Predictive Strength

Negligible
Bitcoin historically had -6.82% 30 days returns when Implied Volatility (3 Months) was▆ Very Low (0 - 0.2). It indicates negative expected returns.
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BTC Price with Implied Volatility (3 Months)

Factor Plot

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▆ Very Low▆ Low▆ Moderate▆ High▆ Very High

Predictive Strength

Negligible

Implied Volatility (IV) is 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.

High Implied Volatility: Traders anticipate larger price swings, and it 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.

Potential Edge

Forward-Looking Sentiment Capture

IV reflects the market's collective expectation of future price turbulence, incorporating insights from sophisticated traders and institutions. Unlike historical volatility, which lags, IV prices in anticipated catalysts (e.g., regulatory shifts, macroeconomic events, or protocol upgrades) before they materialize in spot prices. For example, a sudden IV spike might signal insider positioning ahead of news, while suppressed IV could indicate complacency before a volatility surge.

Contrarian Signal at Extremes

IV tends to peak during panic sell-offs and trough during periods of greed, creating contrarian opportunities. Elevated IV often coincides with market bottoms (e.g., fear-driven put buying), while depressed IV may precede corrections as traders underestimate tail risks. This cyclical pattern mirrors traditional markets, where "buy when there's blood in the streets" strategies exploit fear premiums.

Read more about our methodology

Track this predictive factor on your dashboard

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Scatter plot - Implied Volatility (3 Months) and BTC 30 and 90 Day Average Returns

Backtest - Strategy Performance

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To understand a predictive factors predictive power, we create a simple long/short strategy and simulate its past performance (with daily rebalancing):

  • 100% Long when the predictive factor is close to 1, with a position size equivalent to the predictive factor value.
  • Flat when the predictive factor is close to 0, with a position size equivalent to the predictive factor value.

The strategy is rebalanced daily, on a continuous basis. There are 0.5% transaction costs applied on each position adjustment.

API

Get started by validating the historical performance of the strategy with our transparent code snippets.
Copy and paste the code snippets below into your Python environment or download the files below.

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Our Methodology