Market Insights The Benefits of Integrating Fundamental and Quantitative Research to Deliver Outcome-Oriented Equity Solutions Vincent Costa, CFA Head of Global Equities Peg DiOrio, CFA Head of Global Quantitative Research Executive Summary Traditional factor-based equity strategies employ quantitative research that focuses on a combination of value, momentum, size, quality, and/or low-volatility factors to exploit the inefficiencies of capitalizationweighted indices. While the idea of factor-based investing is not new, there has been a recent proliferation of Smart-Beta equity strategies. As demand for Smart-Beta strategies grows, an increasing amount of investors are being exposed to large sector concentrations as well as unintentional factor exposures that could lead to unanticipated risks, including interest-rate risk. We believe Voya s approach of integrating quantitative and fundamental research signals mitigates the model risk and unintended consequences of a rules-based approach, and delivers more flexibility to achieve outcomes that cannot be met with traditional benchmark-oriented equity strategies: Voya s proprietary multi-factor, stock ranking models have been in place since 04 and deliver lower-cost access to uncorrelated, fundamental alpha sources Sector-neutral approach mitigates sector biases and helps protect against interest-rate risk Focus on three unique alpha sources helps deliver downside protection and strong upside capture Optimization ensures risk positions and factor exposures are deliberate, diversified and consistent with client objectives Investment universe and benchmark can be tailored to address the dynamic needs of our clients Stock-ranking models can be applied across regions (global and international) and market capitalizations (small-, mid-, and large-cap) Voya Equity: The Building Blocks for Reliable and Consistent Investment Outcomes Most factor-based equity strategies apply a primarily quantitative approach to research and portfolio construction. If fundamental insight is used at all, it typically comes at the end of the investment process. Voya s approach combines the portfolio construction and optimization capabilities of our Global Quantitative Equity Research team with the proven alpha signals of our Fundamental Equity Research team. Voya s methodology for ranking and selecting stocks integrates fundamental insights and quantitative capabilities to create a multi-factor stock ranking model. Built in house, the framework for our stock ranking model is based on the factors our senior sector analysts believe make a company successful. Each model is unique to both its sector and region, and results in uncorrelated sources of alpha when we construct the portfolio. For example, we utilize a separate model to rank U.S. industrial companies and non-u.s. industrial companies, U.S. technology companies and non-u.s. technology companies, etc. Created by fundamental analysts and validated and optimized by quantitative research, our multi-factor stock ranking models serve as the foundation for all of our active return strategies. INVESTMENT MANAGEMENT
As shown in Figure 1, our models place varying degrees of emphasis on valuation, quality and growth signals based on what our fundamental analysis has shown to be most important in each sector over time. Factors are back-tested to analyze how they performed over long periods (25+ years) and in specific types of market environments. Rather than relying upon a one-sized fits all valuation model, or more common distinctions such as value/ growth, high/low beta or high/low dividend, our approach enables us to take advantage of the intrinsic strengths of each sector. This has resulted in long-term persistent sources of alpha. Figure 1. Voya s Proprietary Stock Ranking Models Deliver Lower-Cost Access to Uncorrelated Alpha Streams 1A: Examples of Fundamental Stock Ranking System 1B: Annualized Excess Returns vs. Russell 1000 Index (Simulated Performance 01/01/90 12/31/15) Sector A 15 Factor Model Free Cash Flow Yield Change in Sales vs. CapEx Forward EPS Growth 40% 23% 37% Sector B 10 Factor Model EBITDA to EV Change in ROIC Forward PEG Ratio 17% 8% 32% 14% 54% Sector C 7 Factor Model EPS Yield ROE EPS Diffusion 22% Sector D Sector E Sector F 8 Factor Model 11 Factor Model 8 Factor Model Book Yield Forward EPS Yield EBITDA to EV Gross Profits to Assets CapEx to Sales EBITDA to Debt Forward EPS Growth Forward Sales Growth Forward EPS Growth 30% Legend: 45% Valuation Signals 75% Quality Signals 11% Growth Signals 67% 50% Consumer Discretionary Consumer Staples Energy Financials Health Care Industrials Technology Materials Telecom 1.5 Utilities Total 2.3 5.2 5.2 5.7 7.7 7.5 7.3 7.5 10.4 11.3 1C: Correlation of Excess Returns (Simulated Performance 01/01/90 12/31/15) Consumer Discretionary Consumer Staples Energy Financials Health Care Industrials Info Tech Materials Telecom Utilities Consumer Discretionary 1.00 0.06 0.09 0.08 0.12 0.08 0.11 0.13 Consumer Staples 1.00 0.14 0.21 0.15 0.14 0.18 0.12-0.08 Energy 1.00 0.15 0.12 0.04 0.09 0.19 0.12 0.03 Financials 1.00 0.28 0.29 0.18 0.19 0.15 Health Care 1.00 0. 0.15 0.04 Industrials 1.00 0.19 0.11 0.02 0.02 Info Tech 1.00 0.03 0.01 0.01 Materials 1.00 0.11 0.02 Telecom 1.00 0.06 Utilities 1.00 U.S. Model shown above is for illustrative purposes only. Past performance is not indicative of future returns. Source: FactSet and Voya Investment Management. Data from 01/01/90 12/31/15. Backtested results in Figures 1B and 1C are shown using cap-weighted Quintile 1 returns generated by the Voya proprietary Fundamental Stock Ranking System. 2
