Dynamic Volatility Spillovers Among G20 Economies During the Global Crisis Periods—A TVP VAR Analysis

Previous research on financial contagion has mostly looked at volatility spillovers using static or fixed parameter models. These models don’t always take into account how inter-market links change and depend on frequency during big crises. This study fills in that gap by looking at how changes in volatility in the G20 equity markets affected four big global events: the global financial crisis of 2008, the European debt crisis, the COVID-19 pandemic, and the Russia-Ukraine war. The study uses a Time-Varying Parameter Vector Autoregression (TVP VAR) framework along with the Baruník-Křehlík frequency domain spillover measure to look at how connectedness changes over short-term (1–5 days) and long-term (5–Inf days) time periods. The results show that systemic connectedness changes a lot during crises. For example, the Total Connectedness Index (TCI) was 24–25 percent during the GFC and EDC, 34 percent during COVID-19, and a huge jump to 60 percent during the Russia-Ukraine war. During the global financial crisis and the war between Russia and Ukraine, the US constantly emerged as the largest transmitter. During the European debt crisis, on the other hand, emerging markets like Turkey, South Africa, and Japan acted as net transmitters. During all crisis times, short-term spillovers are the most common. This shows how important high-frequency volatility transmission is. This study is different from others because it uses both time-varying and frequency domain views. This gives us a better idea of how crises change the way global finances are linked. The results are very important for policymakers and investors because they show how important it is to coordinate risk management, improve market safety, and make systemic stress testing better in a global financial world.

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Publication Details

Journal
Econometrics
Published
2025-11-14
DOI
https://doi.org/10.3390/econometrics13040045
Primary Topic
Financial Risk and Volatility Modeling
Type
article
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0.00
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article

Dynamic Volatility Spillovers Among G20 Economies During the Global Crisis Periods—A TVP VAR Analysis

Abdallah Alkhawaja, Himanshu Goel, Suzan Dsouza, Monika Agarwal et al.
Econometrics
Financial Risk and Volatility Modeling
article

Dynamic Volatility Spillovers Among G20 Economies During the Global Crisis Periods—A TVP VAR Analysis

Abdallah Alkhawaja, Himanshu Goel, Suzan Dsouza, Monika Agarwal, Parminder Kaur
article en

Abstract

Previous research on financial contagion has mostly looked at volatility spillovers using static or fixed parameter models. These models don’t always take into account how inter-market links change and depend on frequency during big crises. This study fills in that gap by looking at how changes in volatility in the G20 equity markets affected four big global events: the global financial crisis of 2008, the European debt crisis, the COVID-19 pandemic, and the Russia-Ukraine war. The study uses a Time-Varying Parameter Vector Autoregression (TVP VAR) framework along with the Baruník-Křehlík frequency domain spillover measure to look at how connectedness changes over short-term (1–5 days) and long-term (5–Inf days) time periods. The results show that systemic connectedness changes a lot during crises. For example, the Total Connectedness Index (TCI) was 24–25 percent during the GFC and EDC, 34 percent during COVID-19, and a huge jump to 60 percent during the Russia-Ukraine war. During the global financial crisis and the war between Russia and Ukraine, the US constantly emerged as the largest transmitter. During the European debt crisis, on the other hand, emerging markets like Turkey, South Africa, and Japan acted as net transmitters. During all crisis times, short-term spillovers are the most common. This shows how important high-frequency volatility transmission is. This study is different from others because it uses both time-varying and frequency domain views. This gives us a better idea of how crises change the way global finances are linked. The results are very important for policymakers and investors because they show how important it is to coordinate risk management, improve market safety, and make systemic stress testing better in a global financial world.

EconometricsVol. 13(4)
IMS Unison University (IN), American University of the Middle East (KW)
Openalex Percentile: Top 57%
Financial Risk and Volatility Modeling
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