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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

Author

Listed:
  • Mahdi Ghaemi Asl

    (Kharazmi University)

  • Oluwasegun B. Adekoya

    (Federal University of Agriculture)

  • Muhammad Mahdi Rashidi

    (Imam Sadiq University)

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.

Suggested Citation

  • Mahdi Ghaemi Asl & Oluwasegun B. Adekoya & Muhammad Mahdi Rashidi, 2023. "Quantiles dependence and dynamic connectedness between distributed ledger technology and sectoral stocks: enhancing the supply chain and investment decisions with digital platforms," Annals of Operations Research, Springer, vol. 327(1), pages 435-464, August.
  • Handle: RePEc:spr:annopr:v:327:y:2023:i:1:d:10.1007_s10479-022-04882-2
    DOI: 10.1007/s10479-022-04882-2
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    1. Taehyun Ko & Jaeram Lee & Doojin Ryu, 2018. "Blockchain Technology and Manufacturing Industry: Real-Time Transparency and Cost Savings," Sustainability, MDPI, vol. 10(11), pages 1-20, November.
    2. Syed Jawad Hussain Shahzad & Elie Bouri & Ladislav Kristoufek & Tareq Saeed, 2021. "Impact of the COVID-19 outbreak on the US equity sectors: Evidence from quantile return spillovers," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    3. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan, 2019. "International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression," International Review of Financial Analysis, Elsevier, vol. 65(C).
    4. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    5. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    6. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan & Plakandaras, Vasilios, 2018. "Dynamic connectedness of uncertainty across developed economies: A time-varying approach," Economics Letters, Elsevier, vol. 166(C), pages 63-75.
    7. Korobilis, D & Yilmaz, K, 2018. "Measuring Dynamic Connectedness with Large Bayesian VAR Models," Essex Finance Centre Working Papers 20937, University of Essex, Essex Business School.
    8. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Saleem, Owais & Adeoye, Habeeb A., 2022. "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, Elsevier, vol. 68(C).
    9. Fasanya, Ismail O. & Oliyide, Johnson A. & Adekoya, Oluwasegun B. & Agbatogun, Taofeek, 2021. "How does economic policy uncertainty connect with the dynamic spillovers between precious metals and bitcoin markets?," Resources Policy, Elsevier, vol. 72(C).
    10. Antonakakis, Nikolaos & Gabauer, David, 2017. "Refined Measures of Dynamic Connectedness based on TVP-VAR," MPRA Paper 78282, University Library of Munich, Germany.
    11. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    12. Sebastian C. Moenninghoff & Axel Wieandt, 2013. "The Future of Peer-to-Peer Finance," Schmalenbach Journal of Business Research, Springer, vol. 65(5), pages 466-487, September.
    13. Adekoya, Oluwasegun B. & Oliyide, Johnson A., 2021. "How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques," Resources Policy, Elsevier, vol. 70(C).
    14. Adekoya, Oluwasegun B. & Oliyide, Johnson A. & Noman, Ambreen, 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, Elsevier, vol. 74(C).
    15. Baumöhl, Eduard & Shahzad, Syed Jawad Hussain, 2019. "Quantile coherency networks of international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 119-129.
    16. Arim Park & Huan Li, 2021. "The Effect of Blockchain Technology on Supply Chain Sustainability Performances," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    17. Jozef Baruník & Tobias Kley, 2019. "Quantile coherency: A general measure for dependence between cyclical economic variables," The Econometrics Journal, Royal Economic Society, vol. 22(2), pages 131-152.
    18. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    19. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    20. Claudia Antal & Tudor Cioara & Ionut Anghel & Marcel Antal & Ioan Salomie, 2021. "Distributed Ledger Technology Review and Decentralized Applications Development Guidelines," Future Internet, MDPI, vol. 13(3), pages 1-32, February.
    21. Shahzad, Syed Jawad Hussain & Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie, 2021. "Asymmetric volatility spillover among Chinese sectors during COVID-19," International Review of Financial Analysis, Elsevier, vol. 75(C).
    22. Dominik Roeck & Henrik Sternberg & Erik Hofmann, 2020. "Distributed ledger technology in supply chains: a transaction cost perspective," International Journal of Production Research, Taylor & Francis Journals, vol. 58(7), pages 2124-2141, April.
    23. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    24. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    25. Gabauer, David & Gupta, Rangan, 2018. "On the transmission mechanism of country-specific and international economic uncertainty spillovers: Evidence from a TVP-VAR connectedness decomposition approach," Economics Letters, Elsevier, vol. 171(C), pages 63-71.
    26. Mensi, Walid & Nekhili, Ramzi & Vo, Xuan Vinh & Suleman, Tahir & Kang, Sang Hoon, 2021. "Asymmetric volatility connectedness among U.S. stock sectors," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    27. Lee, Jei Young, 2019. "A decentralized token economy: How blockchain and cryptocurrency can revolutionize business," Business Horizons, Elsevier, vol. 62(6), pages 773-784.
    28. Marco Antonio Paula Pinheiro & Daniel Jugend & Ana Beatriz Lopes de Sousa Jabbour & Charbel Jose Chiappetta Jabbour & Hengky Latan, 2022. "Circular economy‐based new products and company performance: The role of stakeholders and Industry 4.0 technologies," Business Strategy and the Environment, Wiley Blackwell, vol. 31(1), pages 483-499, January.
    29. Le, Trung Hai & Do, Hung Xuan & Nguyen, Duc Khuong & Sensoy, Ahmet, 2021. "Covid-19 pandemic and tail-dependency networks of financial assets," Finance Research Letters, Elsevier, vol. 38(C).
    30. Workie, Haimera & Jain, Kavita, 2017. "Distributed ledger technology: Implications of blockchain for the securities industry," Journal of Securities Operations & Custody, Henry Stewart Publications, vol. 9(4), pages 347-355, September.
    31. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    32. Marco Del Negro & Giorgio E. Primiceri, 2015. "Time Varying Structural Vector Autoregressions and Monetary Policy: A Corrigendum," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1342-1345.
    33. Dusko Knezevic, 2018. "Impact of Blockchain Technology Platform in Changing the Financial Sector and Other Industries," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 14(1), pages 109-120.
    34. Umar, Zaghum & Adekoya, Oluwasegun Babatunde & Oliyide, Johnson Ayobami & Gubareva, Mariya, 2021. "Media sentiment and short stocks performance during a systemic crisis," International Review of Financial Analysis, Elsevier, vol. 78(C).
    35. Costa, Antonio & Matos, Paulo & da Silva, Cristiano, 2022. "Sectoral connectedness: New evidence from US stock market during COVID-19 pandemics," Finance Research Letters, Elsevier, vol. 45(C).
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    Cited by:

    1. Ali Emrouznejad & Soumyadeb Chowdhury & Prasanta Kumar Dey, 2023. "Blockchain in operations and supply Chain Management," Annals of Operations Research, Springer, vol. 327(1), pages 1-6, August.

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