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Measures the assets' overall share of all conversations about crypto.
Investor attention demonstrably precedes Bitcoin returns and volatility, acting as a predictive factor. Studies show attention metrics (Google Trends, social volume) Granger-cause price movements, with predictive accuracy improvements of 20% over baseline models in out-of-sample tests. This aligns with behavioral finance principles where attention drives retail investor inflows before institutional actors react.
For smaller-cap assets, attention directly impacts liquidity. A 10% increase in conversation share reduces idiosyncratic risk by improving market depth and narrowing bid-ask spreads. This creates a self-reinforcing cycle: rising attention → improved liquidity → reduced volatility → sustained attention.
The Attention Index sources data from social media platforms, forums, and crypto-related websites to track conversation volumes about specific assets. These inputs are aggregated and normalized against historical averages to determine relative attention levels, with maximum score of 1 indicating heightened interest compared to past trends.
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Benchmark (Ethereum) | Strategy | |
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100% | 100% | |
100% | 100% | |
1.00 | 1.00 | |
100% | 100% | |
1.00 | 1.00 | |
1.00 | 1.00 |
Predictive factors are designed to be translated into simple long-only strategy, with simulated past performance:
The strategy is rebalanced daily, on a continuous basis. There are 0.5% transaction costs applied on each position adjustment.
Get started by replicating the historical performance with our code snippets.