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Quantiles dependence and dynamic connectedness between distributed ledger technology and sectoral stocks: enhancing the supply chain and investment decisions with digital platforms

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Abstract

Distributed Ledger Technology (DLT) is highly applicable in various fields, especially the supply chain in many sectors. Against limited empirical evidence, this paper analyzes the relations between the Kensho Distributed Ledger Technology Index and stock indices of 12 sectors, including communication services, consumer discretionary, consumer staples, energy, health care, financials, industrials, information technology, materials, utilities, and real estate, and ESG by employing the quantile coherency and dynamic connectedness techniques. Our results reveal that the quantile coherency between the DLT stock index and the sectoral stock indices in almost all cases is significant and positive. The positive co-movement tends to be stronger in the longer terms and as we move from the lower to the higher quantiles, implying that they are more strongly connected in the long term and during the bearish market condition. Moreover, the dynamic connectedness indicates that the DLT stocks and the sectoral stocks are highly connected, with the former being a net transmitter of spillover shocks. The spillovers are also time-varying, and the results significantly corroborate those of the quantiles coherency methods. Among other relevant implications, DLT can be an important factor in the development and enhancement of these sectors.

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Notes

  1. Contribution to others.

  2. NET directional connectedness.

References

  • Adekoya, O. B., & Oliyide, J. A. (2021). How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques. Resources Policy, 70, 101898.

    Google Scholar 

  • Adekoya, O.B., Oliyide, J.A., & Noman, A. (2021). The volatility connectedness of the EU carbon market with commodity and financial markets in time- and frequency-domain: The role of the U.S. economic policy uncertainty. Resources Policy, 74, 102252.

  • Adekoya, O. B., Oliyide, J. A., Saleem, O., & Adeoye, H. A. (2022a). Asymmetric connectedness between Google-based investor attention and the fourth industrial revolution assets: The case of FinTech and Robotics & Artificial Intelligence stocks. Technology in Society, 68, 101925.

    Google Scholar 

  • Adekoya, O. B., Oliyide, J. A., & Tiwari, A. K. (2022b). Risk transmissions between sectoral Islamic and conventional stock markets during COVID-19 pandemic: What matters more between actual COVID-19 occurrence and speculative and sensitive factors? Borsa Istanbul Review, 22, 363–376.

    Google Scholar 

  • Anderson, J. (2018). Securing, standardizing, and simplifying electronic health record audit logs through permissioned blockchain technology.

  • Antal, C., Cioara, T., Anghel, I., Antal, M., & Salomie, I. (2021). Distributed ledger technology review and decentralized applications development guidelines. Future Internet, 13(3), 62.

    Google Scholar 

  • Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84.

    Google Scholar 

  • Antonakakis, N., Gabauer, D., & Gupta, R. (2019). International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression. International Review of Financial Analysis, 65, 101382. https://doi.org/10.1016/j.irfa.2019.101382

    Article  Google Scholar 

  • Antonakakis, N., Gabauer, D., Gupta, R., & Plakandaras, V. (2018). Dynamic connectedness of uncertainty across developed economies: A time-varying approach. Economics Letters, 166, 63–75.

    Google Scholar 

  • Antonakakis, N., & Gabauer, D. (2017). Refined measures of dynamic connectedness based on TVP-VAR.

  • Asl, M. G., Adekoya, O. B., & Oliyide, J. A. (2022). Carbon market and the conventional and Islamic equity markets Where lays the environmental cleanliness of their utilities, energy, and ESG sectoral stocks? Journal of Cleaner Production, 351, 131523.

    Google Scholar 

  • Badr, N. G. (2019, 2019). Blockchain or Distributed Ledger Technology What Is in It for the Healthcare Industry?

  • Bao, J., He, D., Luo, M., & Choo, K.-K. R. (2020). A survey of blockchain applications in the energy sector. IEEE Systems Journal.

  • Baruník, J., & Kley, T. (2019). Quantile coherency: A general measure for dependence between cyclical economic variables. The Econometrics Journal, 22(2), 131–152. https://doi.org/10.1093/ectj/utz002

    Article  Google Scholar 

  • Barunık, J., & Kley, T. (2015). Quantile Cross-Spectral Measures of Dependence between Economic Variables. arXiv preprint arXiv:1510.06946.

