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Decisions in Economics and Finance

Erschienen in:

13.11.2021 | Editorial

Blockchain and cryptocurrencies: economic and financial research

verfasst von: Alessandra Cretarola, Gianna Figà-Talamanca, Cyril Grunspan

Erschienen in: Decisions in Economics and Finance | Ausgabe 2/2021

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Abstract

The motivation of proposing and editing the Special Issue “Blockchain and cryptocurrencies” came from the inspirational invited and contributed talks at the 43rd annual A.M.A.S.E.S. conference held in Perugia in September 2019. All the papers have gone through the journal regular refereeing process under the same standards set by the journal, and nine contributions were finally accepted for publication.

Vorheriger Artikel Envy effects on conflict dynamics in supervised work groups

Nächster Artikel Can fiat currencies really hedge Bitcoin? Evidence from dynamic short-term perspective

Ahn, Y., Kim, D.: Sentiment disagreement and bitcoin price fluctuations: a psycholinguistic approach. Appl. Econ. Lett., pp. 1–5 (2019)

Angeris, G., Chitra, T.: Improved price oracles: constant function market makers. In: Proceedings of the 2nd ACM Conference on Advances in Financial Technologies, Association for Computing Machinery, pp. 80–91 (2020)

Ante, L., Meyer, A.: Cross-listings of blockchain-based tokens issued through initial coin offerings: Do liquidity and specific cryptocurrency exchanges matter? Decis. Econ. Finance, pp. 1–24 (2021)

Antulov-Fantulin, N., Guo, T., Lillo, F.: Temporal mixture ensemble models for probabilistic forecasting of intraday cryptocurrency volume. Decis. Econ. Finance, pp. 1–36 (2021)

Baur, D.G., Hong, K., Lee, A.D.: Bitcoin: Medium of exchange or speculative assets? J. Int. Finan. Markets. Inst. Money 54, 177–189 (2018)CrossRef

Bistarelli, S., Cretarola, A., Figà-Talamanca, G., Mercanti, I., Patacca, M.: Is arbitrage possible in the bitcoin market? (Work-in-progress paper). In: Coppola M, Carlini E, D’Agostino D, Altmann J, Bañares JÀ (eds) Economics of Grids, Clouds, Systems, and Services. GECON 2018. Lecture Notes in Computer Science, vol. 11113., Springer, Cham, pp. 243–251 (2019a)

Bistarelli, S., Cretarola, A., Figà-Talamanca, G., Patacca, M.: Model-based arbitrage in multi-exchange models for bitcoin price dynamics. Digit. Finance 1(1), 23–46 (2019b)CrossRef

Bjerg, O.: How is bitcoin money? Theory, Culture & Society 33(1), 53–72 (2016)CrossRef

Blau, B., Griffith, T., Whitby, R., et al.: Comovement in the cryptocurrency market. Economics Bulletin 40(1), 448–455 (2020)

Böhme, R., Christin, N., Edelman, B., Moore, T.: Bitcoin: Economics, technology, and governance. J. Econ. Perspect. 29(2), 213–238 (2015)CrossRef

Bouri, E., Gil-Alana, L.A., Gupta, R., Roubaud, D.: Modelling long memory volatility in the bitcoin market: evidence of persistence and structural breaks. Int. J. Finance Econ. 24, 412–426 (2019)CrossRef

Chaim, P., Laurini, M.P.: Nonlinear dependence in cryptocurrency markets. N. Am. J. Econ. Finance 48, 32–47 (2019)CrossRef

Cheah, E.T., Fry, J.: Speculative bubbles in bitcoin markets? an empirical investigation into the fundamental value of bitcoin. Econ. Lett. 130, 32–36 (2015)CrossRef

Chen, C. Y. H., Härdle, W. K., Hou, A. J., Wang, W.: Pricing cryptocurrency options: the case of CRIX and Bitcoin. Tech. rep., IRTG 1792 Discussion Paper (2018)

Chitra, T., Evans, A.: Why stake when you can borrow? (2020). arXiv:2006.11156

Ciaian, P., Rajcaniova, M., Kancs, D.: The economics of bitcoin price formation. Appl. Econ. 48(19), 1799–1815 (2016)CrossRef

