RAM Active Investments launches the RAM Diversified Alpha Strategy (UCITS)

Geneva, 11 November 2020 - RAM Active Investments SA ("RAM AI"), a systematic asset manager based in Geneva, is launching the RAM Diversified Alpha strategy which will seek to deploy a robust and stable systematic investment process to exploit volatility and dispersion within a broadly diversified global asset allocation, with the intention of offering asymmetric returns that have low correlation to global markets.

“Technological innovation is a key component of the portfolio construction methodology”, explains Maxime Botti, Founding Partner & Senior Fund Manager at RAM AI who heads the systematic macro team formed by Philippe Huber and Tony Guida, Fund Managers and Researchers. “We used a similar methodology than our Alternative Investment Fund strategy which has the objective to provide uncorrelated returns to mainstream asset classes over the medium-term”.

The strategy aims at acting as a real diversifier in a global asset allocation by seeking to deliver absolute returns, not only during normal market conditions but also when it is the most needed during market jolt periods.

The approach to dispersion modelling is agnostic and adaptive. RAM AI models the relationships between liquid assets by analysing them on a relative basis and through multiple dimensions. RAM AI’s expansive and evolving computational capabilities allow to analyse on an ongoing basis a large amount of data to identify the most profitable strategies across time frames spanning from short to long-term.

“Relying on techniques borrowed from natural sciences for solving multi-dimensions problems, the use of genetic algorithm that replicates evolution allows our models to select the fittest alphas, making the overall strategy more robust” adds Philippe Huber.

“As financial markets change (less independent, central banks interventions, etc.), so does our model” shares Tony Guida. The strategy benefits from a robust process of alpha creation and selection; alphas are reassessed several times per year to take into account evolving market conditions.

The strategy is available in a UCITS format as of the 11th of November 2020 to investors in France, Finland, Germany, Italy, Luxembourg, Norway, Portugal, Sweden, Switzerland and United Kingdom.

About the team

Philippe Huber joined RAM AI in 2017 as a Senior Quantitative Analyst to work on the development of systematic investment strategies. In 2020, he became Fund Manager of the RAM Diversified Alpha and continues his focus on the development of a proprietary suite of back testing and non-traditional optimisation tools in Cuda/C++ to run on GPUs.
Philippe is an award-winning PhD in Econometrics and Statistics (University of Geneva, 2004), a graduate of the EPFL (MSc, Physics, 1998) and a graduate of the University of Geneva (MSc, Econometrics and Statistics, 2001).

Tony Guida joined RAM AI in 2019 as a Senior Quantitative Researcher and became Fund Manager of the Diversified Alpha in 2020. His work focuses primarily on extracting market inefficiencies from different sources from traditional fundamentals, market signals, alternative data, and machine learning. His expertise is in mid to low frequency in equities. Tony started his career at Unigestion in the quantitative equity low volatility team and later became a member of the research and investment committee for Minimum Variance Strategies, where he led the factor investing research group for institutional clients. In 2015, he moved to Edhec Risk Scientific Beta as a Senior Consultant for Risk allocation and factor strategies before going to a major UK pension fund in 2016 to build the in-house systematic equity, co-managing 6 billion GBP as a senior quantitative portfolio manager.

Philippe and Tony have a number of publications under their names in some of the best academic research journals, including the recently published “Genetic Algorithms: A heuristic approach to multi-dimensional problems”.