Paper: arXiv 2504.06286

Authors: Mario R. Pinheiro, Mario J. Pinheiro

Abstract

The proposed framework introduces a novel multidimensional representation of money using tensor analysis, enabling a more granular examination of economic interactions and capital flow. By treating money as a multidimensional entity, this approach allows for detailed tracking and modeling of sectoral, temporal, and agent-based dynamics. This enhanced perspective facilitates the design of adaptive economic policies that can effectively respond to evolving macroeconomic conditions, ensuring resilience and inclusivity in financial systems. Furthermore, the tensor-based modeling framework bridges traditional economic analyses with advanced computational techniques, offering a robust foundation for algorithmic governance and data-driven decision-making in complex economies.

Complexity vs Empirical Score

  • Math Complexity: 3.5/10
  • Empirical Rigor: 1.5/10
  • Quadrant: Philosophers — conceptual discussion, limited math and data

Why this score: The paper presents an intriguing conceptual metaphor by formulating money as a tensor to capture sectoral, agent, and temporal dimensions. However, it lacks formal mathematical rigor beyond basic tensor notations (outer products) and provides no empirical backtesting or quantitative validation using actual financial datasets.

Research Flowchart

  flowchart TD
    A[Goal: Model Money as a Multidimensional Tensor] --> B[Data Inputs: Sectoral, Temporal & Agent Data]
    B --> C[Methodology: Tensor Analysis Framework]
    C --> D[Computational Modeling: Track Capital Flows & Dynamics]
    D --> E[Outcome: Adaptive Economic Policies]
    D --> F[Outcome: Algorithmic Governance & Decision-Making]

Cited References (50)

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and 42 more
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0 of 50 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.