Dynamic MDA Portfolios A Systematic Asset Allocation Approach to MDA Products

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1 Dynamic MDA Portfolios A Systematic Asset Allocation Approach to MDA Products Executive Summary ffclearbridge Dynamic MDA Portfolios combine a robust quantitative framework, actively managed proprietary strategies and an established technology platform to deliver investment solutions that seek to generate attractive returns through different market environments. ffdynamic MDA Portfolios use trend following signal models based on capital market characteristics (size, style, geography, and security type) to identify in-favor asset classes and allocation models to optimally overweight client assets among ClearBridge strategies. fffor each Portfolio, a weighting scheme is selected to maximize risk-adjusted return for an acceptable level of strategy turnover. ffall signals and any changes in allocations are reviewed and approved monthly by ClearBridge s co-cios. Introduction ClearBridge Investments innovative Dynamic MDA Portfolios combine multiple ClearBridge active strategies that seek to generate attractive risk-adjusted returns for clients, each providing diversified exposure around a specific goal. Dynamic MDA Portfolios represent an evolution of the Multiple Discipline Account structure by integrating ClearBridge s established lineup of strategies with a systematic allocation process based on robust and reliable principles from quantitative finance. Dynamic MDA Portfolios adjust allocations based on the prevailing market environment, seeking to improve risk-adjusted returns by allocating more assets to the in-favor asset class. Trend Following The ClearBridge Dynamic MDA Portfolios are based on tactical asset allocation using trend following, both well-established concepts in academic and practitioner circles. Trend following is a variation of a momentum-driven strategy. Momentum, the tendency of stocks that have done well recently to continue doing well over the subsequent 1-12 months, 1 has long been recognized as a persistent anomaly in equity markets. 2 Diversification, a simple 1 Dunham, Lee M. Momentum: The Technical Analysis Anomaly. The Handbook of Equity Market Anomalies, Editor Leonard Zacks. Hoboken, New Jersey: John Wiley & Sons, Print. 2 Ibid.

2 DYNAMIC MDA PORTFOLIOS yet powerful driver, is the primary benefit of asset allocation. For investors, diversifying one s exposures among non-correlating assets seeks to improve riskadjusted returns by either increasing return for a given level of risk, or by reducing risk for a given level of return. Dynamic MDA Portfolios diversify client assets among ClearBridge strategies that offer different exposures to specific capital markets characteristics, such as size, style, geography and/or security type. We studied numerous trend following strategies when designing the signal models for the ClearBridge Dynamic MDA Portfolios and decided to use a movingaverage approach. In addition to being fairly simple to implement and explain, research has shown it to be among the most effective and robust approaches to tactical asset allocation. 3 The robust yet simple-to-understand process inherent in the Dynamic MDA Portfolios effectively captures ClearBridge s active management capabilities across asset classes. As a complement to the bottom-up fundamental research approach of our analysts and portfolio managers, we use quantitative analysis to continuously help improve our stock selection and portfolio construction decisions. The Dynamic MDA Portfolios leverage quantitative research and the breadth of ClearBridge s strategies to offer our clients a new suite of solutions that seek to generate attractive risk-adjusted returns. Signal Models Each ClearBridge Dynamic MDA Portfolio is based on one or more signal models in capital market data series and an allocation model that divides a client s portfolio among pre-selected ClearBridge strategies. Four signal models are currently being used among the Dynamic MDA Portfolios currently available to clients. These signal models include: SMB = Small-Minus-Big, measures the performance of small cap stocks compared to large cap stocks HML = High book value/price (value stocks)-minus- Low book value/price (growth stocks), measures the performance of value stocks compared to growth stocks UMI = U.S.-Minus-International, measures the performance of U.S. stocks compared to international developed and emerging market stocks EMB = Equities-Minus-Bonds, measures the performance of U.S. stocks compared to U.S. bonds As the names indicate, each signal model is made up of opposing asset classes along a particular characteristic, such as size, style, geography, and security type. All models are developed and maintained by ClearBridge. The SMB and HML models are inspired by the Fama- French 4 SMB and HML factors, the UMI model is based on the MSCI USA and MSCI ACWI ex-usa indexes, and the EMB model is based on the Russell 3000 and U.S. Government 7-10 Year Bond indexes. The signal models are updated monthly. Each observation is calculated by subtracting the monthly return of one asset class from the other. For instance, the SMB index represents the return of being