  • Baumöhl, E. (2019). Are cryptocurrencies connected to forex? A quantile cross-spectral approach. Finance Research Letters, 29, 363–372. https://doi.org/10.1016/j.frl.2018.09.002

    Article  Google Scholar 

  • Baumöhl, E., & Shahzad, S. J. H. (2019). Quantile coherency networks of international stock markets. Finance Research Letters, 31, 119–129. https://doi.org/10.1016/j.frl.2019.04.022

    Article  Google Scholar 

  • Benos, E., Garratt, R., & Gurrola-Perez, P. (2017). The economics of distributed ledger technology for securities settlement. Available at SSRN 3023779.

  • Bouras, M. A., Lu, Q., Zhang, F., Wan, Y., Zhang, T., & Ning, H. (2020). Distributed ledger technology for eHealth identity privacy: State of the art and future perspective. Sensors, 20(2), 483.

    Google Scholar 

  • Bouri, E., Naeem, M. A., Nor, S. M., Mbarki, I., & Saeed, T. (2021). Government responses to COVID-19 and industry stock returns. Economic Research-Ekonomska Istraživanja, 15, 1–24.

    Google Scholar 

  • Brody, P. (2017). How blockchain is revolutionizing supply chain management. Digitalist Magazine, pp 1–7.

  • Brogan, J., Baskaran, I., & Ramachandran, N. (2018). Authenticating health activity data using distributed ledger technologies. Computational and Structural Biotechnology Journal, 16, 257–266.

    Google Scholar 

  • Calvão, F., & Archer, M. (2021). Digital extraction: Blockchain traceability in mineral supply chains. Political Geography, 87, 102381.

    Google Scholar 

  • Chang, V., Baudier, P., Zhang, H., Xu, Q., Zhang, J., & Arami, M. (2020). How Blockchain can impact financial services–The overview, challenges and recommendations from expert interviewees. Technological Forecasting and Social Change, 158, 120166.

    Google Scholar 

  • Chaudhuri, A., Bhatia, M. S., Kayikci, Y., Fernandes, K. J., & Fosso-Wamba, S. (2021). Improving social sustainability and reducing supply chain risks through blockchain implementation: Role of outcome and behavioural mechanisms. Annals of Operations Research. https://doi.org/10.1007/s10479-021-04307-6

    Article  Google Scholar 

  • Chaudhuri, B. (2019). The Indian energy sector-distributed ledger technology opportunities. Queen Mary School of Law Legal Studies Research Paper(305).

  • Choi, T.-M. (2020). Supply chain financing using blockchain: Impacts on supply chains selling fashionable products. Annals of Operations Research. https://doi.org/10.1007/s10479-020-03615-7

    Article  Google Scholar 

  • Chowdhury, M. J. M., Ferdous, M. D. S., Biswas, K., Chowdhury, N., Kayes, A. S. M., Alazab, M., & Watters, P. (2019). A comparative analysis of distributed ledger technology platforms. IEEE Access, 7, 167930–167943.

    Google Scholar 

  • Clark, B., & Burstall, R. (2018). Blockchain, IP and the pharma industry—how distributed ledger technologies can help secure the pharma supply chain. Journal of Intellectual Property Law & Practice, 13(7), 531–533.

    Google Scholar 

  • Cole, R., Stevenson, M., & Aitken, J. (2019). Blockchain technology: implications for operations and supply chain management. Supply Chain Management: An International Journal.

  • Coleman, L. (2017). Georgia expands project to secure land titles on the Bitcoin blockchain. CryptoCoins: News, 2.

  • Collomb, A., & Sok, K. (2016). Blockchain/distributed ledger technology (DLT): What impact on the financial sector? Digiworld Economic Journal(103).

  • Coppi, G. (2021). Introduction to distributed ledger technologies for social, development, and humanitarian impact. In Blockchain, Law and Governance (pp. 231–241): Springer.

