
Negative tone in financial news
Enter negative-word share, threshold, basket returns and costs to inspect the activated assumed spread.
Tetlock and later research use news-column or corporate-text tone as proxies for sentiment and information response. General dictionaries can misclassify neutral financial terms as negative, motivating finance-specific Loughran–McDonald word lists. A model may use dictionaries, FinBERT or other NLP, but classification quality and text provenance need separate validation.
No full-text news, lexicon or NLP model is connected; stale republications, context and source reliability are not modelled.
Three ways in
Understand the story. Then inspect the risk.
Start with a familiar situation, check the payoff, then test how the numbers change.
The idea · in two minutes
When negative-word share crosses a threshold, what is the supplied event-spread scenario?
Tetlock and later research use news-column or corporate-text tone as proxies for sentiment and information response. General dictionaries can misclassify neutral financial terms as negative, motivating finance-specific Loughran–McDonald word lists. A model may use dictionaries, FinBERT or other NLP, but classification quality and text provenance need separate validation.
Enter negative-word share, threshold, basket returns and costs to inspect the activated assumed spread.
No full-text news, lexicon or NLP model is connected; stale republications, context and source reliability are not modelled.
- Input assumptionsEnter negative-word share, threshold, basket returns and costs to inspect the activated assumed spread.
- Model outputNo full-text news, lexicon or NLP model is connected; stale republications, context and source reliability are not modelled.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
NegativeShare=\frac{N_{negative}}{N_{words}},\quad Signal=I(NegativeShare\geq\tau)
The simulator does not analyse text; negative-word share and basket returns are manual inputs.
Greeks: the directional intuition
- 訊號
- Measures sensitivity to implied volatility.
- 資料
- Measures sensitivity to implied volatility.
- 執行
- Measures sensitivity to implied volatility.
NegativeShare=\frac{N_{negative}}{N_{words}},\quad Signal=I(NegativeShare\geq\tau)
Practical context · published observations
Negative tone in financial news: read the record with its caveats.
The chart uses the published figures or explicitly labelled study inputs below. A historical index or model replay is not the same as an investor’s realised account return.
No full-text news, lexicon or NLP model is connected; stale republications, context and source reliability are not modelled. Source ↗ · Methodology ↗
Change assumptions and inspect the scenario
Inputs illustrate the strategy mechanics; they are not live quotes, forecasts or investment advice.
Variants · same family, different risk levers
Data proxies, holding periods and portfolio construction affect signal interpretation.
Compare measurement and implementation assumptions.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Base scenario | Manual inputs | Tetlock and later research use news-column or corporate-text tone as proxies for sentiment and information response. General dictionaries can misclassify neutral financial terms as negative, motivating finance-specific Loughran–McDonald word lists. A model may use dictionaries, FinBERT or other NLP, but classification quality and text provenance need separate validation. | No full-text news, lexicon or NLP model is connected; stale republications, context and source reliability are not modelled. |
| Conservative version | Higher threshold | Raise signal/sample thresholds and reduce exposure. | May reduce eligible names. |
| Validation version | Out-of-sample review | Freeze definitions before time-ordered evaluation. | Needs clean, representative data. |
No full-text news, lexicon or NLP model is connected; stale republications, context and source reliability are not modelled.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.