long small cap stocks and being short large cap stocks. Each model also calculates the 12-month moving average of the data series. When the index is above the moving average, the model would signal a preference for small cap stocks because it is a small-minus-big data series. The signal would change to a preference for large cap stocks when the index crosses below the moving average for two consecutive months. The signal would change back to a preference for small cap stocks when the index crosses back above the moving average for two consecutive months. Exhibit 1 provides an example of this process for the SMB signal model for a hypothetical two-year period: i. The model prefers large cap during months 1-5 because the index is below the moving average. ii. The index moves above the moving average in month 6. However, the signal model continues to prefer large cap because the index has not stayed above the moving average for two consecutive months. iii. The model switches to a preference for small cap in month 7 because the index has remained above the moving average for two consecutive months. iv. The model maintains a preference for small cap until month 19 because the index stayed above the moving average for each two-month period from month 7 to month 19. v. The index moves below the 12-month moving average in month 19, and the signal changes to a preference for large cap in month 20 after the index remained below the moving average for two consecutive months. 3 Gray, Wesley R. Tactical Asset Allocation: Beware of Greeks Bearing Formulas. Alpha Architect, May 19, Web. Accessed May 19, Fama-French data library: french/data_library.html 2

3 Exhibit 1: Graphical Illustration of the SMB Signal Model Index Value SMB Index 12M Moving Avg Source: ClearBridge Investments. Month We chose 12 months for a simple moving-average calculation and chose to wait two months to confirm a switch. Importantly, the performance of 6- to 12-month moving averages are quite comparable for such strategies. 5 Also, waiting two months to confirm a signal, as opposed to switching when the index first crosses the moving average, reduces turnover significantly while generating a negligible impact on risk-adjusted return. Strategy Selection For an effective asset allocation approach, it is important to select constituent strategies that reflect the characteristics of the signal models being used. ClearBridge has many Separately Managed Account (SMA) strategies representing different asset classes, making it fairly easy to pair up specific strategies with asset classes from the signal models. We have designed a variety of Dynamic MDA Portfolios to cater to a wide range of investor return and risk preferences. Each ClearBridge Dynamic MDA is designed independently with a common goal of maximizing riskadjusted return (as measured by Sharpe ratio) for an acceptable level of strategy turnover. Most of the portfolios comprise three underlying SMA strategies but some consist of two underlying SMA strategies. Additionally, some portfolios are designed using one signal model, while others are designed using two. As an illustration, here are the signal and allocation model details for two Dynamic MDA Portfolios with three underlying strategies but different number of signal models: i. ClearBridge U.S. Dividend Balanced Portfolio based on the EMB signal model a. Appreciation: represents equities b. Dividend Strategy: represents equities c. Select ETF Inv. Grade Bond: represents bonds Allocation Models The Dynamic MDA portfolios currently available were designed independently with a common goal of maximizing risk-adjusted return (as measured by Sharpe ratio) for an acceptable level of strategy turnover. Exhibit 2 (below) shows the strategy allocations for two MDA portfolios. Exhibit 2: Signal and Allocation Model Showing Possible States for Two Dynamic MDA Portfolios U.S. Dividend Balanced Portfolio based on the Global Growth & Value Portfolio based on the UMI and HML Signal Models EMB Signal Model Signal Signal Equities Bonds U.S. Growth U.S.Value Int l Growth Int l Value Allocation Allocation Appreciation 40% 28% Multi Cap Growth 45% 30% 30% 25% Dividend Strategy 40% 28% Dividend Strategy 30% 45% 25% 30% Select ETF Inv. Grade Bond 20% 45% International Value ADR 25% 25% 45% 45% Allocations are as of September 30, 2017 and are subject to change. Source: ClearBridge Investments. The investment process and models used by ClearBridge to determine the Dynamic MDA Portfolios allocations to their constituent strategies are subject to change. In such event, a Dynamic MDA Portfolio s allocations may differ from the possible allocations set forth above. A Dynamic MDA Portfolio s allocations also may vary from the allocations set forth above due to market movements and the relative performance of its constituent strategies. A Dynamic MDA Portfolio s allocations in effect from time to time will be within the allocation bands set forth in the description of the ClearBridge Dynamic MDA Portfolios in ClearBridge s and Legg Mason Private Portfolio Group s combined Form ADV. 5 Faber, Mebane T. A Quantitative Approach to Tactical Asset Allocation. February 1, The Journal of Wealth Management, Spring Available at SSRN: 3

