Guggenheim ROIC

The ROIC Curve Valuation Framework

Content: I. Theoretical Drivers of Firm Valuation II. Why Focus on ROIC? III. Using the ROIC Curve as a Screening Tool IV. ROIC Curve Empirical Results V. The ROIC Curve Versus Traditional Valuation Anomalies

This information is intended to be general in nature and should neither be construed as investment advice nor a recommendation of any specific security or strategy.

Published October 2013. For financial professional use only. Do not distribute to the public.

Executive Summary

EXECUTIVE SUMMARY This paper examines the effectiveness of various valuation drivers in screening for companies that are potentially pre-disposed to outperform on a relative basis. Of the five drivers put forth by Merton Miller and Franco Modigliani in their seminal 1961 work on valuation, our analysis narrows to one driver that has proven over time to be an effective filter: Return on invested capital, or ROIC. This does not mean that Miller-Modigliani’s other drivers are any less important; our conclusion is that ROIC is better deployed in a screening phase of an investment process and the other drivers, less effective as screens, are better utilized later in the fundamental research phase of our investment process as validation or rejection of the screen findings. Based on our findings, we believe:

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ROIC is an effective, time-tested screen for finding companies with the potential to outperform

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As an initial screen, it is superior to the four other Miller-Modigliani valuation drivers

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The ROIC Curve, our proprietary screening mechanism, plots the relationship between ROIC and Enterprise Value/Invested Capital (a proxy for market valuation) and effectively reveals which companies may be mis- priced by the market and are therefore potentially pre-disposed to outperform

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When coupled with rigorous fundamental research, which then includes other Miller-Modigliani measures and other drivers, this screening mechanism has produced proven investment results over time



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Value Investment Philosophy

VALUE INVESTMENT PHILOSOPHY Guggenheim Investments Value (GIV) strategy seeks investment opportunities in which a company’s longterm fundamental expectations and/or risk profile implied by the current stock price are materially different from our internal assessment of the firm’s intrinsic value. Our investment philosophy has the following key components:

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Bottom-up stock selection

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Concentrated positions with portfolio weightings based on relative conviction level

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3–5 year average time horizon

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Preference for companies with stable or improving competitive positions

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Sell discipline based on deteriorating fundamentals, valuation materially exceeding internal estimate, portfolio rebalancing (risk control), or better investment opportunity elsewhere

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Valuation and rigorous fundamental analysis constitute the two core elements of our research

A key component of GIV’s internal valuation methodology is the ROIC Curve, a graphical representation of the relative valuation of companies across a benchmark universe. The ROIC Curve is based on the relationship between a firm’s return on invested capital (ROIC) and the ratio of enterprise

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value to invested capital (EV/IC). This relationship is described in more detail later, but we begin with a brief discussion of the academic valuation theory that underpins the ROIC Curve and an explanation as to why ROIC is a relevant factor for valuation screening. With regard to quantitative measures, although we utilize many metrics to establish a company’s intrinsic value, we believe that return on invested capital is the most reliable and robust. We also point out that intrinsic value is an effective risk-management framework: Buying business at a discount doesn’t just offer a large potential upside; it also helps limit losses by allowing for “margin of safety” if the investor is wrong. In sum, we believe that intrinsic value is a rational approach that can help investors avoid being either paralyzed or whipsawed by the market’s irrationality, volatility and often-conflicting messages. We find that such dislocations can actually unearth many attractive opportunities for astute investors, but that price charts and other external indicators can easily lead investors astray. We believe that in order to find viable long-term opportunities—companies that are currently earning more than their cost of capital, have a record of protecting capital and are in a strong competitive position to grow that capital once the current recession turns around—investors must adopt a bottom-up value framework.

Theoretical Drivers of Firm Valuation

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I. THEORETICAL DRIVERS OF FIRM VALUATION At the most basic level, the theoretical value of a firm is equal to the present value of its future cash flows. In their seminal 1961 paper, Merton H. Miller and Franco Modigliani provide a breakdown of the components that drive the discounted cash flow valuation of a firm: Normalized net operating profit after tax (NOPAT) A proxy for the current (or steady state) cash flow generation of the firm, without accounting for future reinvestment (growth) opportunities. Return on invested capital (ROIC) Return on the firm’s investments. Reinvestment rate (growth) Growth rate of NOPAT, based on ROIC less the

amount distributed to the firm’s investors (dividends, share buybacks, and debt service). Weighted average cost of capital (WACC) Return demanded by investors based on the fundamental risk of the firm’s cash flows. Competitive advantage period (CAP) Period over which a firm can generate ROIC that exceeds firm’s WACC. Only growth related to investments where ROIC exceeds the WACC will create incremental shareholder value. The ROIC Curve utilizes ROIC as the key driver of valuation.

