Analisis cuantitativo de riesgos utilizando "MCSimulRisk" como herramienta didactica

Paper: arXiv 2405.20688

Authors: Fernando Acebes, David Curto, Juan de Anton, Felix Villafanez

Abstract

Risk management is a fundamental discipline in project management, which includes, among others, quantitative risk analysis. Throughout several years of teaching, we have observed difficulties in students performing Monte Carlo Simulation within the quantitative analysis of risks. This article aims to present MCSimulRisk as a teaching tool that allows students to perform Monte Carlo simulation and apply it to projects of any complexity simply and intuitively. This tool allows for incorporating any uncertainty identified in the project into the model.

Complexity vs Empirical Score

• Math Complexity: 2.5/10
• Empirical Rigor: 3.0/10
• Quadrant: Philosophers — conceptual discussion, limited math and data

Why this score: This paper presents ‘MCSimulRisk’, a MATLAB-based educational tool designed to help students run Monte Carlo simulations for project risk management without getting bogged down by Excel programming. While clear and well-structured for pedagogical purposes, the paper lacks advanced mathematical formulation, novel quantitative methodology, or rigorous quantitative empirical validation.

Research Flowchart

  flowchart TD
    A["Research Goal:<br>Simplify Monte Carlo Simulation teaching & application using MCSimulRisk"] --> B["Identify Project Risks & Uncertainties"]
    B --> C["Input Data into MCSimulRisk:<br>Schedule, Cost & Probability Distributions"]
    C --> D["Execute Quantitative Analysis:<br>Monte Carlo Simulation"]
    D --> E["Analyze Simulation Outputs:<br>Risk Exposure & Probability Curves"]
    E --> F["Key Outcome:<br>Intuitive student learning & risk analysis for projects of any complexity"]