4 DYNAMIC MDA PORTFOLIOS ii. ClearBridge Global Growth & Value Portfolio based on the UMI and HML signal models a. Multi Cap Growth: represents U.S. and growth b. Dividend Strategy: represents U.S. and value c. International Value ADR: represents international (agnostic to growth or value) In the Select ETF Investment Grade Bond strategy, allocations among three ETFs are actively managed by ClearBridge portfolio managers to provide close index correlation while diversifying risk. The strategy is reviewed by ClearBridge s Co-CIOs and Risk Management Committee on a quarterly basis, and we maintain the flexibility to make changes to the ETF allocations within each strategy based on market/yield curve conditions or if the objective or structure of one of the ETFs becomes undesirable. In addition to the Select ETF Investment Grade Bond strategy, ClearBridge s suite of Dynamic MDA Portfolios also includes balanced products where the fixed-income sleeve is invested in government/corporate bond portfolios managed by Western Asset, also an affiliate of Legg Mason, Inc. Regular Monitoring and Reviews A monthly review and approval process is a critical component of the Dynamic MDA Portfolios. For an effective asset allocation process, it is critical to follow the signal, in this case based on trend following, systematically and consistently. An objective and impassionate quantitative signal model draws its strength from overriding behavioral pitfalls inherent in human decision-making. At the same time, a quantitative decision-making tool completely independent of human intervention is prone to positive feedback loops that can reinforce one or more negative signals and generate uneconomic and unexpected outcomes. Such outcomes tend to be rare but are entirely possible, and could have unwanted outcomes for clients. For instance, a Dynamic MDA signal model without any human oversight could result in excessive trading (and turnover) in highly volatile markets that have no clear trend(s). Quantitative finance literature and back tests form the genesis of the ClearBridge Dynamic MDA Portfolios and we are committed to using the signal and allocation models systematically to generate attractive riskadjusted returns. At the same time, we reserve the right to override the models if their prescription does not appear sensible in the context of the market environment. This is why we have instituted a mandatory monthly review and approval process for any allocation changes for the Dynamic MDA Portfolios. Each month, we discuss the signal and allocation models with 4 ClearBridge s Co-CIOs and seek their approval for any changes in allocation as indicated by the signal models. Good performance of the SMA strategies underlying each Dynamic MDA Portfolio is a prerequisite for the portfolios to outperform their respective benchmarks. However, even the best managers experience periods of relative underperformance. By combining portfolios with different mandates and exposures to different asset classes, the Dynamic MDA Portfolios have the potential to offset the underperformance of a single strategy. Conclusion The finance industry has been inundated with investment strategies based on quantitative models. Each claim to generate superior risk-adjusted returns by exploiting some form of market inefficiency and most of these claims are supported by rigorous research and back-testing. These strategies cover the spectrum along many dimensions, from the transparent to the black-box opaque, and from the simple-to-understand to the highly complex. At the same time, quantitative strategies share a common goal of trying to overcome human behavioral biases by systematically applying a process across market environments. The quantitative modeling behind the ClearBridge Dynamic MDA Portfolios occupies its own spot along the multiple dimensions described above. Specifically, our signal and allocation models seek to exploit the momentum anomaly through a trend following strategy along multiple capital markets characteristics. At the core, our goal is to overweight the in-favor asset class. Additionally, we are transparent about the mechanics of our process so our clients understand what the models are doing. We are committed to following the signals generated by the models. At the same time, research and experience has taught us that no model is infallible, which is why we reserve the right to override a signal if it does not appear sensible in the context of the market environment. So far we have described the key characteristics of our Dynamic MDA portfolios. What sets our portfolios apart from the competition is our ability to design these portfolios with ClearBridge strategies and our portfolio managers decades of experience in generating excess returns for our clients. Additionally, ClearBridge has developed an industry-leading platform for delivering MDA models that integrates seamlessly with our partners around the world. Putting it all together, the ClearBridge Dynamic MDA Portfolios combine a robust quantitative framework, best-in-class proprietary strategies and a proven technology platform to deliver equity solutions that seek to generate attractive returns through different market environments.

