Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach
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 result...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5543995 |
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| _version_ | 1849685725060005888 |
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| author | Jianqin Hang Xu Zhang |
| author_facet | Jianqin Hang Xu Zhang |
| author_sort | Jianqin Hang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-be6b7b68733e4e588c9b62b4f2d83786 |
| institution | DOAJ |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-be6b7b68733e4e588c9b62b4f2d837862025-08-20T03:23:01ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/55439955543995Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles ApproachJianqin Hang0Xu Zhang1School of Economics and Management, Jiangsu Maritime Institute, Nanjing 211170, ChinaSchool of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, ChinaThis 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.http://dx.doi.org/10.1155/2021/5543995 |
| spellingShingle | Jianqin Hang Xu Zhang Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach Complexity |
| title | Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach |
| title_full | Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach |
| title_fullStr | Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach |
| title_full_unstemmed | Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach |
| title_short | Time- and Quantile-Varying Causality between Investor Attention and Bitcoin Returns: A Rolling-Window Causality-in-Quantiles Approach |
| title_sort | time and quantile varying causality between investor attention and bitcoin returns a rolling window causality in quantiles approach |
| url | http://dx.doi.org/10.1155/2021/5543995 |
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