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dc.contributor.author | Bouri, Elie![]() |
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dc.contributor.author | Gkillas, Konstantinos![]() |
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dc.contributor.author | Gupta, Rangan![]() |
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dc.contributor.author | Pierdzioch, Christian![]() |
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dc.date.accessioned | 2020-10-02T10:01:42Z | |
dc.date.issued | 2021-01 | |
dc.description.abstract | We analyze the role of the US–China trade war in forecasting out-of-sample daily realized volatility of Bitcoin returns. We study intraday data spanning from 1st July 2017 to 30th June 2019. We use the heterogeneous autoregressive realized volatility model (HAR-RV) as the benchmark model to capture stylized facts such as heterogeneity and long-memory. We then extend the HAR-RV model to include a metric of US–China trade tensions. This is our primary forecasting variable of interest, and it is based on Google Trends. We also control for jumps, realized skewness, and realized kurtosis. For our empirical analysis, we use a machine-learning technique that is known as random forests. Our findings reveal that US–China trade uncertainty does improve forecast accuracy for various configurations of random forests and forecast horizons. | en_ZA |
dc.description.department | Economics | en_ZA |
dc.description.embargo | 2021-08-10 | |
dc.description.librarian | mn2020 | en_ZA |
dc.description.sponsorship | German Science Foundation | en_ZA |
dc.description.uri | http://link.springer.com/journal/10614 | en_ZA |
dc.identifier.citation | Bouri, E., Gkillas, K., Gupta, R. et al. Forecasting Realized Volatility of Bitcoin: The Role of the Trade War. Computational Economics 57, 29–53 (2021). https://doi.org/10.1007/s10614-020-10022-4. | en_ZA |
dc.identifier.issn | 0927-7099 (print) | |
dc.identifier.issn | 1572-9974 (online) | |
dc.identifier.other | 10.1007/s10614-020-10022-4 | |
dc.identifier.uri | http://hdl.handle.net/2263/76318 | |
dc.language.iso | en | en_ZA |
dc.publisher | Springer | en_ZA |
dc.rights | © Springer Science+Business Media, LLC, part of Springer Nature 2020. The original publication is available at : http://link.springer.comjournal/10614. | en_ZA |
dc.subject | Heterogeneous autoregressive realized volatility model (HAR-RV) | en_ZA |
dc.subject | Random forests | en_ZA |
dc.subject | Bitcoin | en_ZA |
dc.subject | Realized volatility | en_ZA |
dc.subject | Trade war | en_ZA |
dc.title | Forecasting realized volatility of Bitcoin : the role of the trade war | en_ZA |
dc.type | Postprint Article | en_ZA |