A New GAUSS Software Component for Implementing Dynamic Tests of Contagion with an Application

Paper: arXiv 2610.41740

Authors: Abdulnasser Hatemi-J, Alan Mustafa

Abstract

The main goal of this article is to present a new software component created by the authors in GAUSS for implementing dynamic tests for contagion. These tests are aimed at providing the possibilities of testing for spiller-over effects between financial markets during a crisis or during a pandemic situation such as the one that we experienced recently. Unlike standard tests for contagion that have fixed dates for a potential shift, the tests implemented here are dynamic in the sense that the potential contagion effect is measured across the time span. The leverage bootstrap simulation technique is utilized in order to generate critical values that are reliable when the tests are implemented in order to make sure that the conducted inference is accurate. Since the approach is new, software component needs to be created for conducting the underlying tests, which is accomplished via this article. The module is very easy to implement by the general practitioners via a graphical user interface. An application is offered by using real data from stock markets in order to demonstrate how the software component can be used.

Complexity vs Empirical Score

• Math Complexity: 5.0/10
• Empirical Rigor: 6.0/10
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper presents a novel dynamic contagion test methodology using leverage bootstrap, implemented as a GAUSS software component. It demonstrates empirical application with real stock market data, showing good rigor in its statistical approach and software development focus. The mathematical complexity is moderate, primarily involving OLS and bootstrap techniques.

Research Flowchart

  flowchart TD
    A[Research Goal: Develop GAUSS component for dynamic contagion tests] --> B{Key Methodology: Dynamic Contagion Tests & Leverage Bootstrap Simulation};
    B --> C[Data/Inputs: Financial Market Stock Data];
    C --> D[Computational Process: GAUSS Software Component Development];
    D --> E[Computational Process: Application & Inference with Real Data];
    E --> F[Key Outcome: New GAUSS Software Component for Dynamic Contagion Testing (User-Friendly GUI)];
    F --> G[Key Outcome: Reliable Contagion Inference in Financial Markets (Spillover Effects, Time-Varying)];