Frequency domain causality and quantile connectedness between investor sentiment and cryptocurrency returns
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DOI: 10.1016/j.iref.2023.07.038
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References listed on IDEAS
- Kraaijeveld, Olivier & De Smedt, Johannes, 2020. "The predictive power of public Twitter sentiment for forecasting cryptocurrency prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
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More about this item
Keywords
Investor sentiment; Fears; Cryptocurrency returns; Frequency domain causality; Cross-quantile coherency; Cross-quantile network;All these keywords.
JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
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