Fund Dashboard

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Portfolio Construction:

Top Quarterly Trades:

BlockTerra Research

Our Trade Process

Data

BlockTerra Capital uses an extensive database to inform our trade decisions. Fundamental and sentiment data is gathered from exclusive providers and BlockTerra’s proprietary sources

Signal Generation

This data is then used to generate fundamental and sentiment signals. Signals are added or removed from the model statistically determining whether the model has improved accuracy and performance. Signals are extensively tested to ensure that the data has external validity.

Risk Management

Our model utilizes deep reinforcement learning to optimize the Sharpe ratio and minimize any potential volatility. The model is created to have a lower volatility and beta than comparative strategies.

Improvements

Model constantly iterates and improves on new data utilizing cutting-edge machine learning. Signals are continually tested to create statistical advantages. New signals are constantly being backtested and add/removed based in results.

Our Strategies

Volatility Driven

Utilizing derivative contracts BlockTerra builds strategies to profit from volatility. Betting directly on the implied volatility, BlockTerra is able to benefit from the change in volatility no matter the direction via straddle and spread positions.

Predictive Algorithms

BlockTerra utilizes best-in-class proprietary algorithms that predict the future behavior of digital assets based on a combination of past information, new information, and other second-order information. Some of these algorithms include mean reversion, trend following, and chart pattern recognition.

Event Driven

Events can temporarily inflate or deflate a digital asset price while the market attempts to judge and value these newest developments. BlockTerra identifies the core issues and what will resolve it, as well as the ability to determine individual performance relative to the market in general.