July 6, 2018
In this edition of A View from the Mountain, we report that despite enhancements to our models in past years and despite significant changes in external risk model definitions, the McKinley Capital portfolios remain consistently exposed to Growth and Momentum factors. We deploy both return correlation as well as factor exposure information herein as supporting evidence.
Why do institutions hire asset managers?
Many types of asset managers hold the promise of positive active returns, portfolio returns in excess of the benchmark returns. Mangers differentiate themselves by producing returns that are relatively uncorrelated with other managers. It is relatively easy to think that “Value” managers, traditionally using a low P/E multiple, may be uncorrelated with “Growth” managers that have traditionally used analysts’ revisions or long-term forecasts of earnings. There are “Value” quadrants and “Growth” quadrants to the Zephyrs report that traditionally have been used to access the “style” footprint of managers. A Zephyr report is a four quadrant chart the reports how the portfolio returns compare to its benchmark on the basis of style and size. A portfolio residing in the upper quadrants of the chart show the portfolio has larger-capitalized stocks. Portfolios plotting in the right quadrants of the Zephyr report denote Growth style portfolios. Most McKinley portfolios reside in the upper-rightside box, stocks tend to be larger and are Growth-oriented. In other words, our exposures procedures returns that are most highly correlated with larger Growth stocks then with stocks that have other exposures.
If a manager is hired to produce a growth footprint, then it is important that the manager produce portfolio returns that are reported in the growth quadrants on the returns-based Zephyr report. Do we, at McKinley Capital Management, MCM, believe that a Zephyr Report Growth footprint is important? Yes, we do. The Zephyr report plot shows that portfolio holdings are consistent with our Global Growth mandate. Our portfolio returns are almost always uncorrelated (less than 0.30) with most asset managers’ portfolio returns. For the record, the low P/E approach need not be a necessary and sufficient condition of a Value manager because earnings are often cyclical, which substantially changes the stock P/E. The MCM portfolios should plot on the growth side (right side) of the Zephyr report. Our clients do not expect our portfolios to become more value-oriented.
In practice, managers that change sides of the Zephyr report are referred to as having “style drift.” MCM, since its inception, has promised institutions that our portfolios returns would be “in the [Zephyr report Growth] Box.” Have they been? Yes! We supply evidence in this report for the past fourteen years that our Non-U. S., Global and Emerging Markets portfolios, some 95 percent of MCM assets under management, plot in the Growth Box.
Data is very important to Quants and quantitative modeling.
Data is the most important ingredient for growth investing and in regards to style based factors, but data has become lately more difficult to digest. For example, Is the data of Value, Core and Growth benchmarks exclusive? That is, are there stocks in a growth index that are have negative exposures to a growth factor model? Yes! Bayer AG, BAYER GR, a stock MCM does not own, currently has a -.96 exposure to Axioma Medium-Term Momentum factor, a -.18 exposure to the Axioma Growth factor, and a -.42 exposure to the Axioma Value exposure. Bayer is not a Growth, Momentum, or Value stock according to Axioma, a risk model specialist. The point is that stocks, and thus, managers are no longer exclusively Growth or Value by Axioma’s definition, which complicates manager research. On the other hand, keeping a focus on whether a manager has changed investing philosophy or footprint can and should be the required hurdle.
Risk models change over time.
Different factors are added, such as Profitability, other risk factors are re-estimated such as Growth and Momentum, and estimation universes tend to expand across securities. Academics examine changing asset pricing models, see Barillas and Shanken (2018), as do practitioners and risk model vendors such as Axioma, with its AXWW4 World-Wide Equity Factor Risk Model. When McKinley Capital Management, MCM, says it is a Global growth specialist, then our clients expect us to have positive and large exposures to Axioma Growth and Medium-Term Momentum Risk Factors. Clients hired us to be a growth manager and be lowly correlated with value managers. McKinley Capital has held several Horse Races during the past 8 years in which a set of public models, not our proprietary models, are given to researchers and vendors and portfolios are constructed to maximize the Geometric Mean, Information Ratio and Sharpe Ratio. The Horse Races help ensure that we use the best software available. APT and Axioma have won the MCM Horse Races. McKinley Capital for the past seven years has created “public”, non-proprietary models of expect returns that we shared with risk model vendors and portfolios are constructed, and evaluated, to maximize the Information Ratio, the portfolio excess return divided by the portfolio tracking error, and the Sharpe Ratio, the portfolio excess return divided by its standard deviation. McKinley runs the Horse Race to ensure that our portfolio software maximizes the Information Ratio and Sharpe Ratio, which will enhance client returns. In late 2017, Axioma, the vendor that we use to construct portfolios because of its Horse Race performance and its integration with the ITG cost curve data, announced a major change to its Global Risk Model, including Profitability and reestimating its Growth Risk Factor. As a Global Growth Specialist, MCM had to run a series of portfolio simulations to reassure ourselves, and our clients, that our portfolio construction process would maintain our place among Growth managers. We report that MCM portfolios lie in the Growth quadrants of the Zephyr reports for our Non-U.S., Global and Emerging Markets portfolio for the 2003-21017 and 2010-2017 time periods. What is our message? Be careful, Growth and Value index benchmark stocks are not exclusive with respect to factor exposures and risk models change. However, the MCM portfolio footprints remain consistent.
