sentiment-analysis

Market sentiment is quantified across multiple data sources into a composite 0-100 score, providing tiered position guidance and narrative interpretations for actionable trading signals.

A multi-dimension sentiment framework combines Fear & Greed indices, Put-Call Ratio, financing signals, northbound funds, and social media mood to assess overall market sentiment.

Yes, sentiment analysis is applicable to crypto, equities, and other financial markets, supporting scenarios like detecting fear/greed shifts, options sentiment, leverage signals, and cross-border capital flows.

Portfolio risk assessment uses a five-dimension sentiment framework to report a composite score with current values, percentile context, and suggested positions for risk management and hedging.

Yes, the modular workflow requires clearly defined indicator data as inputs to generate outputs including scores, signals, and narrative interpretation through an auditable process.

The composite sentiment score provides entry and exit timing guidance and percentile context, but relies on available indicator data across its five dimensions for accurate signal generation.