The VIX of Crypto and How Options Data Predicts BTC Price Swings

In-depth analysis of the counter-intuitive relationship between Implied Volatility and future Bitcoin returns.

The interactive version of this report can be found here; our previous report on exchange outflows’s predictive power here.

With investor sentiment and risk premiums encapsulated in its options data, Bitcoin’s implied volatility is becoming an interesting predictive factor with its dual role as a fear gauge and a proxy for speculative behavior.

Implied Volatility (IV)—a metric derived from options that reflects market expectations of future price movement — is calculated by reverse-engineering options pricing models to determine the volatility level that justifies current market prices for derivatives.

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For Bitcoin, this metric encapsulates collective expectations:

• High Implied Volatility: Traders anticipate larger price swings, often driven by events like regulatory shifts, macroeconomic instability. Larger volatility is traditionally associated with prices falling.

• Low Implied Volatility: Market participants expect relatively mild price fluctuations over the near term. This typically translates to lower options premiums, as traders price in a period of reduced uncertainty and risk.

A prolonged period of low IV might also suggest market complacency, where potential risks or future shocks are being underestimated. We can confirm this empirically — low implied volatility is associated with lower future BTC returns, opposite to what theory would dictate.

At the bottom, we plotted “Predictive Correlation”, the rolling Pearson correlation coefficient between the factor and 90 Day BTC forward returns.

Let’s have a look at what happened to BTC in the next 30 days when normalized Implied Volatility was low (yellow) or high (blue).

The chart shows that high values of the index (blue) led to larger subsequent 30 day BTC returns. Another lens to look at the same data can be found below.

We also developed “Predictive Score”, which measures the ability to successfully translate a leading indicator into a simple quantitative strategy - it is a more actionable measurement of “predictiveness”, appropriate to the noisy environment of financial markets. The motivation behind it is to understand which signals truly matter, and help filter out the noise.

Using it, we can look at how predictive Implied Volatility was historically, and track its effectiveness as a leading indicator over time.

Counterintuitive Results

Implied volatility seems to act as a contrarian indicator, reflecting the unique dynamics of Bitcoin markets, where periods of higher realized volatility tend to coincide with stronger returns — a stark contrast to traditional equities, where elevated volatility is more often associated with declining performance.

Implied Volatility’s forward-looking nature allows it to capture shifts in investor expectations before they materialize in spot prices. Our research comparing IV and (Realized Volatility) RV reveals that when IV exceeds RV, it often signals impending market stress. We’ll explore this in an upcoming article.

The interactive version of this report can be found here, and our previous report on exchange outflows here.