Stochastically Structured Reservoir Computers for Financial and Economic System Identification

Lendy Banegas; Fredy Vides

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arXiv · 2507.17115

Stochastically Structured Reservoir Computers for Financial and Economic System Identification

Lendy Banegas·Fredy Vides

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Abstract

This paper introduces a methodology for identifying and simulating financial and economic systems using stochastically structured reservoir computers (SSRCs). The framework combines structure-preserving embeddings with graph-informed coupling matrices to model inter-agent dynamics while enhancing interpretability. A constrained optimization scheme guarantees compliance with both stochastic and structural constraints. Two empirical case studies, a nonlinear stochastic dynamic model and regional inflation network dynamics, demonstrate the effectiveness of the approach in capturing complex nonlinear patterns and enabling interpretable predictive analysis under uncertainty.

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BibTeX RIS

Lendy Banegas, Fredy Vides. 2025-07-23. Stochastically Structured Reservoir Computers for Financial and Economic System Identification. https://arxiv.org/abs/2507.17115

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