Bitcoin Volatility Asymmetry and Market Efficiency Change Over Time

Summary

This study examines daily Bitcoin returns using rolling windows to track volatility asymmetry and multifractal behavior as market properties change. It reports an inverted volatility asymmetry whose strength varies over time and has recently become small. The asymmetry is also observed in higher-frequency returns. Other distributional and dependence measures, including kurtosis, skewness, average returns, serial correlation, and multifractal degree, are likewise described as time-varying.

The analysis relates volatility asymmetry to efficiency measures, including the Hurst exponent, multifractal degree, and kurtosis. The reported pattern is that measures associated with greater market efficiency coincide with weaker volatility asymmetry; the authors characterize the recent market as more efficient on both counts. The document does not specify the rolling-window choices, sample period, or statistical uncertainty, so the reported evolution should not be treated as a stable forecasting rule or evidence of a tradable effect.

Key ideas

• Rolling-window analysis is used to track changing Bitcoin return and volatility properties.
• The study reports inverted volatility asymmetry, with a magnitude that changes over time.
• Volatility asymmetry is also reported in higher-frequency returns.
• Efficiency-related measures tend to coincide with weaker volatility asymmetry in the study.
• The findings describe evolving market statistics but do not establish a forecasting strategy.

Tags

# Time-varying properties of asymmetric volatility and multifractality in Bitcoin


# Time-varying properties of asymmetric volatility and multifractality in Bitcoin









This study investigates the volatility of daily Bitcoin returns and multifractal properties of the Bitcoin market by employing the rolling window method and examines relationships between the volatility asymmetry and market efficiency. Whilst we find an inverted asymmetry in the volatility of Bitcoin, its magnitude changes over time, and recently, it has become small. This asymmetric pattern of volatility also exists in higher frequency returns. Other measurements, such as kurtosis, skewness, average, serial correlation, and multifractal degree, also change over time. Thus, we argue that properties of the Bitcoin market are mostly time dependent. We examine efficiency-related measures: the Hurst exponent, multifractal degree, and kurtosis. We find that when these measures represent that the market is more efficient, the volatility asymmetry weakens. For the recent Bitcoin market, both efficiency-related measures and the volatility asymmetry prove that the market becomes more efficient.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.