Ciaian, P., Rajcaniova, M., et al.: Virtual relationships: Short-and long-run evidence from Bitcoin and altcoin markets. J. Int. Finan. Markets. Inst. Money 52, 173–195 (2018)CrossRef

Corbet, S., Lucey, B., Peat, M., Vigne, S.: Bitcoin futures-what use are they? Econ. Lett. 172, 23–27 (2018a)CrossRef

Corbet, S., Lucey, B., Yarovaya, L.: Datestamping the bitcoin and Ethereum bubbles. Financ. Res. Lett. 26, 81–88 (2018b)CrossRef

Cretarola, A., Figà-Talamanca, G.: Detecting bubbles in bitcoin price dynamics via market exuberance. Ann. Oper. Res. 299, 1–21 (2019)

Cretarola, A., Figà-Talamanca, G.: Bubble regime identification in an attention-based model for bitcoin and Ethereum price dynamics. Econ. Lett. 191, 108831 (2020)CrossRef

Cretarola, A., Figà-Talamanca, G., Patacca, M.: Market attention and bitcoin price modeling: theory, estimation and option pricing. Decis. Econ. Finan. 43(1), 187–228 (2020)CrossRef

De Angelis, P., De Marchis, R., Marino, M., Martire, A. L., Oliva, I.: Betting on bitcoin: a profitable trading between directional and shielding strategies. Decis. Econ. Finance pp 1–21 (2021)

Dryja, T., Poon, J.: Lightning network (2015). https://lightning.network/

Dwork, C., Naor, M.: Pricing via processing or combatting junk mail. In: Brickell, E.F. (ed.) Advances in Cryptology - CRYPTO’ 92, pp. 139–147. Springer, Berlin (1993)

Dyhrberg, A. H.: Bitcoin, gold and the dollar - a garch volatility analysis. Finance Res. Lett. 16(Supplement C):85 – 92 (2016)

Eom, C., Kaizoji, T., Kang, S.H., Pichl, L.: Bitcoin and investor sentiment: statistical characteristics and predictability. Phys. A 514, 511–521 (2019)CrossRef

Figa-Talamanca, G., Patacca, M.: Does market attention affect bitcoin returns and volatility? Decis. Econ. Finance 42(1), 135–155 (2019)CrossRef

Figà-Talamanca, G., Patacca, M.: Disentangling the relationship between bitcoin and market attention measures. J. Ind. Bus. Econ. 47(1), 71–91 (2020)CrossRef

Figà-Talamanca, G., Focardi, S., Patacca, M.: Regime switches and commonalities of the cryptocurrencies asset class. N. Am. J. Econ. Finance 57, 101425 (2021)CrossRef

Figà-Talamanca, G., Focardi, S., Patacca, M.: Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages. Decis. Econ. Finance, pp. 1–20 (2021)

Fry, J., Cheah, E.T.: Negative bubbles and shocks in cryptocurrency markets. Int. Rev. Financ. Anal. 47, 343–352 (2016)CrossRef

Gandal, N., Hamrick, J., Moore, T., Vasek, M.: The rise and fall of cryptocurrency coins and tokens. Decis. Econ. Finance, pp. 1–34 (2021)

Garcia, D., Tessone, C.J., Mavrodiev, P., Perony, N.: The digital traces of bubbles: feedback cycles between socio-economic signals in the bitcoin economy. J. R. Soc. Interface 11(99), 20140623 (2014)CrossRef

Ghorbel, A., Jeribi, A.: Investigating the relationship between volatilities of cryptocurrencies and other financial assets. Decis. Econ. Finance, pp. 1–27 (2021)

Grunspan, C., Pérez-Marco, R.: Double spend races. Int. J. Theor. Appl. Finance 21(08), 1850053 (2018)CrossRef

Grunspan, C., Pérez-Marco, R.: On profitability of Nakamoto double spend. Probability in the Engineering and Informational Sciences pp. 1–15 (2021)

