The Bayesian approach to measuring financial contagion
The Bayesian approach to measuring financial contagion

Summary/Abstract: This paper investigates financial contagion between the US and emerging European markets during recent turbulent periods, including the COVID-19 pandemic, the Russia-Ukraine war, the US presidential election, and changes in US tariff policy in 2025. The S&P 500 and STOXX Europe 50 indices are employed to capture global and regional factors affecting emerging markets in Europe. Using daily returns from January 2013 to April 2025, I conduct a structural break test and endogenously determine the start date of the COVID-19 pandemic. This approach avoids the arbitrary selection of crisis dates, allowing event timings and their market impact to be determined empirically. The paper then estimates returns models for individual emerging markets using the Bayesian approach. The results indicate that emerging countries' stock markets are more affected by regional factors than the US market. Moreover, there is a significant increase in the influence of the STOXX Europe 50 on emerging markets during periods of turmoil. Finally, the paper evaluates whether there is contagion across markets based on Bayesian estimation in the dynamic conditional correlation DCC model. To account for the heavy tails associated with financial returns, this paper assumes that the corresponding error terms follow a skewed Student's t-distributions. The findings also confirm stronger evidence of contagion from regional factors to the examined emerging markets during the episodes of market turmoil. Additionally, the results indicate interdependence, but no contagion, from the US market to emerging European markets.

• Details
• Contents