sentiment-analysis

You can normalize multiple sentiment indicators into a combined 0-100 scale to generate a single trading signal. This approach converts fragmented emotional cues like crypto fear-greed scores and A-share put-call ratios into coherent, quantified position sizing guidance.

Market sentiment analysis quantifies emotional extremes like fear and greed into normalized scores. By tracking leverage and fund-flow thresholds, it delivers actionable positioning guidance to help traders align their position sizing with broader sentiment cycles and avoid emotional overreactions.

Tracking northbound capital flows and margin financing trends involves monitoring balance changes against sentiment gauges. Comparing these fund flows with fear-greed indexes reveals hidden extremes, confirming whether greed is peaking or fear is subsiding before initiating fresh exposure.

Social media sentiment integrates with traditional market indicators by normalizing social heat into the same 0-100 scale. Systematic traders combine this social sentiment with put-call ratios and northbound flows to verify broader market sentiment cycles before adjusting allocations.

You should not rely on sentiment analysis alone when fund-flow thresholds and leverage indicators diverge from social sentiment. Avoid scaling in if the combined fear-greed gauge and northbound inflows do not confirm whether greed is peaking or fear is subsiding.