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Some stylized facts of the cryptocurrency market

Citations

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Cited by:

  1. Masuhr Andreas & Trede Mark, 2020. "Bayesian estimation of generalized partition of unity copulas," Dependence Modeling, De Gruyter, vol. 8(1), pages 119-131, January.
  2. Vidal-Tomás, David, 2021. "The entry and exit dynamics of the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 58(C).
  3. Garcia-Jorcano, Laura & Benito, Sonia, 2020. "Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying," Research in International Business and Finance, Elsevier, vol. 54(C).
  4. Syuhada, Khreshna & Hakim, Arief & Suprijanto, Djoko & Muchtadi-Alamsyah, Intan & Arbi, Lukman, 2022. "Is Tether a safe haven of safe haven amid COVID-19? An assessment against Bitcoin and oil using improved measures of risk," Resources Policy, Elsevier, vol. 79(C).
  5. Parthajit Kayal & G. Balasubramanian, 2021. "Excess Volatility in Bitcoin: Extreme Value Volatility Estimation," IIM Kozhikode Society & Management Review, , vol. 10(2), pages 222-231, July.
  6. Wang, Pengfei & Zhang, Wei & Li, Xiao & Shen, Dehua, 2019. "Is cryptocurrency a hedge or a safe haven for international indices? A comprehensive and dynamic perspective," Finance Research Letters, Elsevier, vol. 31(C), pages 1-18.
  7. Shapovalova, Daria & Stephen, Kathrin, 2019. "No race for the Arctic? Examination of interconnections between legal regimes for offshore petroleum licensing and level of industry activity," Energy Policy, Elsevier, vol. 129(C), pages 907-917.
  8. Qi, Qi & Long, Chao & Wu, Jianzhong & Yu, James, 2018. "Impacts of a medium voltage direct current link on the performance of electrical distribution networks," Applied Energy, Elsevier, vol. 230(C), pages 175-188.
  9. Fulvia Pennoni & Francesco Bartolucci & Gianfranco Forte & Ferdinando Ametrano, 2022. "Exploring the dependencies among main cryptocurrency log‐returns: A hidden Markov model," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 51(1), February.
  10. Nedved, Martin & Kristoufek, Ladislav, 2023. "Safe havens for Bitcoin," Finance Research Letters, Elsevier, vol. 51(C).
  11. Matthias Schnaubelt & Jonas Rende & Christopher Krauss, 2019. "Testing Stylized Facts of Bitcoin Limit Order Books," JRFM, MDPI, vol. 12(1), pages 1-30, February.
  12. Stefano Martinazzi & Daniele Regoli & Andrea Flori, 2020. "A Tale of Two Layers: The Mutual Relationship between Bitcoin and Lightning Network," Risks, MDPI, vol. 8(4), pages 1-18, December.
  13. Yi, Eojin & Ahn, Kwangwon & Choi, M.Y., 2022. "Cryptocurrency: Not far from equilibrium," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
  14. Alla A. Petukhina & Raphael C. G. Reule & Wolfgang Karl Härdle, 2021. "Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies," The European Journal of Finance, Taylor & Francis Journals, vol. 27(1-2), pages 8-30, January.
  15. Borgards, Oliver & Czudaj, Robert L., 2021. "Features of overreactions in the cryptocurrency market," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 31-48.
  16. Martin Waltz & Abhay Kumar Singh & Ostap Okhrin, 2022. "Vulnerability-CoVaR: investigating the crypto-market," Quantitative Finance, Taylor & Francis Journals, vol. 22(9), pages 1731-1745, September.
  17. Chowdhury, Reaz & Rahman, M. Arifur & Rahman, M. Sohel & Mahdy, M.R.C., 2020. "An approach to predict and forecast the price of constituents and index of cryptocurrency using machine learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
  18. Gianna Figá-Talamanca & Sergio Focardi & Marco Patacca, 2021. "Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(2), pages 863-882, December.
  19. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2018. "Cryptocurrencies, Metcalfe's law and LPPL models," IRTG 1792 Discussion Papers 2018-056, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  20. Altan, Aytaç & Karasu, Seçkin & Bekiros, Stelios, 2019. "Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 325-336.
  21. Theophilos Papadimitriou & Periklis Gogas & Athanasios Fotios Athanasiou, 2022. "Forecasting Bitcoin Spikes: A GARCH-SVM Approach," Forecasting, MDPI, vol. 4(4), pages 1-15, September.
  22. Ramit Sawhney & Shivam Agarwal & Vivek Mittal & Paolo Rosso & Vikram Nanda & Sudheer Chava, 2022. "Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models," Papers 2206.06320, arXiv.org.
  23. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "High frequency volatility co-movements in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 35-52.
  24. Andrew Phiri, 2022. "Can wavelets produce a clearer picture of weak-form market efficiency in Bitcoin?," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 373-386, September.
  25. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
  26. Nocera, Silvio & Fabio, Alberto & Cavallaro, Federico, 2020. "The adoption of grid transit networks in non-metropolitan contexts," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 256-272.
  27. Delson Chikobvu & Thabani Ndlovu, 2023. "The Generalised Extreme Value Distribution Approach to Comparing the Riskiness of BitCoin/US Dollar and South African Rand/US Dollar Returns," JRFM, MDPI, vol. 16(4), pages 1-16, April.
