Convergence in cryptocurrency prices? the role of market microstructure
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DOI: 10.1016/j.frl.2020.101685
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- Fernández-Villaverde, Jesús & Sanches, Daniel, 2019.
"Can currency competition work?,"
Journal of Monetary Economics, Elsevier, vol. 106(C), pages 1-15.
- Jesús Fernández-Villaverde & Daniel Sanches, 2016. "Can Currency Competition Work?," NBER Working Papers 22157, National Bureau of Economic Research, Inc.
- Jesus Fernandez-Villaverde & Daniel Sanches, 2016. "Can Currency Competition Work?," PIER Working Paper Archive 16-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 03 Apr 2016.
- Fernández-Villaverde, Jesús & Sanches, Daniel, 2016. "Can Currency Competition Work?," CEPR Discussion Papers 11095, C.E.P.R. Discussion Papers.
- Jesús Fernández-Villaverde & Daniel R. Sanches, 2016. "Can currency competition work?," Working Papers 16-12, Federal Reserve Bank of Philadelphia.
- Hodrick, Robert J & Prescott, Edward C, 1997.
"Postwar U.S. Business Cycles: An Empirical Investigation,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
- Robert J. Hodrick & Edward Prescott, 1981. "Post-War U.S. Business Cycles: An Empirical Investigation," Discussion Papers 451, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Van Vliet, Ben, 2018. "An alternative model of Metcalfe’s Law for valuing Bitcoin," Economics Letters, Elsevier, vol. 165(C), pages 70-72.
- Koutmos, Dimitrios, 2018. "Return and volatility spillovers among cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 122-127.
- Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.
- Connor, Gregory & Korajczyk, Robert A., 1986. "Performance measurement with the arbitrage pricing theory : A new framework for analysis," Journal of Financial Economics, Elsevier, vol. 15(3), pages 373-394, March.
- Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
- Akcora, Cuneyt Gurcan & Dixon, Matthew F. & Gel, Yulia R. & Kantarcioglu, Murat, 2018. "Bitcoin risk modeling with blockchain graphs," Economics Letters, Elsevier, vol. 173(C), pages 138-142.
- Tran, Vu Le & Leirvik, Thomas, 2019. "A simple but powerful measure of market efficiency," Finance Research Letters, Elsevier, vol. 29(C), pages 141-151.
- Chamberlain, Gary & Rothschild, Michael, 1983.
"Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets,"
Econometrica, Econometric Society, vol. 51(5), pages 1281-1304, September.
- Gary Chamberlain & Michael Rothschild, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," NBER Working Papers 0996, National Bureau of Economic Research, Inc.
- Chamberlain, Gary & Rothschild, Michael, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Scholarly Articles 3230355, Harvard University Department of Economics.
- Cuneyt Akcora & Matthew Dixon & Yulia Gel & Murat Kantarcioglu, 2018. "Bitcoin Risk Modeling with Blockchain Graphs," Papers 1805.04698, arXiv.org.
- Connor, Gregory & Korajczyk, Robert A., 1988. "Risk and return in an equilibrium APT : Application of a new test methodology," Journal of Financial Economics, Elsevier, vol. 21(2), pages 255-289, September.
- Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
- Peter C. B. Phillips & Donggyu Sul, 2007.
"Transition Modeling and Econometric Convergence Tests,"
Econometrica, Econometric Society, vol. 75(6), pages 1771-1855, November.
- Peter C.B. Phillips & Donggyu Sul, 2007. "Transition Modeling and Econometric Convergence Tests," Cowles Foundation Discussion Papers 1595, Cowles Foundation for Research in Economics, Yale University.
- Hu, Yang & Valera, Harold Glenn A. & Oxley, Les, 2019. "Market efficiency of the top market-cap cryptocurrencies: Further evidence from a panel framework," Finance Research Letters, Elsevier, vol. 31(C), pages 138-145.
- Easley, David & O'Hara, Maureen & Basu, Soumya, 2019. "From mining to markets: The evolution of bitcoin transaction fees," Journal of Financial Economics, Elsevier, vol. 134(1), pages 91-109.
- 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.
- Lior Menzly & Tano Santos & Pietro Veronesi, 2002. "The Time Series of the Cross Section of Asset Prices," NBER Working Papers 9217, National Bureau of Economic Research, Inc.
- Dyhrberg, Anne H. & Foley, Sean & Svec, Jiri, 2018. "How investible is Bitcoin? Analyzing the liquidity and transaction costs of Bitcoin markets," Economics Letters, Elsevier, vol. 171(C), pages 140-143.
- Jun Liu & Allan Timmermann, 2013. "Optimal Convergence Trade Strategies," The Review of Financial Studies, Society for Financial Studies, vol. 26(4), pages 1048-1086.
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- Gunay, Samet & Goodell, John W. & Muhammed, Shahnawaz & Kirimhan, Destan, 2023. "Frequency connectedness between FinTech, NFT and DeFi: Considering linkages to investor sentiment," International Review of Financial Analysis, Elsevier, vol. 90(C).
- Giannellis, Nikolaos, 2022. "Cryptocurrency market connectedness in Covid-19 days and the role of Twitter: Evidence from a smooth transition regression model," Research in International Business and Finance, Elsevier, vol. 63(C).
- Mohamad, Azhar & Stavroyiannis, Stavros, 2022. "Do birds of a feather flock together? Evidence from time-varying herding behaviour of bitcoin and foreign exchange majors during Covid-19," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
- Wang, Qishu, 2023. "Herding behavior and the dynamics of ESG performance in the European banking industry," Finance Research Letters, Elsevier, vol. 58(PD).
- Apergis, Nicholas, 2023. "Realized higher-order moments spillovers across cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
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More about this item
Keywords
Bitcoin; Club convergence; Cryptocurrencies; Market microstructure;All these keywords.
JEL classification:
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
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