sentiment-analysis

You can quantify market sentiment by building a composite score from fear and greed proxies, options positioning, leverage data, foreign flows, and social media sentiment. This approach normalizes each component to a comparable scale to map sentiment levels into actionable risk guidance.

The put-call ratio works as a contrarian indicator by defining specific PCR ranges to identify overheating or panic conditions. By tracking options positioning across equities and crypto, extreme readings signal potential market reversals for risk management.

Yes, the sentiment analysis framework applies to A-shares by interpreting alternative fear and greed sets, financing and short-selling dynamics, and northbound fund behavior to identify localized overheating versus panic conditions.

The best way to convert social media sentiment into actionable signals is to quantify discussion into heat, sentiment tendency, strength, and change-cycle metrics. This requires applying anti-noise considerations to filter market chatter before integrating it into a composite score.

You map a composite sentiment score to portfolio positioning by applying a consistent scoring model with defined thresholds per market. This translates integrated sentiment levels into suggested positioning ranges, including inverse usage for contrarian strategies.

You should not rely solely on northbound funds and financing data when the market lacks sufficient leverage activity or foreign flow volume. These leverage and flow signals must be normalized alongside options and social sentiment to avoid skewed contrarian interpretations.