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Cryptocurrency Dynamics: Rodeo or Ascot?

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  • Konstantin Hausler
  • Wolfgang Karl Hardle

Abstract

We model the dynamics of the cryptocurrency (CC) asset class via a stochastic volatility with correlated jumps (SVCJ) model with rolling-window parameter estimates. By analyzing the time-series of parameters, stylized patterns are observable which are robust to changes of the window size and supported by cluster analysis. During bullish periods, volatility stabilizes at low levels and the size and volatility of jumps in mean decreases. In bearish periods though, volatility increases and takes longer to return to its long-run trend. Furthermore, jumps in mean and jumps in volatility are independent. With the rise of the CC market in 2017, a level shift of the volatility of volatility occurred. All codes are available on Quantlet.com.

Suggested Citation

  • Konstantin Hausler & Wolfgang Karl Hardle, 2021. "Cryptocurrency Dynamics: Rodeo or Ascot?," Papers 2103.12461, arXiv.org, revised Jan 2022.
    • Handle: RePEc:arx:papers:2103.12461
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    References listed on IDEAS

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