Our models output an attractiveness score for every cryptocurrency traded on exchange. The higher the score is, the more likely is the asset to outperform the broad market in the future. Contrary, the lower the score is, the more likely is the asset to underperform broad market in the future. Clients use these scores to buy assets with high attractiveness scores and short the assets with low attractiveness scores, taking into account expected return, risk, transaction cost and AuM, constructing a portfolio that is market neutral and profiting solely from the predictable patterns in investors' decision-making.
Note: Results are based on transaction prices. Past signal performance does not guarantee future results.
We believe that investors in cryptocurrency markets follow predictable patterns in their decision-making, just like in traditional markets. Our approach turns these behavioural insights into quantitative signals.
We study how cognitive biases (fear of missing out, risk aversion, herd behaviour) drive predictable patterns in investor decision-making across crypto markets.
We rigorously test anomalies for statistical significance and evaluate their consistency across different time periods to ensure robust, lasting predictive power.
Our StatArb signal relies on over 100 anomalies that we have discovered, and we continually uncover new ones to stay ahead in the evolving crypto landscape.
Multiple ways to access our signals, designed to fit seamlessly into your existing workflow and infrastructure.
Programmatic access with real-time and historical endpoints. Integrate directly into your trading systems or research pipelines.
Scheduled or on-demand exports in standard formats, ready for analysis in Excel, Python, R or any other tool.
Automated file delivery to your secure server on a daily or custom schedule.
Need a different format or delivery method? We work with you to build a solution that fits your infrastructure.
