Machine Learning for digital assets and prediction markets

Our machine learning software detects capital flow in BTC markets and anticipates the market maker's response trained over 9 years of combined exchange data.

The inference supplies a detailed signal: A suggested trade, take profit level, specified stake, max hold time and a stop-loss.

Current Sharpe ratio: 2.47.

We are currently trading our pre-fund capital base and establishing our tape.

Good trading teams respect money. They manage risk by cutting losers quick and have exact targets. This is the ethos we subscribe to.

Riptide models capital flows and the market maker response with precision accuracy. We understand the mechanical path capital must take as the market evolves

Our goal is to trade digital asset volatility intelligently instead of guessing outcomes with black box algorithms. Market structure over gambling with money compounds over time and provides superior returns.

If you can see the current clearly, you survive the rip tide which carries other funds out to sea.

All of our machine learning models run fully automated with no downtime across the major exchanges. Our fund strategy compounds small wins on low time frames exploiting volatility with leverage alongside longer term positions in spot.

Our work is based on market structure: how smart money flow shows up, and how mechanical constraints in digital asset markets force capital to move. Market makers must adjust their spread as different takers exhibit aggression in their strategies. We detect their aggression and mark it versus orderbook density, liquidation probabilities, Options flows and the greeks and much more. Our constant goal is to achieve a consistent Sharpe ratio above 3. The following record shows where we are now.