Quantile causal relationship between Bitcoin and stock indices
Bibliographic Data
| ID | 12549996 |
|---|---|
| Authors | Myeong Jun Kim (School of Economics and Finance, South China University of Technology, Guangzhou University Town, Guangzhou Shi), Sung Y Park (0000-0001-9149-7603, Chung-Ang University, corresponding author) |
| Year | 2024 |
| Volume | 30 |
| Issue | 3 |
| Pages | 812-828 |
| Publication date | 2024-05-08 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of the Asia Pacific Economy (JOURNAL) |
| Journal identifiers | ISSN: 1354-7860 • E-ISSN: 1469-9648 |
| Publisher | Routledge (PUBLISHER • GB) |
| DOI | 10.1080/13547860.2024.2347481 |
| OpenAlex | W4396731331 |
| Language | EN |
| References cited | 21 |
This study employs a Granger non-causality test in quantiles to analyze the causal relationship between Bitcoin and representative stock indices. We further bifurcate our analysis into pre- and post-COVID-19 periods, providing a unique perspective on hedge evaluation in different market conditions. The empirical findings reveal several key insights. First, a traditional causal test conducted over the entire period, which only considers causality at the mean, leads us to reject the null hypothesis that Bitcoin does not Granger cause any of the nine stock indices. However, we find that Bitcoin is not Granger caused by five out of nine stock indices. Second, by extending the analysis to the overall quantile interval, we find significant results in 12 out of 18 cases. Third, we identify robust causal relationships between Bitcoin and stock indices across lower and higher quantile intervals. Lastly, in the post-COVID-19 period, characterized by heightened price volatility and increased uncertainty, we observe a near-universal reversal in the causal relationships between Bitcoin and stock indices. Furthermore, the number of cases exhibiting causality increased markedly compared with the pre-COVID-19 period, which was characterized by more moderate price volatility and uncertainty
Business · Econometrics · Economics · Financial economics · Geography · Granger causality · Monetary economics · Quantile · Quantile regression · Stock (firearms · Blockchain Technology Applications and Security · Complex Systems and Time Series Analysis · Market Dynamics and Volatility
| Highly cited | No |
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