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Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach

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  • Jianqin Hang
  • Xu Zhang
  • Atila Bueno

Abstract

This study proposes a novel approach that incorporates rolling-window estimation and a quantile causality test. Using this approach, Google Trends and Bitcoin price data are used to empirically investigate the time-varying quantile causality between investor attention and Bitcoin returns. The results show that the parameters of the causality tests are unstable during the sample period. The results also show strong evidence of quantile- and time-varying causality between investor attention and Bitcoin returns. Specifically, our results show that causality appears only in high volatility periods within the time domain, and causality presents various patterns across quantiles within the quantile domain.

Suggested Citation

  • Jianqin Hang & Xu Zhang & Atila Bueno, 2021. "Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach," Complexity, Hindawi, vol. 2021, pages 1-12, August.
    • Handle: RePEc:hin:complx:5543995
    DOI: 10.1155/2021/5543995
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    Cited by:

    1. Amin Izadyar & Shiva Zamani, 2022. "Investor base and idiosyncratic volatility of cryptocurrencies," Papers 2211.13274, arXiv.org.

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