Case Study: Harnessing the Power of Voya s Fundamental Alpha Generation Capabilities The analytical framework outlined in Figure 1 serves as the alphagenerating engine of our equity platform. Voya s proprietary stock ranking models provide the building blocks to design and implement solutions for a wide range of client objectives that cannot be met with traditional, benchmark-oriented equity strategies. In the current environment, heightened uncertainty and concerns about volatility are fueling demand for downside protection. Yet investors still need to achieve attractive levels of total return and yield to meet their investment objectives. Faced with this dilemma, many investors have turned to alternative strategies such as hedge funds. Other investors have embraced Smart-Beta equity strategies as the solution. Both approaches present problems. Alternative strategies have recently underperformed, while Figure 2. Voya s Sector-Neutral Approach is Less Sensitive to Interest Rates 2A: Large Sector Bets Expose Traditional Low Volatility Strategies to Interest-Rate Risk Active Sector Weights (%) 40% 0-40 27.5 Defensive Sectors 24.1 Cyclical Sectors factor-based Smart-Beta equity strategies often expose investors to sector biases and unintended factor exposures that could lead to unanticipated outcomes, including interest-rate risk. For investors already concerned about the performance of their fixed income allocation in a rising rate environment, an allocation to this type of equity strategy introduces unwanted risk. Recently we used our multi-factor stock ranking models to partner with a large institutional client seeking higher dividend income and total returns with lower volatility relative to the overall market and the potential for attractive upside returns. Using our models and applying our sector-neutral philosophy enabled us to target low volatility, dividend yield and alpha at the sector level. The end result was a sector-neutral portfolio that delivered better outcomes for our client (Figure 2). 5.4 Insurance Heathcare - -5.6 Stpls Telecom Real Estate Utilities Voya HDLV vs R1000-24.1-27.3 MSCI Min Vol vs. MSCI USA 0. 0.40 0.60 0.80 1.0 1. 1.4 1.60 1.8 S&P Low Vol vs. S&P 500 2B: Voya s Sector-Neutral Approach and Focus on Three Unique Alpha Sources Mitigates Interest-Rate Risk 0.15 Energy Industrials Banks Materials Disc Diversified Tech - S&P Low Vol S&P Low Vol High Div Voya HDLV MSCI High Div MSCI MinVol - Beta Yield Model 0. 0.40 0.60 0.80 1.0 1. 1.4 1.60 1.8 0.7 0.8 0.9 1.0 1.1 1.2 1.3 For illustrative purposes only. Source: Voya IM and FactSet. Data as of 1/1/98-12/31/15. Past performance is no assurance of future results. Interest rate sensitivity measures the sensitivity of returns to the change in 10-year bond yields. 3
As demonstrated in Figure 2B, focusing on three unique sources of alpha stock selection (model), dividend yield and low volatility (beta) enabled us to deliver a well-diversified, sectorneutral portfolio, as each of the three factors has demonstrated outperformance with different risk/return profiles. Furthermore, combining our sector-neutral approach with the valuation component embedded within our models also helps us avoid the most expensive stocks in each sector, creating an investment framework better designed to deliver downside protection without sacrificing the potential for attractive upside returns. Accordingly, Voya s investment strategy has the potential to deliver more consistent and attractive outcomes throughout market cycles. Figure 3. Voya s Deliberate and Diversified Risk Positions Generated More Consistent and Attractive Outcomes 3A: Historically Consistent Outperformance Voya High-Dividend Low-Volatility Equity vs. Russell 1000 Index 3-Year Rolling Returns (Simulated Performance 01/31/97 12/31/15) Manager Returns (%) 35 30 25 15 10 5 0-5 -10-15 93% Manager Outperformance vs. the Benchmark -10 0 10 Index Returns (%) 30 40 3B: Outperformed in Flat and Declining Markets Simulated Monthly Performance Results (01/31/97 12/31/15) 79% 82% 58% 42% 21% 18% Monthly Returns # of Observations < -5% 38-5% to 5% 166 Strategy Outperforms Strategy Underperforms > 5% 24 Past performance is not indicative of future returns. Source: FactSet and Voya Investment Management. Data from 01/01/90 12/31/15. Back-tested results in Figure 3 are based on a simulated portfolio vs. Russell 1000 Index, rebalanced quarterly. Voya Equity Solutions: Reliable Partner, Historically Consistent Outcomes Voya s Equity platform manages $45 billion in total assets and has 50 investment professionals with 19 years of average industry experience. Our multi-factor stock ranking models have delivered consistent and uncorrelated alpha across sectors since 04. We are committed to fostering deep strategic partnerships with our clients and understand that many investors have needs that cannot be met with traditional, benchmark-oriented equity strategies. 4 Combining the best of Voya s fundamental and quantitative research capabilities enabled us to deliver historically consistent and strong risk-adjusted returns. We believe this approach to outcome-oriented investing provides lower-cost access to fundamental alpha sources while mitigating the model risk and unintended consequences of a purely rules-based approach.
