Satisfaction with status quo has never been a defining paradigm for the founders of Turing. Their level of creative expertise and willingness to push into previously uncharted territory has allowed them to devise breakthrough solutions that were, candidly, considered unachievable by established 'experts' at the time.


A principal component of Turing's industry changing technologies includes its Hercules System, a first-of-its-kind technology that accurately replicates the security holdings and portfolio weights of public mutual funds on a real-time basis.

Residing in Turing's database are replicated holdings of more than 1,000 actively managed mutual funds, from 280+ fund firms, and reflecting $4+ trillion in fund assets under management. Turing has the capacity to accurately replicate more than 2,000 mutual funds.

Turing has proven through independent analysis that the Hercules System's fund replication accuracy is an order of magnitude improvement over any other replication technology in the industry, with an average correlation between the funds' NAVs and Turing's replicated versions of 99.4%.

The Hercules System is not an ‘algorithm', but rather a series of interlocking algorithms and integrated data cleansing and quality control technologies that, on a real-time basis, replicate daily holdings of US equity funds using only public information. The solution is a continuous, dynamic, sequence of daily portfolio securities and weights that collectively represent the actual performance of the fund.


'Traditional' active management, defined simply as a single investment manager or team, with a single investment philosophy and approach, delivered through a single vehicle/fund, has proven to be insufficient based on decades of hard data. Currently, there are $10+ trillion in 'traditionally' managed, active investments within US equities alone. On average, these assets have underperformed, resulting in a massive financial shortfall for investors in the hundreds of billions of dollars.

Turing's lead solution is an AI- and Machine Learning-based improvement of active investment management known as Ensemble Active Management, or EAM. EAM can best be described as the consensus best stock picks of a dozen elite managers. EAM has been described as starting where traditional active managers end.

EAM relies on the massive information advantage that is borne out of the Hercules System and its ability to look inside up to 2,000 actively managed funds, as well as the power of Ensemble Methods, a 40-year proven branch of mathematics and Machine Learning. Ensemble Methods is used by countless industries to improve the accuracy of predictive algorithms or predictive engines by mathematically identifying areas of agreement across multiple predictive engines.

The good news is that traditional active managers do have stock selection skill. However, proven structural flaws in the approach and delivery of these products impairs and dilutes any investment value-add. EAM is literally built from the ground up to solve these structural flaws, and to deliver investment solutions that are tangibly superior to traditional active management across both key performance and risk management criteria.

A soon to be released White Paper evaluated EAM Portfolios versus traditional active management. The White Paper created 60,000 random portfolios of mutual funds, and then 60,000 corresponding EAM Portfolios. This included 400+ mutual funds, from 142 fund families, and represented $3 trillion in fund assets. The key results showed that:

  • EAM Portfolios outperformed traditional active management 76% of the time over rolling one-year periods, growing to a 97% success rate over 7 years.
  • The annual excess return generated was a very stable 4.5% to 5.3% over rolling 1-, 3-, 5-, and 7 year periods. (For reference, the annual excess return means that if the underlying funds generated a 10% return for a given year, the EAM Portfolios would have on average generated at least a 14.5% return.)