II. WHY FOCUS ON ROIC? A reasonable question to ask is why GIV focuses valuation screening on ROIC rather than the other valuation drivers identified by Miller and Modigliani. It is important to note that GIV investment professionals integrate all of the valuation drivers in their detailed fundamental analysis and construction of discounted cash flow models. However, there are several benefits to using ROIC for a quantitative valuation screening methodology and certain drawbacks to each of the other Miller and Modigliani valuation drivers with regard to valuation screening. There are five key attributes of ROIC that make it a strong factor for valuation screening. The first attribute is measurability. ROIC can be measured relatively easily using readily available historical financial data from a standardized database such as Compustat. The second attribute, automation, is closely related to measurability. ROIC can be compiled in an automated fashion across a large universe of companies, which provides the efficiency needed for a screening tool. The third key attribute is fundamental insight. Viewing valuation through an ROIC lens not only results in a high quality screen, but ROIC itself For financial professional use only. Do not distribute to the public.

provides fundamental insight about the type and quality of business being studied. The fourth key attribute is cross-factor correlation. ROIC provides some incremental information about other valuation drivers. An example is a company’s growth rate. The sustainable growth formula holds that without raising additional capital, a firm cannot grow faster than its ROIC, reduced by the amount of profits returned to capital providers through buybacks, dividends, and debt service. ROIC effectively acts as a cap on a firm’s growth rate, and therefore ROIC and growth are somewhat correlated. The final attribute of ROIC that makes it a strong factor for screening is efficacy. As we demonstrate in a later section with our backtest results, ROIC has proven empirically to be strongly correlated with valuation, and stock selection based on discrepancies between a firm’s ROIC-based warranted valuation and market valuation yields positive alpha over time. The other Miller and Modigliani valuation drivers, while important to our overall fundamental process, fail in one or more of the key attributes that make ROIC a viable screening factor.

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Why Focus on ROIC?

WACC and competitive advantage period suffer from measurability and automation difficulties. NOPAT, while measurable, suffers automation difficulties as normalization of earnings is often necessary on an industry-by-industry basis, and industries change over time. Although academics have proposed several models of WACC estimation, including the Capital Asset Pricing Model (CAPM), these models have difficulty measuring the equity risk premium and therefore result in limited efficacy.

The competitive advantage period is not a directly observable data item; it must be subjectively judged by the fundamental analyst and therefore suffers from measurability and automation difficulties. The following chart in Table 1 compares the various Miller-Modigliani drivers and confirms our hypothesis of ROIC as an effective initial screen. The last Miller and Modigliani valuation driver to

TABLE 1: ROIC VERSUS OTHER VALUATION DRIVERS

Measurability

Automation/ Efficiency

Fundamental Insight

ROIC NOPAT GROWTH WACC CAP Strong Medium Weak

ROIC NOPAT GROWTH WACC CAP

Return on invested capital Normalized net operating profit after tax Reinvestment rate Weighted average cost of capital Competitive advantage period

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Cross-Factor Correlation

Efficacy

Why Focus on ROIC?

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address, the firm’s growth rate, warrants a more detailed discussion. There are two key problems with using a firm’s growth rate as the key valuation driver. The first problem is efficacy. Using a standard discounted cash flow model based on the Miller and Modigliani valuation drivers, we can demonstrate that unless a firm has a high level of ROIC, changes in the firm’s growth rate will not have as big of an impact on valuation as an equally sized change in ROIC. This fact is further illustrated by an analysis from

McKinsey & Co. in Exhibit 1 which depicts the impact of a 1% change in both ROIC and growth on a firm’s valuation (defined as enterprise value). The study holds that a 1% delta in ROIC, given a baseline ROIC of 9% for instance, results in a 26% increase in valuation versus no change from a similar delta in growth given the same base ROIC. Even though the study finds diminishing returns to increasing ROIC, the efficacy of ROIC over growth as a driver of valuation is clearly demonstrated.

*EXHIBIT 1: IMPACT OF ROIC VERSUS GROWTH ON VALUATION

Value, Compared Improving returns on invested capital creates more value than growth (except when ROIC is already high). Value Created by 1% Faster Growth1 %

Value Created by 1% Higher ROIC1 %

26

16

6 Baseline ROIC

0 9

12

8

20

The second difficulty with a growth-based valuation framework is that growth rates are highly unstable and often very difficult to predict. Alternatively, ROIC tends to be more stable and more predictable. Exhibit 2, also courtesy of McKinsey, demonstrates this fact by comparing the migration of ROIC and growth levels

*SOURCE: MCKINSEY & CO. 1 Assumes 9% weighted average cost of capital. For financial professional use only. Do not distribute to the public.

