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

By Eshwar Sai Kandimalla, Sravan Chowdary Kankanala, Sumana Bhimineni, Hem Sundhar Korukunda, Vivek Yelleti

Published 2025-07-14

Everscope rating

1320.7

Relevance to quantitative trading

8 / 10

Implementation complexity

8 / 10

Reproducibility

3 / 5

About this paper

Methodology: Bi-Level Chaotic Fusion Graph Convolutional Network (BCF-GCN). Problem types: Time Series Forecasting, Risk Management, Portfolio Optimization, Graph Learning, Uncertainty Quantification.

arXiv:2605.16324 · Paper rankings

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