Browsing by Author "Atasoy, Burak Sencer"

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Citation - WoS: 1
Citation - Scopus: 1
Correlation Meets Causality: a Holistic Measure of Financial Contagion
(Academic Press inc Elsevier Science, 2024) Atasoy, Burak Sencer; Ozkan, Brahim
This study introduces a new measure of financial contagion. We argue that a rapid increase in correlations between two series is necessary but not sufficient for contagion to occur, and develop a contagion test that combines dynamic conditional correlations with time-varying Granger causality. We empirically illustrate our new approach using systemic risk data covering the period 1996 - 2023. We show that there are periods when correlations increase rapidly without causality, as well as periods when causality is present but correlations do not increase. The proposed test enables data-driven detection of contagion episodes and provides a clear distinction between interconnectedness and contagion.
Citation - WoS: 5
Citation - Scopus: 6
The Determinants of Systemic Risk Contagion
(Elsevier, 2024) Atasoy, Burak Sencer; Ozkan, Ibrahim; Erden, Lutfi
The elevated interconnectedness of the global financial system has resulted in an increased frequency of financial crises, characterized by the swift transmission of turmoil between countries. This study introduces a novel quantile-connectedness-based contagion metric and investigates the drivers of systemic risk contagion, employing methodologies that address endogeneity and time-variation. We analyze data spanning two decades from 27 international banks and encompassing balance sheet-derived variables. Our findings indicate that contagion during the 2004-2021 period is largely driven by credit risk and leverage, while the impact of size and capital adequacy weakens after 2012. Furthermore, funding structure and profitability only display a significant effect during the 2014-2017 and Covid-19 periods, respectively. We also observe distinct peaks and troughs in each bank's systemic risk propagation, although they share commonalities with their counterparts. Given our findings, we suggest a holistic systemic risk surveillance model that employs high-frequency data and simultaneously incorporates multiple risk factors.