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dc.contributor.authorMikhaylov, Alexey
dc.contributor.authorDinçer, Hasan
dc.contributor.authorYüksel, Serhat
dc.contributor.authorPinter, Gabor
dc.contributor.authorShaikh, Zaffar Ahmed
dc.date.accessioned2023-05-26T12:44:27Z
dc.date.available2023-05-26T12:44:27Z
dc.date.issued2023en_US
dc.identifier.citationMikhaylov, A., Dinçer, H., Yüksel, S., Pinter, G. ve Shaikh, Z. A. (2023). Bitcoin mempool growth and trading volumes: Integrated approach based on QROF Multi-SWARA and aggregation operators. Journal of Innovation and Knowledge, 8(3). https://doi.org/10.1016/j.jik.2023.100378en_US
dc.identifier.issn2530-7614
dc.identifier.issn2444-569X
dc.identifier.urihttps://doi.org/10.1016/j.jik.2023.100378
dc.identifier.urihttps://hdl.handle.net/20.500.12511/10981
dc.description.abstractInvestors are looking for objects in which they invest their funds successfully, evaluating the effectiveness of alternative markets and their instruments. Historically, cash flow indicators most effectively reflected the mood of the masses in relation to any financial asset, both in the short-and long-term. This article examines in detail the queue of already completed, but not confirmed transactions in the bitcoin network. The mempool is able to timely display the growth in the number of transactions awaiting confirmation, which makes it a leading indicator of future cash flows that could affect the trading volumes and market prices of bitcoin. This study evaluates bitcoin mempool priorities and two different analyses have been conducted for this purpose. Firstly, the mempool periods are examined through a statistical analysis. Secondly, the performance determinants of mempool are assessed with q-ROF Multi-SWARA. In addition to q-ROF sets, weights are computed with IFS and PFS. Demonstrated here is that the results of all fuzzy sets are identical. This outcome explains the reliability of the findings and they indicate that a transaction is the most important determinant of the bitcoin mempool. It emerged that the adjusted mempool data (+16.7%) for 7-day and 30-day moving averages was able, with a time lag of 24–48 h, to indicate significant volatility of future bitcoin trading volumes (+1.6%) on average. The obtained values confirm the empirical conclusion reached here that the mempool growth leads to cash flow growth. An increase in future cash flows results in a substantial rise in future trading volumes. The key takeaway from the analysis is that mempool is able to effectively predict future increases in trading volumes based on the prior cash flow growth projected into mempool growth. However, as a price indicator, mempool does show mixed results with mostly uncertainty in the direction of price movement.en_US
dc.language.isoengen_US
dc.publisherElsevier B.V.en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBitcoinen_US
dc.subjectCryptocurrenciesen_US
dc.subjectMempoolen_US
dc.subjectTransactionen_US
dc.titleBitcoin mempool growth and trading volumes: Integrated approach based on QROF Multi-SWARA and aggregation operatorsen_US
dc.typearticleen_US
dc.relation.ispartofJournal of Innovation and Knowledgeen_US
dc.departmentİstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümüen_US
dc.authorid0000-0002-8072-031Xen_US
dc.authorid0000-0002-9858-1266en_US
dc.identifier.volume8en_US
dc.identifier.issue3en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1016/j.jik.2023.100378en_US
dc.institutionauthorDinçer, Hasan
dc.institutionauthorYüksel, Serhat
dc.identifier.wosqualityQ1en_US
dc.identifier.wos001053528000001en_US
dc.identifier.scopus2-s2.0-85159293401en_US
dc.identifier.scopusqualityQ1en_US


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