NATIONWIDE ASSET ALLOCATION INVESTMENT PROCESS

Nationwide Funds A Nationwide White Paper NATIONWIDE ASSET ALLOCATION INVESTMENT PROCESS May 2017

INTRODUCTION In the market decline of 2008, the S&P 500 Index lost more than 37%, numerous equity strategies suffered double-digit losses and many sectors of the global bond market posted returns well below average. At that time, these results caused numerous market experts to proclaim that asset allocation is dead. Despite the market carnage that year, many asset allocation funds posted far better relative returns, 1 thereby reducing the downside experienced by many investors during the worst U.S. financial crisis in over 60 years. At Nationwide, the Asset Strategies Team (AST) views asset allocation as a critical part of our mission to help advisors prepare their clients to save for and live in retirement. We are dedicated to developing and managing asset allocation solutions that seek to strike a balance between consistently strong returns and carefully managed risk. In other words, we strive to help investors achieve the highest amount of return for their desired level of risk. Asset allocation can be defined as the process of spreading assets across several different investment styles and asset classes with varying degrees of risk. The purpose is to potentially reduce long-term risk and capture potential profits across various asset classes, and, it comes in many forms. Asset classes (such as U.S. large cap stocks, emerging market stocks and high-yield bonds) can be differentiated by many factors, including market capitalization, investment style, geography and sector. Some asset allocation products seek to diversify among traditional (core) asset classes only, thus allowing an advisor or investor to supplement the program with nontraditional (alternative) asset classes such as commodities, emerging market bonds and real estate. Other programs feature a combination of both core and alternative-asset classes wrapped into one product. When thinking about asset allocation products, it is important to understand what type of asset allocation is needed and how to identify investment firms that are capable of providing the type of product best suited to each client s portfolio. Remember, though, that asset allocation does not ensure a profit or protect against losses. In fact, there is no assurance that the investment objective of any fund will be achieved or that a diversified portfolio will produce better results than a nondiversified portfolio. Nationwide offers an array of asset allocation products, including target-date funds and risk-based funds. In the pages that follow, we detail the four-step process employed by Nationwide s AST that is designed to create, manage and monitor these asset allocation products for our investors. Nationwide Asset Allocation Investment Process 1 2 3 4 Develop Asset Class Inputs Create Asset Class Models Select & Implement Investment Options Monitor the Portfolios Expected Returns Standard Deviation Correlations Optimization Re-sampling Sensitivity Analysis Style Analysis Active vs. Passive Backtesting Monitoring Trading & Rebalancing Annual Strategic Review 1 Source: Morningstar, 2008. 2

Step 1 DEVELOP ASSET CLASS INPUTS Our asset allocation investment process starts with the selection of asset classes for the product. The available universe of asset classes is extensive. To narrow the field, we employ two principal constraints in our selection process. The first constraint is dictated by the type of asset allocation product we seek to create (for example, target date-based or risk-based). The second constraint is dictated by the investability of an asset class the existence of highly liquid investment vehicles at reasonable trading costs to gain exposure to such an asset class. Once a program s design specifications and investment objectives have been determined, we finalize the selection of asset classes that we view as appropriate for the product. At this point, we engage Nationwide Asset Management (NWAM) 2 to begin construction of the model portfolios. Their data inputs consist of sets of both historical (backward-looking) and expected (forward-looking) returns, standard deviation and correlation for each asset class. Historical Returns Historical returns are available to us as far back as 1926 for U.S. equities and 1970 for U.S. fixed income. For purposes of creating and testing our asset allocation portfolios, we customarily use a widely recognized benchmark to represent a specific asset class. Each benchmark is considered a proxy for a given asset class. For example, the Russell 2000 Index may be used for our analytical purposes as an asset class proxy to represent U.S. small-cap equities over various time periods. Asset class proxies are assigned to each asset class and are used to examine the historical returns of that asset class. Standard Deviation We use standard deviation as a mean-variance tool to determine the risk associated with individual asset classes and the aggregate model portfolio. We evaluate the expected risk associated with the variance from the average return of the asset classes to determine the volatility of the portfolio. Essentially, we look at how far the rolling performance over a given time period differs from the average performance over the same time period. The higher the deviation, the more volatility we can expect from that asset class. 