February 28, 2019
Robert A. Gillam, CFA Chief Executive Officer McKinley Capital Management, LLC
Throughout its nearly 30-year history, McKinley Capital Management, LLC (“MCM”) has sought to improve risk-adjusted returns for its clients, and its quantitative strategies have evolved accordingly. The most recent quantitative strategy update directly impacts U.S. All Cap, the firm’s longest-standing product. Since its inception in 1990, U.S. All Cap has produced 0.77%, net, annualized excess returns above the Russell 3000 Index as of the year-ended 2018. Even during market downturns, U.S. All Cap consistently outperformed the Russell 3000 inception-to-date, and MCM believes the latest update will further augment these excess returns.
As the desire to embrace a socially responsible culture expands, investors are eager to incorporate environmental, social, and governance (“ESG”) factors into their portfolios. Traditionally, money managers restricted securities with low ESG scores from purchase, and the resulting portfolios were often suboptimal with lower returns. MCM has developed a way to incorporate these important ESG factors while still pursuing optimal portfolio risk and return characteristics.
Dr. John Guerard, head of the Quantitative Research team, is a Moskowitz Prize winner1 and has earned significant recognition in the field of Socially Responsible Investing (“SRI”). In a recent study of the Russell 1000 Universe2, Guerard and Chris Geczy of the Wharton School found that ESG/SRI portfolios have lower standard deviations of returns than unscreened portfolios. Consequently, ESG/ SRI portfolios tend to produce higher Sharpe Ratios and Information Ratios. Each strategy at MCM is built around an underlying McKinley Quant (“MQ”) score, a proprietary composite variable that includes earnings forecast revisions, price momentum, and standard deviation of returns. To a certain extent, MQ scores already incorporate ESG scores. For example, securities ranked in the top quintile for ESG have a median MQ score of 58.02, in comparison to the lowest quintile of ESG securities which have a median MQ of 44.17. The top ESG quintile also reflects outperformance in price momentum, profitability, dividend yield, size, and liquidity characteristics. Lower volatility is also commonly observed with high ESG scores when compared to the lower ESG quintiles. Overall, by investing in securities with high ESG scores, investors may gain exposure to several favorable characteristics.
MCM’s unique ESG methodology incorporates these characteristics with the goal of providing a prospect for higher future returns, despite ESG portfolios customarily underperforming. Rather than the common practice of building a portfolio solely of securities with high static ESG scores, MCM’s proprietary strategy selects securities with improving ESG scores and excludes securities with deteriorating ESG scores. As illustrated below, the highest expected returns in the hypothetical back-tested portfolios were derived from improving ESG scores combined with high MQ scores. Furthermore, additional upside capture is possible by avoiding deteriorating ESG scores, which tend to drag on returns, relative to unscreened MQ. Given these findings, MCM is incorporating a dynamic ESG variable into the U.S. All Cap quantitative strategy.
To accurately reflect this enhancement to the underlying strategy, the MCM U.S. All Cap Portfolio is being renamed U.S. Sustainable Equity. This portfolio will provide clients a prospect for superior risk-adjusted returns while incorporating social responsibility. MCM values your partnership and welcomes any questions that you may have regarding this change. Please feel free to direct your inquiries to email@example.com.
1Dr. John Guerard was awarded the Moskowitz Prize in 1996 followed by an honorable mention in 2001. The prestigious Moskowitz Prize is the only global award recognizing outstanding quantitative research in sustainable and responsible investing. Since its launch in 1996 by Berkeley-Haas and US SIF, its winners have explored shareholder activism, socially responsible mutual funds, and socially responsible investing as a catalyst to financial performance, among other topics.
2Geczy, C., J.B. Guerard, Jr., and M. Samonov. “Earnings Forecasting and Efficient SRI/ESG Portfolios”. Unpublished Working Paper. 2018. The Wharton School.
3Guerard, J.B., Jr. “Is There a Cost to Being Socially Responsible in Investing?” Journal of Forecasting, 1997, pp. 6, 11-18, 475-490.
4Momentum: total return over the last 12 months, skipping the most recent month 5ROIC: “Return on Invested Capital” =Net Operating Profit After Tax / Invested Capital. This illustrates how efficiently a company uses its capital to generate revenue.
6Dividend Yield: Annual Dividend / Share Price
7Market Cap: Current Market Price per Share * Total Number of Outstanding Shares
8Liquidity Exposure: Axioma liquidity risk factor exposure, expressed in standard deviations from the mean
9Volatility: Annualized standard deviation of daily returns over the last 252 trading days
10Market Beta: the predicted equity market beta from the Axioma risk model.
McKinley Capital Management, LLC (“McKinley Capital”) is a registered investment adviser under the U.S. Investment Advisers Act of 1940. McKinley Capital is registered with the following Canadian provinces: the British Columbia Securities Commission; the Ontario Securities Commission; the Alberta Securities Commission; and the Quebec Financial Markets Authority. McKinley Capital is not registered with, approved by, regulated by, or associated with the Financial Conduct Authority (“FCA”), the Prudential Regulation Authority (“PRA”), the Securities & Futures Commission of Hong Kong or the China Securities Regulatory Commission. Additionally, none of the authorities or commission listed in the previous sentence has commented on the firm, the content of any marketing material or any individual suitability assessments.
Back-tested results are hypothetical (do not reflect trading in actual accounts) and are prepared with the benefit of hindsight. The results are provided for informational and illustrative purposes to indicate historical performance had the model portfolio been available over a relevant period. These results are not intended to recommend trades or be considered investment advice. No representation is being made that any model or model mix will achieve results similar to that shown and there is no assurance that a model that produces attractive back-tested results on a historical basis will work effectively on a prospective basis. Not every client’s account will have the exact characteristics of the backtested portfolio. The actual characteristics with respect to any particular client account will vary based on a number of factors including but not limited to market exigencies at the time of investment. It should not be assumed that any of the investment decisions made in the future will be profitable or will equal back-tested results or current investment performance. The trading strategies retroactively applied were available during the periods presented.
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