As a refresher, in June 2006, McKinley Capital Management, in its “An Assessment of a McKinley Capital Enhanced EAFE Growth Portfolio: A Review of the factors, Returns, and Implementation” White Paper, introduced its McKinley Quant (MQ) variable. The White Paper described Levels I and II tests. A Level I test was completed on the factors that provid an analysis of the information coefficients and resulting t-statistics. A Level II test was conducted on the factors when used together within a set of construction rules that mimic the McKinley Capital construction process. The process passed both tests and was statistically significant at the 5% confidence level. Returns and risk characteristics were examined relative to the McKinley Capital Non-U.S. Growth Portfolio as well as the MSCI EAFE Growth Index and compared favorably to both. Lastly, independent analysis confirmed the reasonableness of the results relative to real world portfolio construction. The following observations about the new Enhanced EAFE Growth Portfolio can be drawn:
- As would be expected for a quantitative-oriented investment process, substantial benefit is missed due to the long-only constraint.
- This portfolio offering uses the same investment process and has the same general risk exposures as all other McKinley Capital portfolios, that is, exposure to Momentum, Growth, and Selection.
- The portfolio provides both a consistent and long-term risk/return profile.
A Level III test, Data Mining, was added to White Papers in 2007. In the eleven years post-MQ development, the McKinley Capital Quantitative Research Department, has monitored the model development to assure MCM clients that their portfolios will be consistent with our Global Growth Specialist mandates. That is, MCM portfolios should produce exposure to Momentum, Growth, and Selection. In this View From the Mountain we specifically address MCM portfolios and specifically examine their characteristics that are consistent with a Global Growth specialist.
In June 2006, MCM used APT to create its optimized portfolios. McKinley Capital tested the effectiveness of APT in its Horse Race competitions, in which it initially outperformed its domestic competitors, see Guerard Gultekin, and Xu (2012). APT, FinAnalytica and Axioma were virtually tied in the Global test, see Guerard, Rachev and Shao (2013) for APT and FinAnalytica results and Saxena and Stubbs (2013) for Axioma results. MCM moved to Axioma in 2015 because of its integration with ITG transactions costs curves. APT and Axioma have statistically-based risk models. APT is exclusively statistically-base. In the King’s English, a statistically-based risk model uses principal component analysis, PCA, to create uncorrelated (orthogonal) factors. In Axioma, the MCM portfolios look almost exactly like the market on the basis of 15 estimated factors.
In February 2018, MCM updated its MQ Model simulations in several products, both with Broad (Core) and Growth universes. While we frequently monitor our models, we specifically reexamined them in February 2018 because Axioma implemented its new World-Wide Global Risk Model, version 4, that included a Profitability Risk Factor. We updated our Non-U.S. (XUS) portfolio testing versus the MSCI All Country World ex U.S. (XUS), MSCI All Country World Growth ex U.S. (XUSG); Global (GL) portfolio testing versus the MSCI All Country World (ACW), MSCI All Country World Growth (GLG); and Emerging Markets (EM) portfolio testing versus the MSCI Emerging Markets (EM), MSCI Emerging Markets Growth (EMG) indexes. MCM tested its models for the long-term, LT, 2003 – 2017 and short-term, ST, 2010 – 2017 time periods. Our simulated portfolios continue to plot in the Growth box of the Zephyr reports for both long-term, 2003-2017, and post-GFC, 2010-2017, time periods.