7 Baseline ROIC

9

12

20

of individual companies between 1994 and 2003. For example, 50% of firms with an ROIC of over 20% in 1994 remained above 20% in 2003, while only 13% of firms with a growth rate of over 20% in 1994 remained above 20% in 2003.

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Why Focus on ROIC?

*EXHIBIT 2: PERSISTENCY OF ROIC AND GROWTH, 1994–2003

Individual companies can sustain a high ROIC ... 3-year average ROIC without goodwill of all publicly listed U.S. companies with real revenues >$200 million %

ROIC in 2003 5–10%

20%

ROIC in 1994 20%

19

17 25

19

7

6 18

17

25

13

13

 % of Companies that Stayed the Same

11

11

20

5

6

50

 % of Companies that Moved to a Higher Level

 % of Companies that Moved to a Lower Level

... but cannot sustain growth 3-year compound annual growth of real revenues of all publicly listed U.S. companies with real revenues >$200 million %

Revenue Growth in 2003 Revenue Growth in 1994

5–10%

20%  % of Companies that Stayed the Same *SOURCE: MCKINSEY & CO.

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11 13

14 10

 % of Companies that Moved to a Higher Level

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13  % of Companies that Moved to a Lower Level

Why Focus on ROIC?

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EXHIBIT 3: EXAMPLE OF ROIC CURVE—RUSSELL 2500TM ROIC CURVE 6

y = 15.998x2 + 1.548x + 1.376 R2 = 75.10%

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EV / IC

4 3 2 1

-10% -5%

0 0%

5%

10% 15% 20% 25% 30% 35% 40% ROIC

Exhibit 3 shows the ROIC curve. The formulaic definitions for EV/IC and ROIC are as follows: EV = market value of equity + book value of debt – cash & short term investments IC = book value of equity + book value of debt ROIC = pretax earnings / IC (as defined above) ROIC is calculated using trailing four quarter data and excludes nonrecurring or extraordinary items. EV and IC are both adjusted to reflect operating leases as debt capital. The use of EV/IC as the metric for market valuation is important because it adjusts for the firm’s debt level. This adjustment is significant because equity investors’ claim on the firm’s cash flows is subordinate to creditors. Using a metric such as P/B or P/E does not capture differential debt loads among firms and thus risks overlooking an important economic difference in comparing firms. Cash is also excluded from EV in order to isolate the valuation of the ongoing operating business of the subject company. The use of ROIC to measure profitability is also instrumental to this valuation framework for two reasons. First, ROIC is superior to profit marginFor financial professional use only. Do not distribute to the public.

based profitability metrics, such as pre-tax margin or net income margin, because ROIC accounts for the capital required to generate profits. Pre-tax margin at best only captures the cost of debt capital (via the expensing of interest costs). Second, ROIC captures the return to all investors in the firm, whether debt or equity. Using an alternative measure such as return on equity (ROE) to capture profitability does not account for differential use of financial leverage among firms to achieve common equity profitability. Exclusion of the Financial Sector from the ROIC Curve The two largest subsets of the financial sector— banking and insurance—have unique attributes relative to industrial sectors that require the exclusion of the financial sector from the ROIC Curve. In the banking industry, the high degree of financial leverage makes the calculation of ROIC not meaningful. In the insurance industry, “leverage” is primarily operating rather than financial in nature because the key leverage statistic is premiums written to equity. This type of leverage is impossible to capture in the ROIC Curve framework. Additionally, both banks and insurance companies have significant uncertainty in profit reporting due to the heavy use of accruals (i.e. provisioning for credit losses in banking and booking reserves in insurance). This uncertainty generally causes financial services companies to trade at a significant discount to the broader market.

Using the ROIC Curve as a Screening Tool

III. USING THE ROIC CURVE AS A SCREENING TOOL The first step in drawing a conclusion from the ROIC Curve is to determine whether there is a discrepancy between the company’s current EV/IC based on market price and the “warranted” valuation based on the relevant ROIC Curve benchmark. The warranted valuation can be determined relative to one of three benchmark ROIC Curves: 1) the broad market, 2) the subject company’s industry, and 3) the company’s own history (adjusting for any changes in ROIC over time). Assuming a similar risk profile and growth outlook, the market should assign the same value to a unit of ROIC regardless of what company generates it. Therefore, if there is a large discrepancy between the subject company’s EV/IC and the warranted EV/ IC based on one of the three benchmarks identified above, a mispricing of the security could be present. We refer to this discrepancy as “delta Y” because it is the vertical distance on the graph between the

company’s valuation and the corresponding point on the benchmark curve. A large positive delta Y implies overvaluation of the subject company, while a large negative delta Y implies undervaluation. Our basic screening process using the ROIC Curve is to screen for companies that have a large negative delta Y. An illustration of delta Y is depicted in Exhibit 4. It is important to note that the presence of a large negative delta Y does not guarantee undervaluation of a security. The ROIC Curve does not capture the other four components of Miller & Modigliani’s theoretical valuation framework. These other factors could be materially higher or lower than the benchmark group of companies against which we are comparing the subject company. It is the primary function of our fundamental research to perform an in-depth industry and company analysis to assess whether the security is truly mispriced.