  28. Chu, Jeffrey & Zhang, Yuanyuan & Chan, Stephen, 2019. "The adaptive market hypothesis in the high frequency cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 221-231.
  29. Yan, Kai & Zhang, Wei & Shen, Dehua, 2020. "Stylized facts of the carbon emission market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
  30. Lahmiri, Salim & Bekiros, Stelios, 2019. "Decomposing the persistence structure of Islamic and green crypto-currencies with nonlinear stepwise filtering," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 334-341.
  31. Konstantin Häusler & Hongyu Xia, 2022. "Indices on cryptocurrencies: an evaluation," Digital Finance, Springer, vol. 4(2), pages 149-167, September.
  32. Arthur A. B. Pessa & Matjaz Perc & Haroldo V. Ribeiro, 2023. "Age and market capitalization drive large price variations of cryptocurrencies," Papers 2302.12319, arXiv.org.
  33. Lee, Jei Young, 2019. "A decentralized token economy: How blockchain and cryptocurrency can revolutionize business," Business Horizons, Elsevier, vol. 62(6), pages 773-784.
  34. Luis Lorenzo & Javier Arroyo, 2022. "Analysis of the cryptocurrency market using different prototype-based clustering techniques," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-46, December.
  35. Nie, Chun-Xiao, 2020. "Correlation dynamics in the cryptocurrency market based on dimensionality reduction analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
  36. Li, Mu-Yao & Cai, Qing & Gu, Gao-Feng & Zhou, Wei-Xing, 2019. "Exponentially decayed double power-law distribution of Bitcoin trade sizes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
  37. Masuhr Andreas & Trede Mark, 2020. "Bayesian estimation of generalized partition of unity copulas," Dependence Modeling, De Gruyter, vol. 8(1), pages 119-131, January.
  38. López-Martín, Carmen & Arguedas-Sanz, Raquel & Muela, Sonia Benito, 2022. "A cryptocurrency empirical study focused on evaluating their distribution functions," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 387-407.
  39. Ghosh, Bikramaditya & Bouri, Elie & Wee, Jung Bum & Zulfiqar, Noshaba, 2023. "Return and volatility properties: Stylized facts from the universe of cryptocurrencies and NFTs," Research in International Business and Finance, Elsevier, vol. 65(C).
  40. Konstantin Hausler & Wolfgang Karl Hardle, 2021. "Cryptocurrency Dynamics: Rodeo or Ascot?," Papers 2103.12461, arXiv.org, revised Jan 2022.
  41. Venelina Nikolova & Juan E. Trinidad Segovia & Manuel Fernández-Martínez & Miguel Angel Sánchez-Granero, 2020. "A Novel Methodology to Calculate the Probability of Volatility Clusters in Financial Series: An Application to Cryptocurrency Markets," Mathematics, MDPI, vol. 8(8), pages 1-15, July.
  42. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and herding behaviour in the cryptocurrencies market," Economics Discussion Papers 2019-16, Kiel Institute for the World Economy (IfW Kiel).
  43. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
  44. Maurice Omane‐Adjepong & Imhotep Paul Alagidede, 2021. "Modelling Asymmetry and Leverage in Cryptocurrencies and Emerging Financial Markets," Economic Papers, The Economic Society of Australia, vol. 40(2), pages 152-166, June.
  45. Kerolly Kedma Felix do Nascimento & Fábio Sandro dos Santos & Jader Silva Jale & Silvio Fernando Alves Xavier Júnior & Tiago A. E. Ferreira, 2023. "Extracting Rules via Markov Chains for Cryptocurrencies Returns Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1095-1114, March.
  46. Punzo, Antonio & Bagnato, Luca, 2021. "Modeling the cryptocurrency return distribution via Laplace scale mixtures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
  47. Alessio Brini & Jimmie Lenz, 2024. "A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes," Papers 2404.04962, arXiv.org.
  48. Ha Nguyen & Bin Liu & Nirav Y. Parikh, 2020. "Exploring the short-term momentum effect in the cryptocurrency market," Evolutionary and Institutional Economics Review, Springer, vol. 17(2), pages 425-443, July.
  49. Borgards, Oliver, 2021. "Dynamic time series momentum of cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
  50. Fang, Sheng & Cao, Guangxi & Egan, Paul, 2023. "Forecasting and backtesting systemic risk in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 54(C).
  51. Tiwari, Aviral Kumar & Adewuyi, Adeolu O. & Albulescu, Claudiu T. & Wohar, Mark E., 2020. "Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
  52. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
  53. Häusler, Konstantin & Härdle, Wolfgang, 2021. "Rodeo or ascot: Which hat to wear at the crypto race?," IRTG 1792 Discussion Papers 2021-007, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  54. Bedi, Prateek & Nashier, Tripti, 2020. "On the investment credentials of Bitcoin: A cross-currency perspective," Research in International Business and Finance, Elsevier, vol. 51(C).
  55. C. Vladimir Rodríguez-Caballero & Mauricio Villanueva-Domínguez, 2022. "Predicting cryptocurrency crash dates," Empirical Economics, Springer, vol. 63(6), pages 2855-2873, December.
  56. Pele, Daniel Traian & Wesselhöfft, Niels & Härdle, Wolfgang Karl & Kolossiatis, Michalis & Yatracos, Yannis, 2019. "Phenotypic convergence of cryptocurrencies," IRTG 1792 Discussion Papers 2019-018, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
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