CALCULO EVOLUTION FUND
Algorithmic commodity fund. Systematic trading strategy with artificial intelligence.
CALCULO EVOLUTION FUND is a trend following commodity fund. Strategy is executed through algorithms in order to automate the investment process and investment allocation.
The fund operate with a set of rules for calculating the trading signals and rules for filtering these signals. In addition to this systematic and static investment process, the fund make use of artificial intelligence as a mean to optimize the exit of the positions. This machine learning process will evaluate the portfolio on a daily basis and adjust the exposure according to historic observations.
The fund can benefit from both rising and falling prices in the underlying commodities. This is due to the mechanisms in the futures market, where no shorting restrictions apply.
A systematic investment process align the decision making and decouple human emotions in trading. This enable the fund to pursue investment opportunities across a broad basket of commodities.
All signals are selected by the developed algorithms. The fund make use of a filtering process to ensure that risk is adjusted and in line with the rules and maximum exposure set by the management team.
Calculo Capital operate through in house developed trading platform. Built to accommodate the trading strategy and portfolio risk management as per the developed trading strategy.
The fund operate with automatic signal generation. Automatic trade execution and automatic risk management.
Commodities offer unique opportunities for diversifying existing investment portfolios. These qualities arrive from the unique fundamentals of commodity markets.
Commodities are affected by weather, geopolitics, local events and supply / demand constraints. All non correlated towards traditional investments.
Correlation is a very important element in an investment portfolio. By combining assets with different underlying drivers (low correlation), the overall risk of the portfolio can be significantly reduced and strengthen the portfolio against cyclic corrections.