Bi-Level Chaotic Fusion Based Graph Convolutional Network for Stock Market Prediction Interval

In three linesPrediction interval method for financial markets combining spatio-temporal graphs and bi-level chaotic fusion. Model with volatility-aware gating mechanism and LUBE objective. Tests on 43 NSE companies (2016-2026): Winkler score 0.0778, coverage 96.6%, significant improvements vs LSTM/GRU/GCN (p<0.001).

Summary generated by Claude — human-verified