sentiment-analysis

You can convert market sentiment indicators into quantitative signals by aggregating fear-and-greed, put-call ratio, and social media data into normalized composite scores. This provides position sizing guidance and hedging suggestions for data-driven trading decisions.

Aggregating fear-and-greed and put-call ratio data involves normalizing them alongside margin financing balances and northbound flows into composite scores. This generates a weekly dashboard flagging extreme market regimes and informing allocation shifts.

This sentiment analysis approach supports A-share, crypto, and US equity markets by applying market-specific thresholds and interpretation guidance to normalized indicators. It generates tailored composite scores and actionable position guidance across asset classes.

Social media sentiment and northbound flows can be integrated into composite sentiment scores for portfolio risk monitoring. This flags extreme market emotions and produces hedging suggestions, such as option hedges, to manage risk during volatile regimes.

To generate position sizing guidance from margin financing balances, normalize them into composite sentiment scores alongside fear-and-greed and social media metrics. This produces actionable allocation guidance and hedging suggestions for trading decisions.