RicciFlowRec: A Geometric Root Cause Recommender Using Ricci Curvature on Financial Graphs

TL;DR

RicciFlowRec is a novel geometric recommendation framework that uses Ricci curvature and flow on financial graphs to improve risk attribution and interpretability in financial decision-making.

Contribution

It introduces the first application of Ricci curvature and flow for root cause attribution and risk-aware ranking in financial graphs, enhancing robustness and interpretability.

Findings

Improved robustness under synthetic perturbations

Enhanced interpretability of causal substructures

Preliminary success on S&P 500 data with sentiment analysis

Abstract

We propose RicciFlowRec, a geometric recommendation framework that performs root cause attribution via Ricci curvature and flow on dynamic financial graphs. By modelling evolving interactions among stocks, macroeconomic indicators, and news, we quantify local stress using discrete Ricci curvature and trace shock propagation via Ricci flow. Curvature gradients reveal causal substructures, informing a structural risk-aware ranking function. Preliminary results on S\&P~500 data with FinBERT-based sentiment show improved robustness and interpretability under synthetic perturbations. This ongoing work supports curvature-based attribution and early-stage risk-aware ranking, with plans for portfolio optimization and return forecasting. To our knowledge, RicciFlowRec is the first recommender to apply geometric flow-based reasoning in financial decision support.