Hafner, C.M.: Testing for bubbles in cryptocurrencies with time-varying volatility. J. Financ. Economet. 18(2), 233–249 (2020)

Kristoufek, L.: What are the main drivers of the bitcoin price? Evidence from wavelet coherence analysis. PLoS ONE 10(4), e0123923 (2015)CrossRef

Kumar, A.S., Anandarao, S.: Volatility spillover in crypto-currency markets: some evidences from GARCH and wavelet analysis. Phys. A 524, 448–458 (2019)CrossRef

Kyriazis, N. A.: the Investigating diversifying or hedging nexus of cannabis cryptocurrencies with major digital currencies. Decis. Econ. Finance, pp. 1–21 (2021)

Lintilhac, P.S., Tourin, A.: Model-based pairs trading in the bitcoin markets. Quant. Finance 17(5), 703–716 (2017)CrossRef

Majdoub, J., Sassi, S.B., Bejaoui, A.: Can fiat currencies really hedge bitcoin? evidence from dynamic short-term perspective. Decisions in Economics and Finance, pp. 1–28 (2021)

Mensi, W., Rehman, M.U., Al-Yahyaee, K.H., Al-Jarrah, I.M.W., Kang, S.H.: Time frequency analysis of the commonalities between bitcoin and major cryptocurrencies: portfolio risk management implications. N. Am. J. Econ. Finance 48, 283–294 (2019)CrossRef

Nakamoto, S.: Bitcoin: A peer-to-peer electronic cash system. Decent. Bus. Rev., p. 21260 (2008)

Nakano, M., Takahashi, A., Takahashi, S.: Bitcoin technical trading with artificial neural network. Phys. A 510, 587–609 (2018)CrossRef

Nian, L.P., Chuen, D.L.K.: Introduction to bitcoin. In: Chuen, D.L.K. (ed.) Handbook of Digital Currency, Elsevier, pp 5–30 (2015)

Platanakis, E., Sutcliffe, C., Urquhart, A.: Optimal vs naïve diversification in cryptocurrencies. Econ. Lett. 171, 93–96 (2018)CrossRef

Provenzano, D., Baggio, R.: Complexity traits and synchrony of cryptocurrencies price dynamics. Decis. Econ. Finance, pp. 1–15 (2021)

Scaillet, O., Treccani, A., Trevisan, C.: High-frequency jump analysis of the bitcoin market. J. Financ. Economet. 18(2), 209–232 (2020)

Shynkevich, A.: Bitcoin arbitrage. Financ. Res. Lett. 40, 101698 (2021)CrossRef

Siu, T.K., Elliott, R.J.: Bitcoin option pricing with a SETAR-GARCH model. Eur. J. Finance 27(6), 564–595 (2021)CrossRef

Tiwari, A.K., Adewuyi, A.O., Albulescu, C.T., Wohar, M.E.: Empirical evidence of extreme dependence and contagion risk between main cryptocurrencies. N. Am. J. Econ. Finance 51, 101083 (2020)CrossRef

Yaya, O. S., Ogbonna, A. E., Olubusoye, O. E.: How persistent and dynamic inter-dependent are pricing of bitcoin to other cryptocurrencies before and after 2017/18 crash? Physica A: Statistical Mechanics and its Applications p 121732 (2019)

Yermack, D.: Is bitcoin a real currency? An economic appraisal. In: Chuen, D.L.K. (ed.) Handbook of Digital Currency, Elsevier, pp. 31–43 (2015)

Titel: Blockchain and cryptocurrencies: economic and financial research
verfasst von: Alessandra Cretarola
Gianna Figà-Talamanca
Cyril Grunspan
Publikationsdatum: 13.11.2021
Verlag: Springer International Publishing
Erschienen in: Decisions in Economics and Finance / Ausgabe 2/2021
Print ISSN: 1593-8883
Elektronische ISSN: 1129-6569
DOI: https://doi.org/10.1007/s10203-021-00366-3

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Can fiat currencies really hedge Bitcoin? Evidence from dynamic short-term perspective

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Common dynamic factors for cryptocurrencies and multiple pair-trading statistical arbitrages

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