Paper: arXiv 2502.02125

Authors: Emanuele Dri, Achille Yomi, Muthumanimaran Vetrivelan, Cedric Kuassivi, Ivàn Diego Exposito

Abstract

In this paper, we present an approach for estimating significant financial metrics within risk management by utilizing quantum phenomena for random number generation. We explore Quantum-Enhanced Monte Carlo, a method that combines traditional and quantum techniques for enhanced precision through Quantum Random Numbers Generation (QRNG). The proposed methods can be based on the use of photonic phenomena or quantum processing units to generate random numbers. The results are promising, hinting at improved accuracy with the proposed methods and slightly lower estimates (both for VaR and CVaR estimation) using the quantum-based methodology.

Complexity vs Empirical Score

  • Math Complexity: 3.0/10
  • Empirical Rigor: 4.0/10
  • Quadrant: Philosophers — conceptual discussion, limited math and data

Why this score: The paper presents a standard introduction of Quantum Random Number Generation (QRNG) applied to basic Monte Carlo risk calculations (VaR/CVaR), using elementary textbook mathematics. The empirical testing is limited, relying heavily on third-party APIs (ANU) and commercial platforms (Scenario X) without offering deep statistical backtesting or true Quantum Amplitude Estimation speedups.

Research Flowchart

  flowchart TD
    A[Goal: Enhance Financial Risk Estimation<br>VaR & CVaR via QRNG] --> B[Input Data: Multi-Asset Financial Portfolios]
    B --> C[QRNG Source Selection:<br>Photonic Phenomena or QPUs]
    C --> D[Quantum-Enhanced Monte Carlo<br>QEMC Simulation]
    D --> E[Outcome: Higher Precision &<br>Slightly Lower Risk Estimates]

Cited References (6)

  1. Credit Risk Management (2008) — link
  2. Monte Carlo Methods for Value-at-Risk and Conditional Value-at-Risk: A Review (2014) — link
  3. A fast and compact quantum random number generator (2000) — link
  4. Quantum random number generation (2016) — link
  5. ANU QRNG – Quantum random numbers — link
  6. IBM Quantum — link

0 of 6 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.