2 A federally registered investment advisor and affiliate of Nationwide Fund Advisors. Pursuant to the terms of an executed consulting agreement, NWAM provides asset allocation recommendations to NFA. Correlation The risk of each individual asset class is important, but it is also important to understand the relationship among the returns of various asset classes, known as correlation. Correlation is calculated on a scale from -1 to +1, where the +1 represents perfect positive correlation. In other words, the return patterns of the two asset classes move in the same direction, at the same time and to the same magnitude. The -1 represents perfect negative correlation where the return patterns move in exact opposite directions, at the same time, and to the same magnitude. A correlation of zero means that the return patterns have no relationship to one another. Determining correlations among asset classes is essential in ensuring that proper diversification exists within each model portfolio. Returns for two asset classes over a given time period may be similar. However, if the asset classes have relatively low correlation to each other over the long run, then combining them could yield a portfolio with less risk and more diversification than each of the individual asset classes could provide on their own. The low correlation is reflected in the red line in the chart below. Growth of $10,000 10 years ending December 2016 $20,000 $18,000 $16,000 $14,000 $12,000 $10,000 $8,000 $6,000 S&P 500 Index Correlation: 0.02 Bloomberg Barclays U.S. Aggregate Bond Index 50% S&P 500 Index/50% Bloomberg Barclays U.S. Aggregate Bond Index $4,000 12/06 12/07 12/08 12/09 12/10 12/11 12/12 12/13 12/14 12/15 12/16 $19,572 $18,007 $15,300 Source: FactSet Research Systems, Inc., December 31, 2016. PERFORMANCE SHOWN REPRESENTS PAST PERFORMANCE AND DOES NOT GUARANTEE FUTURE RESULTS. This chart is an example of how correlation can affect a portfolio during certain periods of time, and is used for illustrative purposes only. It shows the growth of $10,000 invested in the S&P 500 Index, the Bloomberg Barclays U.S. Aggregate Bond Index and a portfolio consisting of 50% of each index over a 10-year period from December 2006 - December 2016. The correlation during this time period between the S&P 500 Index (representing equity investments) and the Bloomberg Barclays U.S. Aggregate Bond Index (representing fixed-income investments) is 0.02. This means there is almost no correlation between the two asset classes. The value of a portfolio consisting of 50% equities/50% fixedincome investments during a 10-year period is higher than would have been achieved if you invested 100% of your assets in only one asset class or the other during the same 10-year period. Performance shown in this chart is not indicative of any Nationwide Fund. Indexes are unmanaged and have been provided for comparison purposes only. No fees or expenses have been reflected. Individuals cannot invest directly in an index. 3

Expected Risk/Return Profile We next use historical returns as a foundation to forecast expected returns for each asset class, while also incorporating more recent economic and market trends. Nationwide Asset Management, LLC (NWAM) assists us by creating expected returns and risk characteristics for each of the selected asset classes. The expected return of each asset class consists of three principal components: Real Risk-Free Rate The return that can be earned without incurring any default or inflation risk. This is often associated with money market or cash investments. Expected Inflation Additional return necessary to compensate investors for future price increases. Risk Premium Additional return necessary for accepting the inherent uncertainty associated with the asset class. Of course, past performance is not a guarantee of future results, and there is no guarantee that results can be achieved or maintained. Sharpe Ratio Step 2 CREATE ASSET CLASS MODELS Following the analysis of each asset class, the next step in the process is to bring the asset classes together to create model portfolios, or models. These models will identify the percentage of the portfolio to be allocated to a specific asset class. We engage NWAM to develop one or more sets of model portfolios for our consideration. These portfolios are created along what is known as an efficient frontier, a sophisticated analytical approach made famous by Dr. Harry Markowitz s Modern Portfolio Theory, for which he was awarded a Nobel Prize in Economics. The efficient frontier displays all asset allocation portfolios that produce the maximum return achievable for a given level of risk. Portfolio optimization and stress testing are two critical steps in this process. Optimal Portfolios on the Efficient Frontier For Illustrative Purposes Only Sharpe ratio is a measure of the excess return per unit of risk as compared to the risk-free rate. It shows the riskadjusted differences between two portfolios that have similar returns. We use the Sharpe ratio to determine if the potential additional return of an allocation to a given asset class is worth the additional risk likely to be incurred to achieve that return. The higher the Sharpe ratio, the better, as the portfolio s risk/return profile has been improved. Here s a hypothetical example: Return Portfolio B Portfolio C Portfolio A High Risk/ High Return Potential Low Risk/ Low Return Potential Sharpe Ratio For Illustrative Purposes Only Risk (Standard Deviation) Return % Return: 6% Risk: 19% Sharpe: 0.32 Return: 3% Risk: 17% Sharpe: 0.18 Return: 4% Risk: 24% Sharpe: 0.17 In this illustration, the efficient frontier is represented by the purple line and depicts the range of optimal portfolios for a mix of asset classes and the maximum return achievable for those portfolios at given levels of risk. Portfolios above this line are theoretically impossible to achieve with the existing set of asset classes. Portfolios below the line are considered suboptimal because for the same risk, one could potentially achieve greater return or for less risk, one could potentially achieve the same return. Portfolio A is a sub-optimal portfolio because it falls below the efficient frontier. An investor would be better off with Portfolio B (same return with less risk), Portfolio C (same risk with greater return) or any portfolio that falls within the shaded area. Risk % (Standard Deviation) In this illustration, the return for Portfolio A is 3% and standard deviation (risk) is 17%, resulting in a Sharpe ratio of 0.18. The return for Portfolio B is 4% and the risk level is 24%, resulting in a Sharpe ratio of 0.17. Based on this comparison, Portfolio A would be a slightly better choice than Portfolio B from a risk-adjusted return basis because Portfolio A s Sharpe ratio is higher. However, Portfolio C, with a return of 6%, a risk level of 19% and a Sharpe ratio of 0.32 would be the best choice of the three based on its risk-adjusted returns showing the highest Sharpe ratio. 4

