Forecasting bitcoin volatility: evidence from the options market

Lai T. Hoang, Dirk G. Baur

Research output: Contribution to journalArticleResearchpeer-review

15 Citations (Scopus)

Abstract

This paper studies a large number of bitcoin (BTC) options traded on the options exchange Deribit. We use the trades to calculate implied volatility (IV) and analyze if volatility forecasts can be improved using such information. IV is less accurate than AutoRegressive–Moving-Average or Heterogeneous Auto-Regressive model forecasts in predicting short-term BTC volatility (1 day ahead), but superior in predicting long-term volatility (7, 10, 15 days ahead). Furthermore, a combination of IV and model-based forecasts provides the highest accuracy for all forecasting horizons revealing that the BTC options market contains unique information.

Original languageEnglish
Pages (from-to)1584-1602
Number of pages19
JournalJournal of Futures Markets
Volume40
Issue number10
DOIs
Publication statusPublished - Oct 2020
Externally publishedYes

Keywords

  • bitcoin
  • bitcoin options market
  • forecasting
  • implied volatility
  • realized volatility

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