  • Costa, A., Matos, P., & da Silva, C. (2022). Sectoral connectedness: New evidence from US stock market during COVID-19 pandemics. Finance Research Letters, 45, 102124. https://doi.org/10.1016/j.frl.2021.102124

    Article  Google Scholar 

  • Del Negro, M., & Primiceri, G. E. (2015). Time varying structural vector autoregressions and monetary policy: A corrigendum. The Review of Economic Studies, 82(4), 1342–1345. https://doi.org/10.1093/restud/rdv024

    Article  Google Scholar 

  • Diebold, F. X., & Yılmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119–134. https://doi.org/10.1016/j.jeconom.2014.04.012

    Article  Google Scholar 

  • Diebold, F. X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119(534), 158–171.

  • Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of forecasting, 28(1), 57–66.

  • Deshpande, A., Stewart, K., Lepetit, L., & Gunashekar, S. (2017). Distributed Ledger Technologies/Blockchain: Challenges, opportunities and the prospects for standards. Overview Report the British Standards Institution (BSI), 40, 40.

    Google Scholar 

  • Downes, L., & Reed, C. (2020). Distributed ledger technology for governance of sustainability transparency in the global energy value chain. Global Energy Law and Sustainability, 1(1), 55–100.

    Google Scholar 

  • Drescher, D. (2017). Blockchain Grundlagen: eine Einführung in die elementaren Konzepte in 25 Schritten: MITP-Verlags GmbH & Co. KG.

  • El Ioini, N., & Pahl, C. (2017, 2018). A review of distributed ledger technologies.

  • Engelhardt, M. A. (2017). Hitching healthcare to the chain: An introduction to blockchain technology in the healthcare sector. Technology Innovation Management Review, 7(10), 22–34.

    Google Scholar 

  • Fan, Z.-P., Wu, X.-Y., & Cao, B.-B. (2020). Considering the traceability awareness of consumers: should the supply chain adopt the blockchain technology? Annals of Operations Research, 309, 837–860.

    Google Scholar 

  • Farahani, B., Firouzi, F., & Luecking, M. (2021). The convergence of IoT and distributed ledger technologies (DLT): Opportunities, challenges, and solutions. Journal of Network and Computer Applications, 177, 102936.

    Google Scholar 

  • Fasanya, I. O., Adekoya, O. B., & Adetokunbo, A. M. (2021b). On the connection between oil and global financial exchange markets: The role of economic policy uncertainty. Resources Policy, 72, 102110.

    Google Scholar 

  • Fasanya, I. O., Oliyide, J. A., Adekoya, O. B., & Agbatogun, T. (2021a). How does economic policy uncertainty connect with the dynamic spillovers between precious metals and bitcoin markets? Resources Policy, 72, 102077.

    Google Scholar 

  • Ferraro, P., King, C., & Shorten, R. (2018). Distributed ledger technology for smart cities, the sharing economy, and social compliance. IEEE Access, 6, 62728–62746.

    Google Scholar 

  • Gabauer, D., & Gupta, R. (2018). On the transmission mechanism of country-specific and international economic uncertainty spillovers: Evidence from a TVP-VAR connectedness decomposition approach. Economics Letters, 171, 63–71.

    Google Scholar 

  • Gökalp, E., Gökalp, M. O., Çoban, S., & Eren, P. E. (2018, 2018). Analysing opportunities and challenges of integrated blockchain technologies in healthcare.

  • Hasse, F., von Perfall, A., Hillebrand, T., Smole, E., Lay, L., & Charlet, M. (2016). Blockchain–an opportunity for energy producers and consumers. PwC global power & utilities, 1–45.

  • Ikeda, K., & Hamid, M.-N. (2018). Applications of blockchain in the financial sector and a peer-to-peer global barter web. Advances in Computers Elsevier.

    Google Scholar 

  • Jiang, S., Cao, J., Wu, H., Yang, Y., Ma, M., & He, J. (2018, 2018). Blochie: a blockchain-based platform for healthcare information exchange.

  • Jutila, L. (2017). The blockchain technology and its applications in the financial sector.

