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Information flow between asset classes during extreme events

Author

Listed:
  • Almeida, Dora
  • Dionísio, Andreia
  • Ferreira, Paulo
  • Aslam, Faheem
  • Quintino, Derick

Abstract

The interconnectedness between asset classes becomes particularly relevant during extreme events, as market stress amplifies risk spillovers and impacts asset relationships, influencing risk transmission and financial market stability. While existing studies often examine financial interdependencies, including extended periods, they frequently focus on specific markets or asset classes, limiting the understanding of cross-asset contagion effects. Thus, it is crucial to grasp the interconnectedness among asset classes and how they communicate information under different economic conditions. This research bridges the gap by applying the transfer entropy approach to analyze the evolving connections among various asset classes from April 2017 to September 2024, spanning the COVID-19 pandemic and the Russia–Ukraine war. The findings reveal that stocks and cryptocurrencies consistently are net information transmitters to the system. Currency benchmarks and gold tend to receive information from the system during increased tension, reflecting their role in absorbing risk-driven capital flows. This study challenges the idea that cryptocurrencies are separate from traditional financial markets and shows how they are becoming more integrated. By employing net transfer entropy within a financial network analysis framework, this study uncovers time-varying shifts in market interdependencies and, thus, an enhanced description of financial contagion dynamics. The dynamic nature of such relationships highlights the need for adaptive portfolio strategies and enhanced risk assessment models. Our results have direct implications for portfolio management and risk assessment. Investors can use this study’s findings to recognize assets that are sources of systemic risk or safe haven assets, facilitating adaptative changes in their portfolios. Policymakers and regulators can use these findings to forecast systemic vulnerabilities and implement strategies aiming to reduce financial instability in times of crisis.

Suggested Citation

  • Almeida, Dora & Dionísio, Andreia & Ferreira, Paulo & Aslam, Faheem & Quintino, Derick, 2025. "Information flow between asset classes during extreme events," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 671(C).
    • Handle: RePEc:eee:phsmap:v:671:y:2025:i:c:s0378437125003395
    DOI: 10.1016/j.physa.2025.130687
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