Sentiment analysis

Measuring market mood from text and flows — news, social, surveys; contextual signal, not an oracle.

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Who this is for — Traders blending fundamentals, technicals or quant with market «tone» — headlines, social, analyst notes. Useful as filter and confirmation, fragile alone.

Sentiment analysis quantifies attitude (positive, negative, neutral) toward assets, sectors or macro from textual and behavioural sources — news, earnings calls, Twitter/X, Reddit, AAII surveys, extreme positioning as euphoria/fear proxy.

In plain terms — Gauge whether the market is scared or euphoric — often a contrarian at extremes, moderately useful in the middle.


Sources and methods

Source Method Limit
News / wire Lag, duplicates, clickbait
Social Volume + polarity Bots, manipulation
Surveys % bullish/bearish Small sample
Market VIX, put/call, extreme funding Not text, but «price sentiment»

Sentiment combines with market regime and herding: persistent extremes often precede mean-reversion or final melt-up.


Operational use

  • Confirmation: technical setup aligned with non-extreme sentiment
  • Contrarian: record euphoria + price divergence → caution on longs
  • Risk-off: panic + thin liquidity — watch gaps and slippage
  • ML: feature in pipeline with lags and data leakage control

Common mistake — Trading real-time sentiment without news lag — price often already discounted the headline.

Example — Crypto fear & greed at 90 (extreme greed) + elevated BTC-PERP funding → reduce long size despite uptrend.

Summary card

  • Role: context and filter, rarely sole trigger.
  • Quality: source, timestamp, deduplication.
  • Hub: AI & markets.