{"as_of":"2026-10-21T06:24:15.855482+00:00","window_days":7,"overall":49.0,"overall_label":"Neutral","categories":{"crypto":{"score":49.3,"label":"Neutral","tickers_with_data":4,"tickers_total":5,"headlines":264},"fx":{"score":47.8,"label":"Neutral","tickers_with_data":7,"tickers_total":7,"headlines":102},"equity":{"score":52.2,"label":"Neutral","tickers_with_data":20,"tickers_total":20,"headlines":3274},"etf":{"score":39.9,"label":"Fear","tickers_with_data":5,"tickers_total":6,"headlines":174},"commodity":{"score":55.6,"label":"Greed","tickers_with_data":4,"tickers_total":4,"headlines":748}},"methodology":"Built from real financial news headlines scored by FinBERT (a financial-domain NLP model) -- not trader positioning, order flow, or social-media chatter. Reddit, StockTwits and X posts are excluded. Score per ticker = mean sentiment over the trailing 7 days. Category score = equal-weighted mean across that category's tickers (headline volume doesn't skew it). Overall = equal-weighted mean across the 5 asset classes, so equities' 20 tickers can't dominate a number meant to represent all of them. Scale: 0 = extreme fear, 50 = neutral, 100 = extreme greed."}