Assessing the Risk of Bitcoin Futures Market: New Evidence

Anupam Dutta ()
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Anupam Dutta: University of Vaasa

Annals of Data Science, 2025, vol. 12, issue 2, No 3, 497 pages

Abstract: Abstract The main objective of this paper is to forecast the realized volatility (RV) of Bitcoin futures (BTCF) market. To serve our purpose, we propose an augmented heterogenous autoregressive (HAR) model to consider the information on time-varying jumps observed in BTCF returns. Specifically, we estimate the jump-induced volatility using the GARCH-jump process and then consider this information in the HAR model. Both the in-sample and out-of-sample analyses show that jumps offer added information which is not provided by the existing HAR models. In addition, a novel finding is that the jump-induced volatility offers incremental information relative to the Bitcoin implied volatility index. In sum, our results indicate that the HAR-RV process comprising the leverage effects and jump volatility would predict the RV more precisely compared to the standard HAR-type models. These findings have important implications to cryptocurrency investors.

Keywords: Bitcoin futures market; Realized volatility; Jump-induced volatility; Bitcoin implied volatility index; Leverage effects; HAR-RV models (search for similar items in EconPapers)
JEL-codes: C01 G13 G17 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s40745-024-00517-4

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