Past performance does not guarantee future results. This commentary has been prepared by Voya Investment Management for informational purposes. Nothing contained herein should be construed as (i) an offer to sell or solicitation of an offer to buy any security or (ii) a recommendation as to the advisability of investing in, purchasing or selling any security. Any opinions expressed herein reflect our judgment and are subject to change. Certain of the statements contained herein are statements of future expectations and other forward-looking statements that are based on management s current views and assumptions and involve known and unknown risks and uncertainties that could cause actual results, performance or events to differ materially from those expressed or implied in such statements. Actual results, performance or events may differ materially from those in such statements due to, without limitation, (1) general economic conditions, (2) performance of financial markets, (3) interest rate levels, (4) increasing levels of loan defaults, (5) changes in laws and regulations, and (6) changes in the policies of governments and/or regulatory authorities. Simulated returns for the High Dividend Low Volatility strategy were created using a disciplined three-stage process: 1) build investable universe, 2) generate stock scores, and 3) construct the optimal portfolio. In building the investment universe, we began with the strategy s benchmark constituents and filtered the universe to include only those companies that have either a highdividend yield or have dividend growth potential within each sector. We then filtered that list further by using our proprietary yield-at-risk model to assess the ability of each company to sustain its dividend payments. Generally, this step eliminated the lowest quality stocks (i.e. stocks where the dividend is at risk of being cut or eliminated). The result was a high quality universe of stocks with sustainable high-dividend yields and dividend growth potential. Next, the sustainable high-yield universe flowed into our stock selection model a sector-specific multi-factor model that has been successfully used by the Voya IM equity platform since 04. The multi-factor framework is unique to each sector and utilizes quantitative factors (valuation, quality, and growth) that have sound economic rationale, test well quantitatively (back-tested over 25+ years), and represent the fundamental factors our senior analyst believe makes a company successful. The model was used to identify the most attractive stocks within each sector by assigning a numerical score ( z-score ) to each stock that indicated the relative attractiveness of the stock compared to all other stocks within in each sector. It is important to note however, that while the models incorporated the fundamental insights of our senior analysts, stock selection was purely model driven. As such, no qualitative assessments or judgments were used to select stocks during the simulation process. Lastly, we used a mean-variance optimization approach to rebalance the portfolio. The optimizer selected stocks for inclusion in (or removal from) the portfolio and determined the weight that each stock will be held. The objective of the optimization was to maximize the expected return (weighted average model score) while achieving its dividend yield target (>1.5x benchmark) and beta target (0.85), and abiding by a list of constraints (sector weights, asset weights, exposures, portfolio turnover, etc.). The simulation was simply the time-series of monthly returns generated by the portfolio holdings, which were rebalanced on a quarterly basis. Backtested performance is NOT an indicator of future actual results. The results reflect the performance of a strategy not historically offered to investors and do not represent returns that any investor actually attained. Backtested results are calculated by retroactive application of a model constructed on the basis of historical data and based on assumptions integral to the model which may or may not be testable and subject to losses. General assumptions include that the firm would have been able to purchase the securities recommended by the model and the markets were sufficiently liquid to permit all trading. Changes in these assumptions may have a material impact on the backtested returns presented. Certain assumptions have been made for modeling purposes and are unlikely to be realized. No representations and warranties are made as to the reasonableness of the assumptions. This information is provided for illustrative purposes only. Backtested performance is developed with the benefit of hindsight and has inherent limitations. Specifically, backtested results do not reflect actual trading or the effect of material economic and market factors on the decision making process. Since trades have not actually been executed, results may have under- or over-compensated for the impact, if any, of certain market factors may have had on a decision-making process. Further, backtesting allows the security selection methodology to be adjusted until past returns are maximized. Actual performance may differ significantly from backtested performance. Backtested results are adjusted to reflect the reinvestment of dividends and other income and except where otherwise indicated, are presented gross-of fees and do not include the effect of backtested transaction costs, management fees, performance fees or expenses, if applicable. No cash balance or cash flow is included in the calculation. The opinions, views and information expressed in this commentary regarding holdings are subject to change without notice. The information provided regarding holdings is not a recommendation to buy or sell any security. Fund holdings are fluid and are subject to daily change based on market conditions and other factors. For Australian Investors Voya Investment Management Co. LLC ( Voya ) is exempt from the requirement to hold an Australian financial services license under the Corporations Act 01 (Cth) ( Act ) in respect of the financial services it provides in Australia. Voya is regulated by the SEC under US laws, which differ from Australian laws. This document or communication is being provided to you on the basis of your representation that you are a wholesale client (within the meaning of section 761G of the Act), and must not be provided to any other person without the written consent of Voya, which may be withheld in its absolute discretion. 16 Voya Investments Distributor, LLC 230 Park Ave, New York, NY 10169 All rights reserved. For qualified institutional investor use only. 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