Comparing Historical, GARCH, and Implied Bitcoin Volatility

Summary

The paper compares three ways to characterize Bitcoin volatility: historical volatility measured by sample standard deviation, conditional forecasts from GARCH-type models, and implied volatility derived from Bitcoin options. It uses these measures to examine how observed variation, model-based expectations, and options-market pricing relate. The study reports that all three approaches indicate high expected volatility on both daily and annual horizons, though the excerpt gives no specific values or evaluation period.

The authors caution that options-market liquidity is limited. This can make implied volatility less reliable, especially for options far from the money or with extreme maturities, and may cause it to differ from other measures. The comparison helps frame the distinct information each measure may convey, but the excerpt does not specify forecasting accuracy tests, model details, or how the measures performed against realized volatility. Its conclusions are therefore descriptive, and the implied-volatility findings should be interpreted with the stated liquidity constraint in mind.

Key ideas

• Historical volatility, GARCH-type forecasts, and options-implied volatility capture different views of Bitcoin risk.
• The study reports high expected volatility across the methods it examines.
• Limited liquidity in Bitcoin options can distort implied-volatility estimates.
• Implied-volatility estimates may be especially problematic for extreme moneyness or maturities.

Tags

# Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches


# Forecasting Bitcoin Volatility: A Comparative Analysis of Volatility Approaches









This paper conducts an extensive analysis of Bitcoin return series, with a primary focus on three volatility metrics: historical volatility (calculated as the sample standard deviation), forecasted volatility (derived from GARCH-type models), and implied volatility (computed from the emerging Bitcoin options market). These measures of volatility serve as indicators of market expectations for conditional volatility and are compared to elucidate their differences and similarities. The central finding of this study underscores a notably high expected level of volatility, both on a daily and annual basis, across all the methodologies employed. However, it's crucial to emphasize the potential challenges stemming from suboptimal liquidity in the Bitcoin options market. These liquidity constraints may lead to discrepancies in the computed values of implied volatility, particularly in scenarios involving extreme moneyness or maturity. This analysis provides valuable insights into Bitcoin's volatility landscape, shedding light on the unique characteristics and dynamics of this cryptocurrency within the context of financial markets.

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.