Predictive Strength

Negligible
Bitcoin historically had 8.78% 30 days returns when Long Short Ratio was▆ Very Low (0 - 0.2). It indicates higher than average expected returns.
Unravel

unravel

BTC Price with Long Short Ratio

Factor Plot

Unravel

unravel

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

Predictive Strength

Negligible

Measures the accounts that are long versus the accounts that are short.

Potential Edge

Contrarian Signals at Sentiment Extremes

The LSR acts as a "crowd psychology meter." Extreme long/short ratios often precede reversals because retail traders (the "herd") tend to overcrowd trades at market tops or bottoms. For example:

  • A >60% long ratio during a rally suggests euphoria, increasing liquidation risks as over-leveraged longs get squeezed
  • Conversely, <40% long ratios in downtrends signal capitulation, creating buy-the-dip opportunities
  • This aligns with historical patterns where retail traders incorrectly fade institutional momentum

Institutional vs. Retail Positioning Divergence

LSR data reveals asymmetries between informed players and speculative traders:

Institutions often accumulate during high short ratios (retail panic) and distribute during excessive long ratios.

Liquidity Provision Dynamics

Retail traders frequently act as liquidity providers to institutions:

  • Rising prices + falling LSR (e.g., BTC up 10% but longs drop to 48%) indicate pros buying into retail shorting
  • These divergences create self-reinforcing cycles where stop losses and liquidations amplify moves

Early Warning for Leverage Imbalances

Crypto's leverage-heavy markets magnify LSR's predictive power:

  • A 49.46% long / 50.54% short near-equilibrium (as seen recently) masks hidden leverage. Minor imbalances in derivatives open interest can trigger cascading liquidations
  • Platforms like Binance display real-time ratios, allowing traders to front-run anticipated margin calls

Data Collection Methodology

The Long Short Ratio is sourced by aggregating open long and short positions from crypto exchanges, primarily through margin trading or futures contracts. Data is collected from both centralized (CEX) and decentralized (DEX) platforms, though CEXs provide more reliable tracking due to centralized order books. The ratio is then normalized against historical averages to create a relative index, where values above 1 indicate higher-than-average bullish sentiment.

Read more about our methodology

Track this predictive factor on your dashboard

Unravel

unravel

Scatter plot - Long Short Ratio and BTC 30 and 90 Day Average Returns

Backtest - Strategy Performance

47.96%
1.31
-37.73%
0.46
34.33%
0.18

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.

Ready to dive in?

Be among the first to experience the cutting-edge, institutional-grade predictive analytics Unravel offers.

Our Methodology