Profitability has been added to academic risk models for at least 7-8 years, see Barillas and Shanken (2018). The Axioma Profitability Risk Factor includes the Return on Equity (ROE), the Return on Assets (ROA), Cash Flow to Assets and Sales to Assets. The Axioma AXWW4 Risk Model includes the estimated earnings-to-price variable, which is a component of our MCM forecasted earnings acceleration model. In fact, the original BARRA Risk Model contained an ROE variable in its Index of Immaturity and Unsuccess, see Rudd and Clasing (1982). Despite the announced major change to the Axioma Global Risk Model, including Profitability, and re-estimating its Growth Risk Factor, the results of the portfolio simulations reassure ourselves and our clients that, from a holdings based perspective, our portfolio construction process maintains our place among Growth managers. Our portfolios are Global Growth strategies.
|Universe: ACW xUS|
|Universe: ACW xUSG|
- MQ is statistically significant in Active Specific, and Momentum Returns in the XUS, GL and EM universes in the 2003 – 2017 time period using both Axioma World Wide Global Risk Models OLD (Version 2) and NEW (Version 4). See Table 1 for the XUS Growth portfolio attributions with the OLD and NEW Models. The Active and Specific Returns and Information Ratios rise with the NEW Risk models.
- The short-term period, 2010-2017 MCM Models, MQ, are statistically significant in Active Specific, and Momentum Returns in the XUS, GL,and EM universes.
- The MQ XUS growth portfolio has little, if any “style drift.” The XUS Growth Portfolio (Medium Term) Momentum exposures are positive, 0.30 – 0.40 and produce highly statistically significant Factor Contributions, with Medium Term Momentum contributions exceeding 225 basis points, annually, with t-statistics exceeding 4.75. The XUS Growth Portfolio Growth exposures are positive, 0.10 – 0.20 in the OLD Risk Model and produce statistically significant Factor Contributions in the OLD Risk Model, with about 30 basis points of Factor Contributions with t-statistics exceeding 3.90. The XUS Growth Portfolio Growth exposures are positive, 0.10 – 0.15, in the NEW Risk Model and produce statistically insignificant Factor Contributions in the NEW Risk Model, with about 3 basis points of Factor Contributions with t-statistics less than 1.00. The XUS Growth Portfolio Profitability exposures are positive, 0.40 – 0.50 and produce highly statistically significant Factor Contributions, about 100 basis points, annually, with t-statistics exceeding 7.80.
- The MCM XUS, GL, and EM Growth and Core Portfolios in the Growth Box of the Zephyr report in long-term and short-term periods with OLD and NEW Risk Models. There is, and has been, no style drift at McKinley Capital since 2006.
- Despite the fact that the MCM definition of growth, E’, is very different than the Axioma definition of growth, had we used the MCM forecasted earnings acceleration variable, E’, rather than MQ, to construct portfolios, the portfolios would still be in the Growth box. The reader is referred to Gillam, Guerard, and Samorajski (2017) for the discussion of the MCM Growth measure.
Axioma Robust Risk Model Version 4 Handbook. October 2017.
Barillas, F. and Shanken, J. (2018). Comparing asset pricing models. Journal of Finance 73, 715-755.
Connor, G., L. Goldberg, and Korajczyk, R. (2010). Portfolio Risk Analysis. Princeton: Princeton University Press.
Guerard Jr., J. B., Xu, G., & Gultekin, M. N. (2012). Investing with momentum: the past, present, and future. Journal of Investing 21, 68-80.
Guerard Jr., J. B., Rachev, R. T., & Shao, B. (2013). Efficient Global portfolios: big data and investment universes. IBM Journal of Research and Development 57, No. 5, Paper 11.
Guerard, J.B., Jr., Markowitz, H.M., & Xu, G. (2015). Earnings Forecasting in a Global Stock Selection Model and Efficient Portfolio Construction and Management. International Journal of Forecasting, 31, 550-560.
Markowitz, H. M. (1959). Portfolio Selection: Efficient Diversification of Investment. New York: Wiley.
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Saxena, A., & Stubbs, R. A. (2012). An empirical case study of factor alignment using the USER model. Journal of Investing 21, 25-44.
Sivaramakrishnan, K., & Stubbs, R. A. (2013). Improving the investment process with a custom risk model: a case study with the GLER model. Journal of Investing 22, 129-147.
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