  • Kamble, S. S., Gunasekaran, A., Subramanian, N., Ghadge, A., Belhadi, A., & Venkatesh, M. (2021). Blockchain technology’s impact on supply chain integration and sustainable supply chain performance: Evidence from the automotive industry. Annals of Operations Research. https://doi.org/10.1007/s10479-021-04129-6

    Article  Google Scholar 

  • Khan, S. A. R., Godil, D. I., Jabbour, C. J. C., Shujaat, S., Razzaq, A., & Yu, Z. (2021). Green data analytics, blockchain technology for sustainable development, and sustainable supply chain practices: Evidence from small and medium enterprises. Annals of Operations Research, 1–25. https://doi.org/10.1007/s10479-021-04275-x

  • Khan, S. A. R., Razzaq, A., Yu, Z., & Miller, S. (2021). Industry 4.0 and circular economy practices: A new era business strategies for environmental sustainability. Business Strategy and the Environment, 30(8), 4001–4014.

    Google Scholar 

  • Knezevic, D. (2018). Impact of blockchain technology platform in changing the financial sector and other industries. Montenegrin Journal of Economics, 14(1), 109–120.

    Google Scholar 

  • Ko, T., Lee, J., & Ryu, D. (2018). Blockchain technology and manufacturing industry: Real-time transparency and cost savings. Sustainability. https://doi.org/10.3390/su10114274

    Article  Google Scholar 

  • Ko, T., Lee, J., & Ryu, D. (2018b). Blockchain technology and manufacturing industry: Real-time transparency and cost savings. Sustainability, 10(11), 4274.

    Google Scholar 

  • Konashevych, O. (2020). Constraints and benefits of the blockchain use for real estate and property rights. Journal of Property, Planning and Environmental Law, 12(2), 109–127.

    Google Scholar 

  • Koop, G., & Korobilis, D. (2013). Large time-varying parameter VARs. Journal of Econometrics, 177(2), 185–198. https://doi.org/10.1016/j.jeconom.2013.04.007

    Article  Google Scholar 

  • Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4

    Article  Google Scholar 

  • Korobilis, D., & Yilmaz, K. (2018). Measuring dynamic connectedness with large Bayesian VAR models. Available at SSRN 3099725.

  • Krupa, K. S., & Akhil, M. S. (2019). Reshaping the real estate industry using blockchain. In Emerging Research in Electronics, Computer Science and Technology (pp. 255–263): Springer.

  • Kuo, T.-T., Kim, H.-E., & Ohno-Machado, L. (2017). Blockchain distributed ledger technologies for biomedical and health care applications. Journal of the American Medical Informatics Association, 24(6), 1211–1220.

    Google Scholar 

  • Lavanya, S., Lavanya, G., & Divyabharathi, J. (2017, 2017). A Survey on Internet of Things for Healthcare and Medication Management.

  • Le, T. H., Do, H. X., Nguyen, D. K., & Sensoy, A. (2021). Covid-19 pandemic and tail-dependency networks of financial assets. Finance Research Letters, 38, 101800.

    Google Scholar 

  • LeMahieu, C. (2018). Nano: A feeless distributed cryptocurrency network. Nano [Online resource]. URL: https://nano.org/en/whitepaper (date of access: 24.03. 2018), 16, 17.

  • Lee, J. Y. (2019). A decentralized token economy: How blockchain and cryptocurrency can revolutionize business. Business Horizons, 62(6), 773–784.

    Google Scholar 

  • Lemieux, V. L. (2017, 2017). Blockchain and distributed ledgers as trusted recordkeeping systems.

  • Leng, J., Ye, S., Zhou, M., Zhao, J. L., Liu, Q., Guo, W., & Fu, L. (2020). Blockchain-secured smart manufacturing in industry 4.0: A survey. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(1), 237–252.

    Google Scholar 

  • Li, J., & Kassem, M. (2019). Informing implementation of distributed ledger technology (DLT) in construction: Interviews with industry and academia. Advances in ICT in Design, Construction and Management in Architecture, Engineering, Construction and Operations (AECO). Proceedings of the 36th CIB W, 78, 2019.

  • Litvinenko, V. S. (2020). Digital economy as a factor in the technological development of the mineral sector. Natural Resources Research, 29(3), 1521–1541.

