ABOUT Pegassets


Q: Who is Pegassets LLC?

A:  Pegassets LLC is a forward-looking firm dedicated to the licensing of innovative and disruptive proprietary and third-party intellectual property to the financial services industry. Current offerings are based on applying the power of Ensemble Active Management to investment solutions. Pegassets has the primary intellectual property ("IP") licensing and sub-licensing rights to Ensemble Active Management technology from Turing Technology Associates. Pegassets is responsible for the sales and sub-licensing of this IP to ETFs, Fund Managers and other asset managers.


Q: Who are the Principals of Pegassets LLC?

A: The senior managers of Pegassets are:


  • Bryan Tull, Partner of Pegassets LLC

  • Kristi Siaosi, Partner of Pegassets LLC


Both principals were consultants of Robert Tull and Company and previously focused on consulting in the ETF marketplace. 

Kathleen Neumann, CFA, serves as President of Pegassets.

Kathleen was most recently President and CCO of SerenityShares, an ESG-dedicated ETF start-up, preceded by over a decade a TAMRO Capital Partners, a small-cap equity institutional money manager where she was President. 


Q: What was the impetus for the creation of the Pegassets LLC?

A: Robert Tull of Robert Tull and Company has been focused on the ETF marketplace since 1991. Robert has been a thought leader in the ETF market and a named inventor on multiple ETF patents going back to 1993.


For years, active managers have approached Robert to provide new active investment models to active management companies as a response to the passive ETF growth. Upon learning of Ensemble Active Management and collaborating Turing Technology Associates, Robert encouraged his consultants to form Pegassets.


Q. Why will Ensemble Active Management be important to active portfolio management?

A: Today active managers are losing assets to the ETF marketplace. These negative flows are primarily caused by the inability, on average, of active managers to outperform their stated benchmarks on an after-fee basis. The management companies have made huge investment in staff, infrastructure and data analytic models to build their portfolio stock selection processes and require higher fees to cover these expenses. Investors are paying extra fees for active management but are receiving lower net returns. 


Q: Why is this new investment approach significant?

A:  Ensemble Active Management (EAM) uses machine learning, algorithms and big data analytics to remove the human biases that are inherent in each individual manager's stock selection processes. EAM uses multi-expert approach to produce the "best of the best" prediction of stocks that are more likely to exceed the returns of their stated benchmarks overtime.


Q: Who does Pegassets believe can benefit from EAM?

A: If EAM results in higher long-term returns, then the ultimate beneficiaries will be the end investors whose long-term investment performance will be improved. This includes retail investors, pension plans, foundations and endowments. Additional beneficiaries will be firms in the business of providing investment advice or products, as they stand to benefit as their clients succeed. 



Q: What are the key problems facing active management returns?

A: Over the last decade active managers have shown a very low probability of outperforming their stated benchmark returns or corresponding index funds after fees. One of the key reasons is that active managers dilute their best ideas by adding additional stocks to their portfolios in order to manage portfolio risk. While this risk management succeeds in reducing the likelihood of what is known as a toxic tail, it creates a performance penalty.

Q: How have other industries achieved success using Ensemble Methods?

A: Multiple industries utilize ensemble methods with the goal of achieving higher levels of predictive accuracy and to solve what are referred to as "glass ceiling" problems. For decades other industries have solved the problem of weak "predictors" by applying Ensemble Methods, with core components that include Artificial Intelligence ("AI") and machine learning to merge many weak predictors into a more effective "multi-expert" predictive engine to increase their success. A good example of the use of Ensemble Methods in another industry is the prediction of hurricane landfalls, where multiple predictive algorithms are combined to create a superior prediction. 


Q: How have others looked at their limited success in the current market?

A: For decades other industries have solved the problem of weak “predictors” by applying “Ensemble Methods”, with core components that includes Artificial Intelligence (“AI”), and machine learning to merge many weak predictors into a more effective “multi-expert” predictive engine to increase their success.

Q: How can you explain ensemble methods to a retail investor?

A: Ensemble Methods is a multi-expert approach and can be thought of as a mathematical search for many second opinions. Would you not seek several medical opinions to a serious medical condition?

Q: Who is bringing this technology to active management?

A: Turing Technology Associates is the original inventor of Ensemble Active Management (EAM), which is the result of applying time-tested Ensemble Methods technologies and techniques to the high-conviction stock selections of actively managed investment portfolios. Turing, along with other technologists, academics, investment and business professionals formed the research group EAM Research Consortium because they believe that Ensemble Active Management is a real and viable solution to achieving better returns. They have focused on the equity markets now as the amount of public data in this space provides the required “big data universe” Ensemble Methods needs to process in order to achieve meaningful results.


Q. What was the result of all this data and how was it presented to the market?

A. The white paper Ensemble Active Management: The Next Revolution in Investment Management is the result of the EAM research consortium's analysis of applying Ensemble Methods to active investment management. What was recognized was: * (1) that traditional active managers have failed to reliably deliver on their mandate of outperforming the market after fees; (2) the asset management industry has within its grasp the power to improve investor returns and (3) if Ensemble Active Management technology is adopted by active managers, it has the potential power to transform investment management over the next decade. This is similar in scope to the way that Exchange Traded Funds (“ETFs”) transformed passive asset management. 

* Please refer to Ensemble Active Management: The Next Revolution in Investment Management for more information and context.


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