{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T08:13:41Z","timestamp":1747210421965,"version":"3.40.5"},"reference-count":21,"publisher":"RGSA- Revista de Gestao Social e Ambiental","issue":"3","license":[{"start":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T00:00:00Z","timestamp":1716163200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["RGSA"],"abstract":"<jats:p>Background: The global economy faced increased instability due to the simultaneous occurrence of two major events, the global pandemic in 2020 and the Russian-Ukrainian conflict in 2022, which impacted the financial markets.\n\u00a0\nPurpose: This paper aimed to evaluate the comovements between the USA (S&amp;P 500), Germany (DAX 30), France (CAC40), Japan (Nikkei 225), Canada (TSX), Russia (MOEX) and Ukraine (PFTS) stock markets and the cryptocurrencies Bitcoin (BTC), Ethereum (ETH), Litcoin (LTC) Dash (DASH\/USD), Ripple (XRP) DigiByte (DGB) and Nem (XEM), from February 24, 2022, to April 12, 2023\n\u00a0\nMethods: The approach to our research question will involve using the causality econometric model, Granger SVAR (Vector Autoregressive).\n\u00a0\nResults: The results showed that stock indices and digital currencies show sharp structural breaks, and not all markets influence cryptocurrencies. The MOEX stock market affects the price formation of BTC, ETH, DGB, XEM, and XRP, while the DAX 30 stock index impacts ETH, LTC, DASH, DGB, and XEM. The Ukraine market (PFTS) influences ETH, but the other stock markets do not influence any of the cryptocurrencies analysed.\n\u00a0\nConclusion: Investors, policymakers, and other participants operating in the digital currency markets can find valuable information in the study's conclusions when seeking to rebalance their portfolios.<\/jats:p>","DOI":"10.24857\/rgsa.v18n3-108","type":"journal-article","created":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T20:24:50Z","timestamp":1716236690000},"page":"e06546","source":"Crossref","is-referenced-by-count":0,"title":["Analysing the Nexus: Stock Indices and Cryptocurrencies During the Conflict Between Russia and Ukraine"],"prefix":"10.24857","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6138-3098","authenticated-orcid":false,"given":"Rui","family":"Dias","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9444-3333","authenticated-orcid":false,"given":"Mariana","family":"Chambino","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8282-6604","authenticated-orcid":false,"given":"Rosali","family":"Galv\u00e3o","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1781-7036","authenticated-orcid":false,"given":"Paulo","family":"Alexandre","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8388-1250","authenticated-orcid":false,"given":"Miguel","family":"Varela","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4956-1170","authenticated-orcid":false,"given":"Mohammad","family":"Irfan","sequence":"additional","affiliation":[]}],"member":"10484","published-online":{"date-parts":[[2024,5,20]]},"reference":[{"key":"134148","doi-asserted-by":"crossref","unstructured":"Ahmed, S., Hasan, M. M., & Kamal, M. R. (2022). Russia\u2013Ukraine crisis: The effects on the European stock market. European Financial Management. https:\/\/doi.org\/10.1111\/eufm.","DOI":"10.1111\/eufm.12386"},{"key":"134149","doi-asserted-by":"crossref","unstructured":"Appiah-Otoo, I. (2023). The Impact of the Russia-Ukraine War on the Cryptocurrency Market. Asian Economics Letters, 4(1). https:\/\/doi.org\/10.46557\/001c.53110","DOI":"10.46557\/001c.53110"},{"key":"134150","doi-asserted-by":"crossref","unstructured":"Breitung, J. (2000). The local power of some unit root tests for panel data. Advances in Econometrics. https:\/\/doi.org\/10.1016\/S0731-9053(00)15006-6","DOI":"10.1016\/S0731-9053(00)15006-6"},{"key":"134151","doi-asserted-by":"crossref","unstructured":"Chambino, M., Manuel, R., Dias, T., & Horta, N. R. (2023). 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