5 About the Author Farhan Mustafa, CFA Director, Head of Investment Risk Management 14 years of investment industry experience Joined ClearBridge, LLC (f/k/a Legg Mason Capital Management, LLC) in 2003 Leads Quantitative Research Team Member of the CFA Institute BA in Economics and Computer Science from Washington and Lee University MBA from the Robert H. Smith School of Business at the University of Maryland ClearBridge Investments 620 8th Avenue, New York, NY ClearBridge.com MDAs may not be appropriate for all investors. MDA minimums are typically $300,000 and may be more appropriate for affluent investors. It is important to review the investment objectives, risk tolerance, tax objectives and liquidity needs before choosing an investment style or manager. MDA disciplines may utilize Exchange-Traded Fund (ETF) disciplines. An ETF is a type of Investment Company whose investment objective is to achieve a return similar to that of a particular market index. An ETF will invest in either all of the securities or a representative sample of the securities included in the index they track. ETFs may be bought or sold throughout the day in the secondary market, but are generally not redeemable by retail investors for the underlying basket of securities they track. Clients likely to find an MDA strategy that utilizes ETF disciplines most appropriate are those willing to accept market-like returns for the ETF discipline with little potential for the individual ETFs to outperform the indices they track. Potential investors should understand that the annual advisory fee charged in the MDA program is in addition to the management fees, operating expenses, and other expenses associated with an investment in ETFs. Separately Managed Accounts (SMAs) are investment services provided by Legg Mason Private Portfolio Group, LLC (LMPPG), a federally registered investment adviser. Client portfolios are managed based on investment instructions or advice provided by one or more of the following Legg Mason-affiliated sub-advisers: ClearBridge Investments, LLC and Western Asset Management Company. Management is implemented by LMPPG, the designated subadviser or, in the case of certain programs, the program sponsor or its designee. ClearBridge Dynamic MDA portfolios are managed by Raymond James & Associates, Inc. Asset Management Services (AMS) under a model delivery arrangement. Under the model delivery arrangement, ClearBridge Investments, LLC provides Raymond James with a model portfolio and is generally not involved in organizing or effecting portfolio trades. Raymond James retains discretionary investment authority rather than ClearBridge, and therefore, trades are generally expected to be executed through Raymond James. In addition, Raymond James, rather than ClearBridge, is responsible for proxy voting (unless this authority has been retained by the client), as well as submitting instructions related to corporate actions such as reorganizations and tender offers. Under such arrangement, Raymond James manages client accounts on a discretionary basis using advice furnished by ClearBridge Investments, LLC. Asset allocation and diversification do not ensure a profit or protect against a loss. There is no assurance that any investment strategy will be successful. Equity securities are subject to price fluctuation and possible loss of principal. All investments involve risk, including loss of principal. MDA Portfolios invest in stocks and bonds, which are subject to risks, including possible loss of principal. Stocks of mid- and small capitalization companies tend to involve more risk than stocks of larger, more established companies. Investments may also be made in American Depositary Receipts (ADRs) and other securities of non-u.s. companies in developed and emerging markets, which involve risks in addition to those ordinarily associated with investing in domestic securities, including the potentially negative effects of currency fluctuation, political and economic developments, foreign taxation, and differences in auditing and other financial standards. These risks are magnified in emerging markets, which may be less liquid and more volatile because they tend to reflect economic structures that are generally less diverse and mature, and political systems that may be less stable than those in more developed countries. Fixed income securities are subject to interest rate and credit risk, which is a possibility that the issuer of a security will be unable to make interest payments and repay the principal on its debt. As interest rates rise, the price of fixed income securities falls Legg Mason Investor Services, LLC. Member FINRA, SIPC. Legg Mason Investor Services, LLC and ClearBridge Investments, LLC are subsidiaries of Legg Mason, Inc. Past performance is no guarantee of future results. All opinions and data included in this commentary are as of and are subject to change. The opinions and views expressed herein are of Farhan Mustafa, CFA and may differ from other managers, or the firm as a whole, and are not intended to be a forecast of future events, a guarantee of future results or investment advice. This information should not be used as the sole basis to make any investment decision. The statistics have been obtained from sources believed to be reliable, but the accuracy and completeness of this information cannot be guaranteed. Neither ClearBridge Investments, LLC nor its information providers are responsible for any damages or losses arising from any use of this information. For institutional and financial intermediary use only. Not for distribution to the general public. 5