Practical Applications Summary In recent years, management of multi-asset portfolios has shifted away from conventional “asset allocation” approaches toward what might loosely be termed “risk allocation” methodologies, or “factor investing.” The factor-oriented approach presents its own set of challenges, say Mark Kritzman (Windham Capital Management and MIT Sloan School of Management), Alain Bergeron, and Gleb Sivitsky (both of Mackenzie Investments). Asset Allocation and Factor Investing: An Integrated Approach, published in the 2018 Quantitative Special Issue of The Journal of Portfolio Management, highlights some of these challenges, such as the “mapping risk” between factors (e.g., inflation or growth) and assets (e.g., bonds or equities). To preserve the virtues of both asset allocation and factor investing while minimizing their pitfalls, the authors propose a model for integrating factors with a traditional asset allocation methodology. Although the authors demonstrate their model using the macro-based factors of growth and inflation, the model could also be used to integrate views on security-based risk premia such as value, momentum, and low volatility. TOPIC:Portfolio construction

In <b><i>A Comparative Analysis of Performance Fees</i></b>, from the Summer 2018 issue of <b><i>The Journal of Portfolio Management</i></b>, <b>Megan Czasonis</b>, <b>Baykan Pamir</b>, <b>David Turkington</b> (all at <b>State Street Associates</b>) and <b>Mark Kritzman</b> (of <b>Windham Capital Management</b>) compare flat-fee structures for investment management services with performance-based fee structures. They demonstrate that determining an investor’s preference among different possible fee structures depends on the complex interplay of the fee structure, the expected performance of the investment portfolio, and the investor’s attitude toward risk. The authors argue that the appropriate approach for evaluating performance fees and comparing them with an alternative flat fee is to simulate the distribution of after-fee returns and, given a particular utility function for investors, to use the certainty equivalent of the after-fee return distribution to determine the appropriate fee structure. The authors also explain how the asymmetric nature of performance fees causes the distribution of net returns to be non-normal, even if before-fee returns are normally distributed. This can cause biased results when using tools that treat net returns as normally distributed. <b>TOPICS:</b>In portfolio management, portfolio management/multi-asset allocation

1. Mark Adelson <!-- --> 1. To order reprints of this report, please contact David Rowe at D.Rowe{at}pageantmedia.com or 212-224-3045. </br>![][1]</img> Mark Adelson Content Director Here is your Fall 2018 issue of Practical Applications (PA). This issue comprises a selection of twelve

Practical Applications Summary In When Does Capitalization Weighting Outperform? Factor-Based Explanations, from the Fall 2018 issue of The Journal of Index Investing, Roger Clarke of Ensign Peak Advisors, Harindra de Silva of Analytic Investors, and Steven Thorley of Brigham Young University weigh in on the active/passive debate from a factor-investing perspective. Specifically, they examine whether the underperformance of actively managed mutual funds relative to capitalization-weighted indexes over the past 25 years can be explained by the actively managed funds’ disproportionate exposure to specific equity market factors such as value, momentum, size, low beta, and profitability. The authors posit that the aggregate holdings of actively managed mutual funds have some similarities to an equal weighting of securities within the population of large-cap equities. This implies a significant tilt toward the size factor by actively managed funds. Such funds also currently display tilts toward the momentum and profitability factors. Together, the factor tilts explain roughly half of the underperformance of actively managed mutual funds relative to the capitalization-weighted indexes.

Practical Applications Summary In Market-Driven Scenarios: An Approach for Plausible Scenario Construction , from the Spring 2018 issue of The Journal of Portfolio Management , authors Bennett Golub , David Greenberg and Ronald Ratcliffe (all of BlackRock ) explain the need for scenario analysis as part of a firm9s overall approach to risk management and describe a framework for conducting rigorous and systematic scenario analysis. A key challenge in applying scenario analysis is constructing tail event scenarios that are severe but plausible. The authors address that challenge by providing a quantitative framework for assessing a scenario9s plausibility by reference to the behavior of observable variables used to define the scenario (e.g., asset prices, bond yields, credit spreads, etc.). Different quantitative implementations of the framework naturally produce somewhat different results, but those differences can themselves offer a vehicle for understanding the dimensions of sensitivity associated with a particular scenario definition. The authors conclude with an illustration of the framework9s application using Brexit as an example.

