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Fear and Volatility in Digital Assets

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  • Faizaan Pervaiz
  • Christopher Goh
  • Ashley Pennington
  • Samuel Holt
  • James West
  • Shaun Ng

Abstract

We show Bitcoin implied volatility on a 5 minute time horizon is modestly predictable from price, volatility momentum and alternative data including sentiment and engagement. Lagged Bitcoin index price and volatility movements contribute to the model alongside Google Trends with markets responding often several hours later. The code and datasets used in this paper can be found at https://github.com/Globe-Research/bitfear.

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  • Faizaan Pervaiz & Christopher Goh & Ashley Pennington & Samuel Holt & James West & Shaun Ng, 2020. "Fear and Volatility in Digital Assets," Papers 2010.15611, arXiv.org.
    • Handle: RePEc:arx:papers:2010.15611
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    File URL: http://arxiv.org/pdf/2010.15611
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    References listed on IDEAS

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    1. Afees A. Salisu & Aviral Kumar Tiwari & Ibrahim D. Raheem, 2018. "Analysing the distribution properties of Bitcoin returns," Working Papers 058, Centre for Econometric and Allied Research, University of Ibadan.
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