    Google Scholar 

  • Liu, X., Wu, H., Wu, W., Fu, Y., & Huang, G. Q. (2021). Blockchain-enabled ESG reporting framework for sustainable supply chain. In Sustainable Design and Manufacturing 2020 (pp. 403–413): Springer.

  • Lopes de Sousa Jabbour, A. B., Frascareli, F. C. d. O., Santibanez Gonzalez, E. D., & Chiappetta Jabbour, C. J. (2021). Are food supply chains taking advantage of the circular economy? A research agenda on tackling food waste based on Industry 4.0 technologies. Production Planning & Control, 1–17.

  • López-Oriona, Á., & Vilar, J. A. (2021). Quantile cross-spectral density: A novel and effective tool for clustering multivariate time series. Expert Systems with Applications, 185, 115677.

    Google Scholar 

  • Masood, F., & Faridi, A. R. (2018). An overview of distributed ledger technology and its applications. International Journal of Computational Science and Engineering, 6(10), 422–427.

    Google Scholar 

  • Maull, R., Godsiff, P., Mulligan, C., Brown, A., & Kewell, B. (2017). Distributed ledger technology: Applications and implications. Strategic Change, 26(5), 481–489. https://doi.org/10.1002/jsc.2148

    Article  Google Scholar 

  • Mensi, W., Nekhili, R., Vo, X. V., Suleman, T., & Kang, S. H. (2021). Asymmetric volatility connectedness among U.S stock sectors. The North American Journal of Economics and Finance, 56, 101327. https://doi.org/10.1016/j.najef.2020.101327

    Article  Google Scholar 

  • Mettler, M. (2017, 2016). Blockchain technology in healthcare: The revolution starts here.

  • Moenninghoff, S. C., & Wieandt, A. (2013). The Future of Peer-to-Peer Finance. Schmalenbachs Zeitschrift Für Betriebswirtschaftliche Forschung, 65(5), 466–487. https://doi.org/10.1007/BF03372882

    Article  Google Scholar 

  • Mohamed, N., & Al-Jaroodi, J. (2019). Applying Blockchain in Industry 4.0 applications. In: Paper presented at the 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC).

  • Mondragon, A. E. C., Mondragon, C. E. C., & Coronado, E. S. (2018). Exploring the applicability of blockchain technology to enhance manufacturing supply chains in the composite materials industry. In: Paper presented at the 2018 IEEE International Conference on Applied System Invention (ICASI).

  • Naeem, M. A., Adekoya, O. B., & Oliyide, J. A. (2021). Asymmetric spillovers netween green bonds and commodities. Journal of Cleaner Production, 314, 128100.

    Google Scholar 

  • Ølnes, S., Ubacht, J., & Janssen, M. (2017). Blockchain in government: Benefits and implications of distributed ledger technology for information sharing. In: Elsevier.

  • Pal, K. (2021). Applications of Secured Blockchain Technology in the Manufacturing Industry. In Blockchain and AI Technology in the Industrial Internet of Things (pp. 144–162): IGI Global.

  • Park, A., & Li, H. (2021). The effect of Blockchain technology on supply chain sustainability performances. Sustainability, 13(4), 1726.

    Google Scholar 

  • Perez, C. (2009). Technological Revolutions and Techno-economic Paradigms.” In Working Papers in Technology Governance and Economic Dynamics, Working Paper 20. Tallin: Norway and Tallinn University of Technology. In: Tallinn.

  • Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. https://doi.org/10.1016/S0165-1765(97)00214-0

    Article  Google Scholar 

  • Pinheiro, M. A. P., Jugend, D., de Sousa, Lopes, Jabbour, A. B., Chiappetta Jabbour, C. J., & Latan, H. (2022). Circular economy-based new products and company performance: The role of stakeholders and Industry 4.0 technologies. Business Strategy and the Environment, 31(1), 483–499.