Portfolio Optimization The first step in creating the model portfolios is known as mean-variance optimization (MVO). This is the process used to determine the mix of the asset classes selected for the model to achieve an optimal risk/return level identified along the efficient frontier. MVO is a static mathematical calculation that accounts for one specific scenario in efficient markets. Since MVO does not take inefficient markets into consideration, it is also essential to conduct a re-sampled MVO that accounts for the uncertainty inherent in the assumptions behind the expected risk/return profiles. Re-sampled MVO is conducted through a series of Monte Carlo simulations. These simulations are used to test the expected returns and risk levels of the asset classes in varying market conditions. The conditions are based on a forward-looking set of capital market assumptions, so the results have similar return, risk and correlation characteristics. Each simulation creates a new set of capital market assumptions. This process is repeated thousands of times, and a traditional MVO is calculated for each simulation. The average of these scenarios is determined to be the optimal solution. Creating An Optimal Solution Through The MVO Process For Illustrative Purposes Only Return Sensitivity Analysis NWAM tests the results from the re-sampled MVO analyses to determine the stability of the model in varying market environments by making small adjustments to the assumptions over different time periods. In this series of hypothetical situations, the asset allocation strategy remains constant, but the risk/return characteristics will change in each scenario. The goal is to keep each overall model as close to the efficient frontier as possible while the results are tested in various economic conditions and market cycles. This analysis leads us to either accept or reject the model allocations. These models are utilized in a number of ways. Many of the models are distributed throughout Nationwide to support other business lines. These business lines may use these models in a variety of products or in the education of customers and business development. In some cases we provide an open architecture framework, identifying only the asset classes, allowing the advisor to select the specific investments. In other cases, we select the specific investments (as described in the next step) that best represent the asset classes from an investable universe provided to us by the business line. In this scenario, we seek to utilize Nationwide Funds in these allocations, but use third-party funds when no Nationwide Fund is available or the available Fund does not satisfy the performance requirement. Some of these models remain static, while others are dynamically managed. Other models are used as the basis for dynamically managed asset allocation portfolios. There is no difference in methodology between those that remain as models and those that become portfolios. Attempting to near the efficient frontier by adjusting model portfolios over time for illustrative purposes only Risk (Standard Deviation) The points in the hypothetical illustration on the above left represent the historical risk/return characteristics for each individual asset class. Mean-variance optimization is then conducted to create an efficient frontier, represented by the purple line, which consists of each optimal mix of the asset classes shown at increasing levels of risk. Each combination represents a portfolio with its own unique risk/return characteristics. If further diversification or higher return is desired, it can be achieved by adding an additional low-correlated asset class, shown by the red dot. The efficient frontier is pushed outward as a result of incorporating the new asset class. This new efficient frontier, represented by the red dotted line, consists of portfolios with higher return potential than were previously attainable. Return Risk (Standard Deviation) Fixed Income Equity The chart on the above right shows samples of some hypothetical portfolios along the efficient frontier. 5

Step 3 SELECT & IMPLEMENT INVESTMENT OPTIONS We then select the underlying investments for each of the asset classes. This process will largely depend on whether we are creating a product that is predominantly passively managed or actively managed. Passively Managed Underlying Investments If our objective is to replicate the return of a specific benchmark, or if we cannot find a suitable actively managed underlying investment, then we may elect to employ a passively managed investment to fulfill that asset class allocation. Passive investing provides the ability to maintain style and market capitalization size consistency, maintain sector neutral positioning, minimize securities overlap and eliminate manager bias. This helps to ensure that our products deliver consistent, market-tracking returns. Actively Managed Underlying Investments Alternatively, we may select actively managed underlying funds in an attempt to generate excess return (alpha) compared to the return generated by the asset class benchmark. Whether our actively managed underlying investments achieve the goal of consistently generating alpha is largely dependent on our choice of the portfolio managers