EAM is a quantitative solution that captures high conviction stock ideas that are identified by combining the Alpha Engines (not the Beta Anchors) from multiple, independent investment strategies. It uses the Machine Learning discipline of Ensemble Methods to identify those stocks with the highest level of consensus agreement among the various Alpha Engines, and creates a new “super‐charged” Alpha Engine that can exist without a Beta Anchor.

The risk management benefit arises from integrating the Alpha Engines of multiple investment strategies, which effectively diversifies the biases unique to each individual strategy. This approach can be utilized as an alternative to what is normally referred to in the institutional market as a multi‐manager approach. Rather than at the manager level, EAM creates diversification at the investment process level. This added layer of diversification functions the way that diversification should — by reducing risk. Using the output created by this quantitative approach, an EAM Portfolio can theoretically be constructed as 100 percent Alpha Engine.

The CFA Paper provided useful data supporting the EAM concepts, while a separate but affiliated White Paper (“Ensemble Active Management – the Next Evolution in Investment Management” — currently available for downloading free of charge at ensembleactivemanagement.com.) provides a massive data set that tests EAM concepts. The latter included the creation of 30,000 unique EAM portfolios, 165 million data points, and covered more than a decade of time. The results were exactly in line the expectations that had been built.  EAM Portfolios:

• Outperformed the S&P 500 72 percent of rolling 1‐year periods, with an average annual excess return of 3.4 percent (340 basis points);

• Achieved a 94 percent success rate versus the S&P 500 for rolling 3‐year periods, with an average annual excess return of 3.8 percent (380 basis points).

Institutional investors have faced serious challenges in finding new and effective sources of return for their Funds for years now. Lower average annual returns from public markets, combined with historically low interest rates, have driven them to seek return from non‐traditional asset classes, typically at a higher risk level relative to traditional asset classes. Ensemble Active Management could be an ideal application for institutional investors of all sizes and types.

The plans cited in the previously referenced Milliman study cover the retirement benefits of more than 25 million American workers. The unfunded liability of these plans as of June 30, 2017, was estimated to be an astounding $1.4 trillion. From my experience with plan sponsors, the negative implications of sub‐par Funding Ratios are profound. For example, some states are facing downgrades in their bond ratings due to the unfunded liability in their state pension plans. A recent WSJ article by Sarah Krouse stated: “Certain pension funds face the prospect of insolvency unless governments increase taxes, divert funds or persuade workers to relinquish money they are owed.” (Source: Sarah Krouse, WSJ, “The Pension Hole for U.S. Cities and States Is the Size of Germany’s Economy”, July 30, 2018.) And in what can only be described as ironic, many states have had an increase in salaries of teachers or other state employees, which immediately triggers an escalating increase in future benefit liabilities that can further reduce funding ratios.

Which is where EAM Portfolios come in. Based on the information provided, a typical EAM Portfolio has 40–50 stocks with a standard deviation 5­–7 percent greater than the benchmark, is completely liquid, has a fully transparent process, the fund’s custodian controls the assets, there are no derivatives, and all holdings are within the benchmark — an ideal profile for institutions. Equally attractive, an EAM Portfolio can potentially be built and tested by nearly any institutional investor at low cost, and with virtually no adverse portfolio exposure.

For example, an EAM portfolio can be built (there are firms that can assist with this) and run that portfolio for 6–12 months. If it fails to live up to expectations, the EAM Portfolio can be easily converted into an index fund through a transfer in kind process at any time.  Even a performance result at the tail end of the expectations (remember that EAM portfolios have an additional layer of diversification supporting risk management) should have a de minimis impact on the overall portfolio.

But if the EAM Portfolio is able to deliver excess returns versus the benchmark at a level even close to the White Paper’s results (340bp annual excess return, superior Sharpe Ratios), then the Investor has found a new, persistent alpha source that can — and should — be expanded throughout their investment portfolio.