    Google Scholar 

  • Primiceri, G. E. (2005). Time Varying Structural Vector Autoregressions and Monetary Policy. The Review of Economic Studies, 72(3), 821–852. https://doi.org/10.1111/j.1467-937X.2005.00353.x

    Article  Google Scholar 

  • Ren, Y., Liang, J., Su, J., Cao, G., & Liu, H. (2020). Data sharing mechanism of various mineral resources based on blockchain. Frontiers of Engineering Management, 7(4), 592–604.

    Google Scholar 

  • Roeck, D., Sternberg, H., & Hofmann, E. (2020). Distributed ledger technology in supply chains: A transaction cost perspective. International Journal of Production Research, 58(7), 2124–2141.

    Google Scholar 

  • Río, D., & César, A. (2017). Use of distributed ledger technology by central banks: A review. Enfoque Ute, 8(5), 1–13.

    Google Scholar 

  • Santo, A., Minowa, I., Hosaka, G., Hayakawa, S., Kondo, M., Ichiki, S., & Kaneko, Y. (2016). Applicability of distributed ledger technology to capital market infrastructure. Japan Exchange Group.

    Google Scholar 

  • Scott, B., Martindale, W., & Slebos, M. (2018). RESPONSIBLE INVESTMENT AND BLOCKCHAIN. Retrieved from

  • Shahnaz, A., Qamar, U., & Khalid, A. (2019). Using blockchain for electronic health records. IEEE Access, 7, 147782–147795.

    Google Scholar 

  • Shahzad, S. J. H., Bouri, E., Kristoufek, L., & Saeed, T. (2021a). Impact of the COVID-19 outbreak on the US equity sectors: Evidence from quantile return spillovers. Financial Innovation, 7(1), 1–23.

    Google Scholar 

  • Shahzad, S. J. H., Naeem, M. A., Peng, Z., & Bouri, E. (2021b). Asymmetric volatility spillover among Chinese sectors during COVID-19. International Review of Financial Analysis, 75, 101754.

    Google Scholar 

  • Siano, P., De Marco, G., Rolán, A., & Loia, V. (2019). A survey and evaluation of the potentials of distributed ledger technology for peer-to-peer transactive energy exchanges in local energy markets. IEEE Systems Journal, 13(3), 3454–3466.

    Google Scholar 

  • Singh, N., & Vardhan, M. (2019). Digital ledger technology-based real estate transaction mechanism and its block size assessment. International Journal of Blockchains and Cryptocurrencies, 1(1), 67–84.

    Google Scholar 

  • Spielman, A. (2016). Blockchain: digitally rebuilding the real estate industry.

  • Swan, M. (2015). Blockchain: Blueprint for a new economy: " O'Reilly Media, Inc.".

  • Tarr, J.-A. (2018). Distributed ledger technology, blockchain and insurance: Opportunities, risks and challenges. Insurance Law Journal, 29(3), 254–268.

    Google Scholar 

  • Thulasiraman, K., & Swamy, M. N. (2011). Graphs: theory and algorithms. John Wiley & Sons.

  • Umar, Z., Adekoya, O. B., Oliyide, J. A., & Gubareva, M. (2021). Media sentiment and short stocks performance during a systemic crisis. International Review of Financial Analysis, 78, 101896.

    Google Scholar 

  • Van Oerle, J., & Lemmens, P. (2016). Distributed ledger technology for the financial industry. White Paper, ROBECO.

  • Wang, Q., & Su, M. (2020). Integrating blockchain technology into the energy sector—from theory of blockchain to research and application of energy blockchain. Computer Science Review, 37, 100275.

    Google Scholar 

  • Workie, H., & Jain, K. (2017). Distributed ledger technology: Implications of blockchain for the securities industry. Journal of Securities Operations & Custody, 9(4), 347–355.

    Google Scholar 

  • Yoo, S. (2017). Blockchain based financial case analysis and its implications. Asia Pacific Journal of Innovation and Entrepreneurship., 11(3), 312–321.

    Google Scholar 

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Ghaemi Asl, M., Adekoya, O.B. & Rashidi, M.M. Quantiles dependence and dynamic connectedness between distributed ledger technology and sectoral stocks: enhancing the supply chain and investment decisions with digital platforms. Ann Oper Res 327, 435–464 (2023). https://doi.org/10.1007/s10479-022-04882-2

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