selected to manage those investments. We seek managers who have historically delivered consistently strong performance while adhering to their stated investment strategy. Nationwide s Manager Strategies Team (MST) assists in the analysis of these managers. The MST uses measurable data to identify managers who have previously delivered consistent results through a variety of market conditions. The MST also conducts a qualitative analysis of the managers including an evaluation of investment process, philosophy, people, style and organizational risks to affirm the results from their quantitative analysis. This analysis is essential to our model s effectiveness because if a manager s style deviates too much from the benchmarks used to create the model, then the model may not perform as we expected. Back testing Back testing, also known as stress testing a model, is achieved by combining the various strategies of the underlying funds at the allocations in which they appear in the model. The result of this process is a hypothetical portfolio which is then analyzed over a variety of time periods and market conditions. This is in contrast to combining the indexes of the underlying asset classes in the model and delivers a better understanding of how the portfolio reacted in the test periods and may be indicative of how the portfolio may perform in similar market scenarios in the future. Back testing of a model with actively managed investments is critical to ensure that the steps a manager takes to generate alpha do not change the expected characteristics of the model created earlier. It is not as critical to back test models with passively managed investments because they should assume the same characteristics as the initial asset class model. Back testing also allows us to examine the performance of the investments selected in the context of the model over a long period of time, as well as over specific shorter periods of time throughout various segments of the market cycle. Of course, selecting time periods and performance data to back test model performance is a subjective process, and it is important to remember that past performance is not indicative of future results. Step 4 MANAGE THE PORTFOLIOS This final step in the process involves the day-to-day management of the asset allocation products we offer. Many factors can result in an asset allocation product deviating from its model allocations. Therefore, a rigorous and ongoing monitoring process is essential toward striving to have the models stay within the stated parameters. Portfolio Monitoring We track each product s cash flow, return, ranking and deviation from the model allocation on a daily basis. We further examine the performance of each asset allocation product and its underlying investments on a monthly basis. A detailed performance analysis of the product is generated quarterly along with a comprehensive report that includes investment commentary, comparison of current and target allocations, performance attribution and risk analysis. Trading and Rebalancing On a daily basis, JPMorgan the asset allocation funds sub administrator allocates net cash flows among each underlying investment in our asset allocation products. They determine each fund s net available cash based on shareholder and expense activity using a proprietary allocator system. We approve the trades if they are in line with the current approved models and send the information back to JPMorgan for documentation each day. Portfolio rebalancing aims to ensure that asset class allocations stay within the guidelines established for the model. This generally occurs on a quarterly basis. Rebalancing is important because it helps reduce portfolio risk and should deliver better risk-adjusted returns over time. 6

Annual Strategic Review On at least an annual basis, we conduct a more thorough analysis with NWAM to assess the performance of our products and make any necessary changes to the allocations. Using current data, we repeat the first two steps in our process to determine if each model portfolio is still meeting the fund s stated objectives. Changes to the models are reviewed by the AST and, if approved, are promptly implemented. CONCLUSION The AST is solely dedicated to the success of our asset allocation products. Notwithstanding the short-term volatility that often grips the markets, we remain focused on maintaining a long-term investment perspective. We maintain sight of the fact that we have been entrusted with the responsibility to prudently invest our clients retirement assets. Working in close collaboration with other teams within the Nationwide Funds Group, we collectively take pride in being client-focused. We believe the process described above and the results we ve posted over the years should give you confidence in Nationwide s ability to help you position your clients to achieve their retirement goals. GLOSSARY Actively managed investment an investment continuously managed in such a way to generate alpha by exploiting inefficiencies in the market Alpha risk-adjusted return in excess of a designated benchmark return Asset allocation distributing assets across various asset classes to meet an investor s objective at a specified level of risk over a given time horizon Asset class a group of investments that exhibit the same characteristics over varying market conditions Asset class proxy the benchmark used to represent an entire class of assets such as the Russell 2000 Index to represent U.S. small-cap equities; it is used to examine the historical returns of an asset class Benchmark the standard against which an investment is measured, usually an unmanaged broad market index in which an investor cannot invest directly Correlation a statistical measure ranging from -1 to +1 depicting the relationship between two or more investments or asset classes Efficient frontier an analytical