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Between financial and algorithmic dynamics of cryptocurrencies: An exploratory study

Author

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  • Christophe Schinckus
  • Canh Phuc Nguyen
  • Felicia Hui Ling Chong

Abstract

This article aims at investigating the extent to which the algorithmic nature (i.e., mining process) of cryptocurrencies might influence their dynamics and interaction with some major economic indicators. Our study observes that proof‐of‐stake based cryptocurrencies are less correlated with other crypto‐assets offering more opportunities for diversifying portfolio strategy. We also observe a positive correlation between the proof‐of‐work based cryptocurrencies and the oil price. This article discusses these matters and suggests that the differences in cryptocurrencies' dynamics are more related to their service or purpose rather than their mining protocol. This claim contributes to the current debates on the intrinsic value of cryptocurrencies and it is illustrated with a discussion of the Stellar (XLM) and Ether (ETH) cases. Beyond our empirical results, our article suggests that, the liquidity and the returns dynamics of cryptocurrencies might be affected by two different aspects. Precisely, the former appears to be influenced by the economic service for which these cryptocurrencies are used, while cryptocurrencies' returns are more reactive to the way their cryptographic validation is operated. Our findings also suggest that an analysis through the economic service/purpose of cryptocurrencies is actually appropriate to understand their dynamics in relation to economic indicators. This perspective implicitly questions the monetary aspect often associated with cryptocurrencies and it calls for a more categorized research (by economic purpose) of cryptocurrencies whose potential intrinsic value would then be related to their economic purpose.

Suggested Citation

  • Christophe Schinckus & Canh Phuc Nguyen & Felicia Hui Ling Chong, 2023. "Between financial and algorithmic dynamics of cryptocurrencies: An exploratory study," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 3055-3070, July.
    • Handle: RePEc:wly:ijfiec:v:28:y:2023:i:3:p:3055-3070
    DOI: 10.1002/ijfe.2583
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    1. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    2. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    3. Christophe Schinckus & Canh Phuc Nguyen & Felicia Chong Hui Ling, 2020. "Crypto-currencies Trading and Energy Consumption," International Journal of Energy Economics and Policy, Econjournals, vol. 10(3), pages 355-364.
    4. Shaen Corbet & Charles Larkin & Brian M. Lucey & Andrew Meegan & Larisa Yarovaya, 2020. "The impact of macroeconomic news on Bitcoin returns," The European Journal of Finance, Taylor & Francis Journals, vol. 26(14), pages 1396-1416, September.
    5. Tan, Shay-Kee & Chan, Jennifer So-Kuen & Ng, Kok-Haur, 2020. "On the speculative nature of cryptocurrencies: A study on Garman and Klass volatility measure," Finance Research Letters, Elsevier, vol. 32(C).
    6. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    7. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    8. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    9. Baur, Dirk G. & Dimpfl, Thomas & Kuck, Konstantin, 2018. "Bitcoin, gold and the US dollar – A replication and extension," Finance Research Letters, Elsevier, vol. 25(C), pages 103-110.
    10. Muhammad Ali Nasir & Toan Luu Duc Huynh & Sang Phu Nguyen & Duy Duong, 2019. "Forecasting cryptocurrency returns and volume using search engines," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-13, December.
    11. Canh, Nguyen Phuc & Wongchoti, Udomsak & Thanh, Su Dinh & Thong, Nguyen Trung, 2019. "Systematic risk in cryptocurrency market: Evidence from DCC-MGARCH model," Finance Research Letters, Elsevier, vol. 29(C), pages 90-100.
    12. Corbet, Shaen & Larkin, Charles & Lucey, Brian, 2020. "The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies," Finance Research Letters, Elsevier, vol. 35(C).
    13. Giancarlo Giudici & Alistair Milne & Dmitri Vinogradov, 2020. "Cryptocurrencies: market analysis and perspectives," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 1-18, March.
    14. Akyildirim, Erdinc & Corbet, Shaen & Lucey, Brian & Sensoy, Ahmet & Yarovaya, Larisa, 2020. "The relationship between implied volatility and cryptocurrency returns," Finance Research Letters, Elsevier, vol. 33(C).
    15. Łukasz Goczek & Ivan Skliarov, 2019. "What drives the Bitcoin price? A factor augmented error correction mechanism investigation," Applied Economics, Taylor & Francis Journals, vol. 51(59), pages 6393-6410, December.
    16. Abdel M. Zellou & John T. Cuddington, 2012. "Trends and Super Cycles in Crude Oil and Coal Prices," Working Papers 2012-10, Colorado School of Mines, Division of Economics and Business.
    17. Corbet, Shaen & Larkin, Charles & Lucey, Brian & Meegan, Andrew & Yarovaya, Larisa, 2020. "Cryptocurrency reaction to FOMC Announcements: Evidence of heterogeneity based on blockchain stack position," Journal of Financial Stability, Elsevier, vol. 46(C).
    18. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Yoon, Seong-Min, 2018. "Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets," Finance Research Letters, Elsevier, vol. 27(C), pages 228-234.
    19. Camilo Mora & Randi L. Rollins & Katie Taladay & Michael B. Kantar & Mason K. Chock & Mio Shimada & Erik C. Franklin, 2018. "Bitcoin emissions alone could push global warming above 2°C," Nature Climate Change, Nature, vol. 8(11), pages 931-933, November.
    20. Raymond Li & Roselyne Joyeux & Ronald D. Ripple, 2010. "International Steam Coal Market Integration," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 181-202.
    21. Frode Kjærland & Aras Khazal & Erlend A. Krogstad & Frans B. G. Nordstrøm & Are Oust, 2018. "An Analysis of Bitcoin’s Price Dynamics," JRFM, MDPI, vol. 11(4), pages 1-18, October.
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