Forecasting the volatility of Bitcoin: the importance of jumps and structural breaks

Shen, D., Urquhart, A. ORCID: https://orcid.org/0000-0001-8834-4243 and Wang, P. (2020) Forecasting the volatility of Bitcoin: the importance of jumps and structural breaks. European Financial Management, 26 (5). pp. 1294-1323. ISSN 1468-036X doi: 10.1111/eufm.12254

Abstract/Summary

This paper studies the volatility of Bitcoin and determines the importance of jumps and structural breaks in forecasting volatility. We show the importance of the decomposition of realized variance in the in‐sample regressions using 18 competing heterogeneous autoregressive (HAR) models. In the out‐of‐sample setting, we find that the HARQ‐F‐J model is the superior model, indicating the importance of the temporal variation and squared jump components at different time horizons. We also show that HAR models with structural breaks outperform models without structural breaks across all forecasting horizons. Our results are robust to an alternative jump estimator and estimation method.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/87932
Identification Number/DOI	10.1111/eufm.12254
Refereed	Yes
Divisions	Henley Business School > Finance and Accounting
Publisher	Wiley
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