process that identifies all asset allocation portfolios that produce the maximum achievable return for a given level of risk Market capitalization the total dollar amount of a company s outstanding shares used to determine the size of a company Market sector a group of securities within an asset class which share common characteristics Mean-variance optimization the process used to determine the mix of the asset classes selected for the model to achieve an optimal risk/return level along the efficient frontier Modern Portfolio Theory a theory that attempts to maximize potential return at a given level of risk or minimize risk at a given expected return assuming markets are efficient Monte Carlo simulations a series of repeated random simulations to account for various market conditions Passively managed investment an investment managed to achieve the same risk and return characteristics as its benchmark (gross of expenses) Re-sampled mean-variance optimization a series of Monte Carlo simulations used to test the expected returns and risk levels of asset classes in varying market conditions Return the gain or loss of an investment over a specified time period expressed as a percentage Risk the probability that an investment s return will be lower than its expected return, usually expressed in terms of standard deviation Risk-adjusted return the gain or loss of an investment over a specified time period decreased by the risk incurred to achieve the return Risk-free rate the return that can be earned without incurring any default or inflation risk Risk premium Additional return necessary to compensate investors for accepting the inherent uncertainty associated with an asset class Sharpe ratio the measure of excess return per unit of risk as compared to the risk-free rate Standard deviation the measure by which an investment s return deviates from its average return, used to determine the volatility of the portfolio 7

Important Disclosures This material is not a recommendation to buy, sell, hold, or rollover any asset, adopt an investment strategy, retain a specific investment manager or use a particular account type. It does not take into account the specific investment objectives, tax and financial condition or particular needs of any specific person. Investors should work with their financial professional to discuss their specific situation. There is no assurance that the investment objective of any fund will be achieved. Except where otherwise indicated, the views and opinions expressed herein are those of Nationwide Funds Group as of the date noted, are subject to change at any time, and may not come to pass. Principal Risks Investing in mutual funds involves risk, including the possible loss of principal. Investors shares, when redeemed, may be worth more or less than their original cost. Asset allocation is the process of spreading assets across several different investment styles and asset classes. The purpose is to potentially reduce long-term risk and capture potential profits across various asset classes. Market Indexes Market index performance is provided by a third-party source Nationwide Funds Group deems to be reliable (Morningstar). Indexes are unmanaged and have been provided for comparison purposes only. No fees or expenses have been reflected. Individuals cannot invest directly in an index. Bloomberg Barclays U.S. Aggregate Bond Index: An unmanaged, market value-weighted index of investment-grade, fixed-rate debt issues (including government, corporate, asset-backed and mortgage-backed securities with maturities of one year or more) that is generally representative of the bond market as a whole. Russell 2000 Index: An unmanaged index that measures the performance of the stocks of small-capitalization U.S. companies; includes the 2,000 smallest U.S. companies in the Russell 3000 Index, which measures the performance of the stocks of the 3,000 largest U.S. companies, based on market capitalization. Russell Investment Group is the source and owner of the trademarks, service marks and copyrights related to the Russell Indexes. The Fund is not sponsored, endorsed, or promoted by Russell, and Russell bears no liability with respect to any such funds or securities or any index on which such funds or securities are based. Russell is a trademark of Russell Investment Group. S&P 500 Index: An unmanaged, market capitalization-weighted index of 500 stocks of leading large-cap U.S. companies in leading industries; gives a broad look at the U.S. equities market and those companies stock price performance. Morningstar (Mstar) Lifetime Allocation Indexes: A series of 13 unmanaged, multi-asset-class indexes designed to benchmark target-date investment products. Each index is available in three risk profiles: aggressive, moderate and conservative. The index asset allocations adjust over time, reducing equity exposure and shifting toward traditional income-producing investments. The strategic asset allocation of the indexes is based on Ibbotson Associates Lifetime Asset Allocation methodology. About Nationwide Funds Group (NFG) Nationwide Funds Group (NFG) comprises Nationwide Fund Advisors, Nationwide Fund Distributors LLC and Nationwide Fund Management LLC. Together they provide advisory, distribution and administration services, respectively, to Nationwide Funds. Nationwide Fund Advisors (NFA) is the investment adviser to Nationwide Funds. Distributor Nationwide Funds distributed by Nationwide Fund Distributors LLC (NFD), member FINRA, Columbus, OH. NFD is not affiliated with any subadviser contracted by Nationwide Fund Advisors (NFA), with the exception of Nationwide Asset Management, LLC (NWAM). Nationwide Investment Services Corporation (NISC), member FINRA. Nationwide, the Nationwide N and Eagle and Nationwide is on your side are service marks of Nationwide Mutual Insurance Company. 2017 Nationwide MFM-0878AO.7 (05/17) 8