Investment Philosophy

Quantitative Research

We deploy the capital of our clients by adopting a sophisticated proprietary quantitative research process. We apply the scientific method to analyze and test our hypotheses on vast amounts of historical in order to find signals of alpha. All the company's strategies undergo an extensive backtesting and validation process before going into production.

Disclaimer: commodity trading involves a substantial risk of loss.


We invest a substantial amount of monetary and human capital with the objective of developing a superior technological and operational infrastructure. All the code is thoroughly tested by our quantitative developers before going into production. This enables us to minimize technological issues in live production and to easily make modifications when necessary to accommodate the requirements of an investment strategy.

Risk Management

Managing all types of risks for our clients and invested capital is of primary importance to us. We developed a sophisticated risk management framework with the objective of monitoring and keeping under predefined limits various types of risks embedded in our investment portfolios.


We understand that a primary factor of success for a company resides in its team. For this reason, we always strive to attract and retain the best human talent from advanced degrees in the scientific and technological fields. When new members join our firm we always make sure that they fit into our culture and can provide a significant contribution to the improvement of our business.

Investment Process

Data Collection

In the first phase of our investment process we collect data from a variety of traditional and alternative sources. In order to maximize our chances of finding new sources of alpha, we consider multiple datasets, including financial, fundamental, macroeconomic, government, and alternative sources. This allows us to develop a deeper understanding of how financial markets work by testing our hypotheses in a more comprehensive and extensive way in the following phases of our strategy development framework.

Data Cleaning

We use proprietary automated algorithms to clean the vast amounts of data at our disposal. Thereafter, our data scientists review and check the automated cleaning procedures to make sure that the data sets are clean and can be used thereafter by our quantitative researchers.

Data Analysis

Our quantitative researchers analyze the data sets processed in the previous step using sophisticated and advanced statistical methods in order to find alpha signals. This step is a key differentiator, since alpha it is diffult to find and as a consequence it is important to have an excellent team of quantitative researcher that can identify hidden investment opportunities through vast amounts of data.


After the data has been thoroughly analyzed, our quants apply the scientific method to the financial data by testing their hypotheses though backtesting experiments on long time series data spanning multiple decades. By adopting lengthy historical datasets we reduce backtesting bias and increase the likelihood of robustness of our invesment strategies across multiple market conditions.

Pilot Test

Once our quantitative research team has found investment strategies that have performed well in backtesting, we test them in a pilot live production environment with proprietary capital for a suitable period of time before offering them to our clients. This step is very important since it increases the probability that the strategy will work as expected in real market conditions, and allows us to have the time to fix potential technological issues before live production.


Having confirmed that pilot trading returns are consistent with the backtest and what we expected, our investment team allows our clients to invest in the new investment product.

Disclaimer: these investment products involve substantial risks of loss.