Predictive Strength

Negligible
Polkadot historically had 9.21% 30 days returns when Open Interest (Aggregate) was▆ High (0.6 - 0.8). It indicates higher than average expected returns.
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DOT Price with Open Interest (Aggregate)

Factor Plot

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

Predictive Strength

Negligible

Aggregate Open Interest aggregates and standardizes open interest data across leading global exchanges, including futures, options, and perpetual swaps, offering insight into liquidity trends.

Potential Edge

Macro Capital Flow Tracking

Aggregate OI acts as a real-time ledger of global speculative capital entering/leaving derivatives markets. Sustained increases signal institutional-grade liquidity injections. This metric filters out noise from isolated exchange anomalies, revealing cross-platform consensus about trend conviction.

Leverage Cycle Early Warning

Extreme OI levels (2+ standard deviations above mean) historically precede volatility spikes. The March 2024 BTC drawdown saw OI drop 22% alongside price, flushing overleveraged positions – a reset that enabled April's rebound. Monitoring aggregate OI helps identify overheated markets before forced liquidations cascade.

Data Collection Methodology

Open Interest (Aggregate) data is sourced by aggregating raw open interest values from leading exchanges, converting all positions to a standardized USD notional value (including futures, options, and perpetual swaps). This involves normalizing the data relative to historical averages, where a value of 1 indicates higher-than-average liquidity and 0 represents lower-than-average levels.

Read more about our methodology

Track this predictive factor on your dashboard

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Scatter plot - Open Interest (Aggregate) and DOT 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