Modeling COVID-19 pandemic with financial markets models: The case of Jaén (Spain)

Paper: arXiv 2301.08803

Authors: Julio Guerrero, Maria del Carmen Galiano, Giuseppe Orlando

Abstract

The main objective of this work is to test whether some stochastic models typically used in financial markets could be applied to the COVID-19 pandemic. To this end we have implemented the ARIMAX and Cox-Ingersoll-Ross (CIR) models originally designed for interest rate pricing but transformed by us into a forecasting tool. For the latter, which we denoted CIR*, both the Euler-Maruyama method and the Milstein method were used. Forecasts obtained with the maximum likelihood method have been validated with 95% confidence intervals and with statistical measures of goodness of fit, such as the root mean square error (RMSE). We demonstrate that the accuracy of the obtained results is consistent with the observations and sufficiently accurate to the point that the proposed CIR* framework could be considered a valid alternative to the classical ARIMAX for modelling pandemics.

Complexity vs Empirical Score

• Math Complexity: 5.5/10
• Empirical Rigor: 6.0/10
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper presents a novel interdisciplinary application by adapting financial stochastic models (Cox-Ingersoll-Ross and ARIMAX) to epidemiological forecasting. It features solid mathematical foundations using SDE discretization methods (Euler-Maruyama, Milstein) alongside reasonable empirical validation via standard error metrics (RMSE) and confidence intervals on local COVID-19 data.

Research Flowchart

  flowchart TD
    A[Goal: Adapt Financial Models to Forecast COVID-19 in Jaén] --> B[Input Data: Local COVID-19 Pandemic Time Series]
    
    B --> C[Apply Methodology & Models]
    
    subgraph Methodology [Financial Models Adaptation]
        C --> D[ARIMAX Standard Baseline]
        C --> E[CIR* Model via Euler-Maruyama & Milstein Methods]
    End
    
    D & E --> F[Parameter Estimation & Validation<br/>Maximum Likelihood, RMSE & 95% Confidence Intervals]
    
    F --> G[Outcome: CIR* is a Valid, Accurate Alternative to ARIMAX for Pandemic Forecasting]