Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/304154 
Year of Publication: 
2023
Citation: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 11 [Issue:] 2 [Article No.:] 2241205 [Year:] 2023 [Pages:] 1-33
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
The Russia-Ukraine military conflict, commencing on February 24, 2022, notably impacted the international community. This study aims to quantify the volatility engendered by the conflict, drawing from the analysis of stock market indices across 40 countries. Time-series returns data from January 1 to December 31, 2022, were examined utilizing EGARCH econometric models. The relationship between volatility and news regarding the conflict was analyzed through a vector autoregression model, and associations between variables were examined using the Granger causality test. Findings suggest that some markets proximate to Ukraine, notably in Hungary, Polassnd Poland, Serbia, Bosnia and Herzegovina, and the Czech Republic, reacted in anticipation of the conflict, days prior to February 24. Remote markets experienced comparatively lower volatility, along with the primary stock markets. Additionally, a decline in volatility was observed as war-related information became available. Notably, the period between March 2 and March 16, 2022, recorded the highest volatility in 21 countries. Conversely, the value markets of the US, China, Japan, the UK, and Germany navigated the analyzed period with lower volatilities. These results demonstrate that conflict shocks influence stock markets globally. The implications of these findings are significant for investors, decision-makers, portfolio managers, investment funds, and central banks.
Subjects: 
asymmetric effect
EGARCH
Granger
Russia-Ukraine war
vector autoregression model
volatility
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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