Taylor effect in Bitcoin time series
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DOI: 10.1016/j.econlet.2018.07.046
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References listed on IDEAS
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Citations
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Cited by:
- Tetsuya Takaishi & Takanori Adachi, 2020. "Market Efficiency, Liquidity, and Multifractality of Bitcoin: A Dynamic Study," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 145-154, March.
- de la Horra, Luis P. & de la Fuente, Gabriel & Perote, Javier, 2019. "The drivers of Bitcoin demand: A short and long-run analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 21-34.
- Takaishi, Tetsuya, 2020. "Rough volatility of Bitcoin," Finance Research Letters, Elsevier, vol. 32(C).
- Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
- da Cunha, C.R. & da Silva, R., 2020. "Relevant stylized facts about bitcoin: Fluctuations, first return probability, and natural phenomena," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
- Tetsuya Takaishi, 2019. "Rough volatility of Bitcoin," Papers 1904.12346, arXiv.org.
- Tetsuya Takaishi & Takanori Adachi, 2019. "Market efficiency, liquidity, and multifractality of Bitcoin: A dynamic study," Papers 1902.09253, arXiv.org.
- Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021.
"Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis,"
Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
- Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723, arXiv.org.
- Tetsuya Takaishi, 2021. "Time-varying properties of asymmetric volatility and multifractality in Bitcoin," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-21, February.
- Ting-Hsuan Chen & Mu-Yen Chen & Guan-Ting Du, 2021. "The Determinants of Bitcoin’s Price: Utilization of GARCH and Machine Learning Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 267-280, January.
- T. Takaishi, 2021. "Power-Law Return-Volatility Cross Correlations of Bitcoin," Papers 2102.08187, arXiv.org.
- Nikolaos A. Kyriazis, 2019. "A Survey on Efficiency and Profitable Trading Opportunities in Cryptocurrency Markets," JRFM, MDPI, vol. 12(2), pages 1-17, April.
- Shaen Corbet & Les Oxley, 2023. "Investigating the Academic Response to Cryptocurrencies: Insights from Research Diversification as Separated by Journal Ranking," Review of Corporate Finance, now publishers, vol. 3(4), pages 487-528, September.
- Huthaifa Alqaralleh & Alaa Adden Abuhommous & Ahmad Alsaraireh, 2020. "Modelling and Forecasting the Volatility of Cryptocurrencies: A Comparison of Nonlinear GARCH-Type Models," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(4), pages 346-356, July.
- Tetsuya Takaishi, 2021. "Time-varying properties of asymmetric volatility and multifractality in Bitcoin," Papers 2102.07425, arXiv.org.
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Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
- Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723, arXiv.org.
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More about this item
Keywords
Taylor effect; Bitcoin; Cryptocurrency; Autocorrelation;All these keywords.
JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
- G1 - Financial Economics - - General Financial Markets
Statistics
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