Predictive Strength
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Predictive Strength
Measures the accounts that are long versus the accounts that are short.
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:
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.
Retail traders frequently act as liquidity providers to institutions:
Crypto's leverage-heavy markets magnify LSR's predictive power:
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.
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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):
The strategy is rebalanced daily, on a continuous basis. There are 0.5% transaction costs applied on each position adjustment.
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.