A Dynamic Spillover Effect Investigation on Cryptocurrency Market Before and After Pandemic

Paper: arXiv 2412.19983

Authors: Wenjie Lan

Abstract

This paper distinguishes between risk resonance and risk diversification relationships in the cryptocurrency market based on the newly developed asymmetric breakpoint approach, and analyzes the risk propagation mechanism among cryptocurrencies under extreme events. In addition, through the lens of node association and network structure, this paper explores the dynamic evolutionary relationship of cryptocurrency risk association before and after the epidemic. In addition, the driving mechanism of the cryptocurrency risk movement is analyzed in a depth with the epidemic indicators. The findings show that the effect of propagation of risk among cryptocurrencies becomes more significant under the influence of the new crown outbreak. At the same time, the increase in the number of confirmed cases exacerbated the risk spillover effect among cryptocurrencies, while the risk resonance effect that exists between the crude oil market and the cryptocurrency market amplified the extent of the outbreak’s impact on cryptocurrencies. However, other financial markets are relatively independent of the cryptocurrency market. This study proposes a strategy to deal with the spread of cryptocurrency risks from the perspective of a public health crisis, providing a useful reference basis for improving the regulatory mechanism of cryptocurrencies.

Complexity vs Empirical Score

• Math Complexity: 6.5/10
• Empirical Rigor: 6.0/10
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper applies advanced mathematical techniques, specifically combining Conditional Expected Shortfall (CoES) with a non-parametric asymmetric breakpoint approach to analyze tail risk spillover. The empirical design evaluates a dataset of 25 major cryptocurrencies across pre-epidemic and post-epidemic periods using rolling window networks to effectively model dynamic contagion mechanisms.

Research Flowchart

  flowchart TD
    A[Research Goal: Analyze Dynamic Cryptocurrency Risk Spillover & Resonance Before/After Pandemic] --> B[Data Inputs: Crypto Prices, Crude Oil, Financial Markets & COVID-19 Indicators]
    B --> C[Methodology: Asymmetric Breakpoint Approach & Dynamic Network Analysis]
    C --> D[Computational Processes: Measure Risk Propagation, Node Associations & Network Evolution]
    D --> E[Finding 1: COVID-19 Confirmed Cases Exacerbated Crypto Risk Spillover]
    D --> F[Finding 2: Crude Oil Risk Resonance Amplified Pandemic Impact on Cryptos]
    D --> G[Finding 3: Traditional Financial Markets Remained Relatively Independent]