Practical Applications Summary CTAs: Superior Performance or Diversification Only? , published in the Spring 2018 issue of The Journal of Wealth Management , demonstrates the advantages of including managed futures in investment portfolios. Although risk-adjusted returns are shown to be somewhat weak relative to traditional asset classes, very low correlation makes CTAs a valuable addition from a Modern Portfolio Theory standpoint. The authors, Martin Florea (now at Cevian Capital), Stefan Florea (now at Morgan Stanley), Iliya Kutsarov , Thomas Maier, and Marcus Storr (FERI Trust) also demonstrate that these diversification benefits do not necessarily require (actively managed, expensive) CTAs but may be delivered by (cheaper) alternative betas.

Practical Applications Summary In Improving the System of Financing Long-Term Services and Supports for Older Americans, from the Summer 2017 issue of The Journal of Retirement, authors Mark Warshawsky and Ross Marchand (then both with the Mercatus Center at George Mason University) explore possible weaknesses of the existing framework under which seniors can qualify for long-term services and supports (“LTSS”) under Medicaid. They explain that aspects of the eligibility criteria in certain states allow seniors to draw on the Medicaid resources even if they have sufficient resources to pay for their care. The authors also discuss how states with mandates to recover assets from deceased Medicaid recipients have a poor track record of doing so. The authors assert that the market for long-term care insurance (“LTCI”) is being depressed by the ability of seniors to qualify for Medicaid LTSS benefits even when they can afford private LTCI. The authors offer several policy recommendations, including tightening Medicaid eligibility standards, narrowing the “primary residence” exclusion, and implementing a more robust estate recovery scheme.

<h3>Practical Applications Summary</h3> In <b><i>An Index Methodology for Diversifying Business Risk</i></b>, published in <b><i>The Journal of Index Investing</i></b>, <b>Rory Riggs</b> and <b>Jonathan Chandler</b>, both of <b>Syntax, LLC</b>, and <b>Mark T. Finn</b>, of Vantage Consulting Group, introduce a methodology for constructing an equity index in which the weight assigned to each component is determined by reference to the nature of the business risks to which it is exposed. The methodology uses the technique of statistical stratification to maximize the index’s diversification across different categories of business risks. Using the populations of the S&amp;P 500 and the S&amp;P MidCap 400 indexes, the authors compare the performance of stratified indexes created using their methodology to both market-capitalization-weighted and equal-weighted indexes comprising the same components. They find that the stratified indexes delivered higher returns and higher Sharpe ratios than the others. <b>TOPICS:</b>VAR and use of alternative risk measures of trading risk, performance measurement

Practical Applications Summary The 60/40 domestic stock/bond benchmark is still the mainstay of many U.S. corporate pension fund policy portfolios. In Hobbled by Benchmarks , published in the special 2018 multi-asset issue of The Journal of Portfolio Management, authors Mike Aked, Rob Arnott, Omid Shakernia and Jonathan Treussard argue that investors must rethink this paradigm due to the greater alpha generation potential available within a more diversified global multi-asset portfolio. They illustrate that potential by applying academically recognized risk factors in a long-only, multi-asset context.

<h3>Practical Applications Summary</h3> Quantitative investing, which deploys machine learning and other algorithms, now more or less dominates financial markets. In this environment, it9s useful to step back and compare the performance and risk exposures of discretionary and systematic hedge fund managers. Many allocators to hedge funds, large and small alike, avoid allocating to systematic funds, either partially or entirely, believing them to be difficult to understand, to offer less transparency, and to deliver worse performance due to the use of data from the past. These reasons seem to be consistent with “algorithm aversion”—a distrust of systems. In their article Man vs. Machine: Comparing Discretionary and Systematic Hedge Fund Performance, published in the Summer 2017 issue of <b><i>The Journal of Portfolio Management</i></b>, Campbell R. Harvey, Sandy Rattray, Andrew Sinclair, and Otto van Hemert compare the past performance of systematic funds with their discretionary counterparts. They show that, after adjusting for volatility and factor exposures, the lack of confidence in systematic funds is not justified. <b>TOPICS:</b>Real assets/alternative investments/private equity, statistical methods, performance measurement, manager selection