EXHIBIT 4: ROIC CURVE WITH "DELTA Y"—RUSSELL 2500TM ROIC CURVE 6

y = 15.998x2 + 1.548x + 1.376 R2 = 75.10%

5 4 EV / IC

10

3

Positive "delta Y" potential overvaluation Stock A

2 1

-10% -5%

0 0%

Stock B Negative "delta Y" potential undervaluation 5%

10% 15% 20% 25% 30% 35% 40% ROIC

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ROIC Curve Empirical Results

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IV. ROIC CURVE EMPIRICAL RESULTS GIV has performed a rigorous empirical backtest for the ROIC Curve to demonstrate that when a company’s valuation diverges significantly from its warranted EV/IC–ROIC relationship, opportunities for excess return (alpha) may be present. The backtest was performed by splitting the investment universe into deciles based on delta Y, with stocks showing the largest negative delta Y (i.e. highest potential undervaluation) in decile 1. A summary of the results of this backtest across the market capitalization

spectrum from 1986 to 2010 are presented in Exhibit 5. The charts show the annualized absolute return of each decile over the relevant benchmark, using a 3-year time horizon, which is consistent with our typical holding period. The backtest results show a strong positive correlation between delta Y and superior investment returns, as measured by absolute return.

EXHIBIT 5: ROIC CURVE BACKTEST RESULTS1—ANNUALIZED ABSOLUTE RETURN OVER BENCHMARKS (BY DECILE) 8% 7% 6% 5% 4% 3% 2% 1% 0%

8%

R1000 Annualized Active Returns vs. Benchmark

1

2

3

4

5

6

7

8

9

10

R2500 Annualized Active Returns vs. Benchmark

6% 4% 2% 0% -2% -4% -6%

1

2

3

4

5

6

7

8

9

10

5% 4% 3% 2% 1% 0% -1% -2% -3%

8% 6% 4% 2% 0% -2% -4% -6% -8% -10%

RMidCap Annualized Active Returns vs. Benchmark

1

2

3

4

5

6

7

8

9

10

R2000 Annualized Active Returns vs. Benchmark

1

2

3

4

5

6

7

8

9

10

Past performance is no guarantee of future results.

1

Delta Y Deciles from 1986–2012, 3-Year Holding Period. Decile 1 represents largest negative delta Ys; GICS sectors equal weighted to avoid large sector bias.

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The ROIC Curve Versus Traditional Valuation Anomalies

V. THE ROIC CURVE VERSUS TRADITIONAL VALUATION ANOMALIES While we have addressed why GIV uses ROIC rather than the other Miller-Modigliani valuation drivers as a key factor for valuation screening, there remains the question as to why the ROIC Curve methodology is superior to other valuation “anomalies” that have been identified by academic researchers over time. Examples of these anomalies include low price-toearnings (P/E), P/E-to-growth (PEG), price-to-book (P/B), and enterprise-value-to-EBITDA (EV/EBITDA). We believe that these traditional valuation metrics suffer from significant shortcomings that fail to account for the key theoretical drivers of firm valuation as proposed by Miller-Modigliani. Traditional valuation multiples that are based on the ratio of equity market price to current earnings, cash flow, or some proxy for either (such as EBITDA) are weak because they do not provide any insight as to the returns generated by a firm and whether or not those returns are in excess of the cost of capital. From Miller-Modigliani we know this is critical to shareholder value creation.

Valuation metrics that are based on the relationship of steady-state earnings (or cash flow) multiples to growth in earnings (cash flow), such as the PEG ratio, suffer from the shortcomings we identified in an earlier section of this paper (see “Why Focus on ROIC?”), as well as a key shortcoming common to the other basic multiples: they do not indicate whether the growth generated is economically profitable (i.e. ROIC > WACC). Without understanding the ROIC profile of the firm, we cannot make an informed judgment about market valuation. Exhibit 6, courtesy of Legg Mason Capital Management, illustrates the theoretical relationship of P/E to growth and ROIC. Exhibit 6 shows that if a firm is reinvesting at its cost of capital (and no more), the P/E ratio will not change regardless of an increase in growth rate. If the firm reinvests below the cost of capital, its P/E ratio will fall as growth increases, because the firm is destroying shareholder value.

*EXHIBIT 6: THE RELATIONSHIP OF P/E TO ROIC AND GROWTH—RETURN ON INVESTED CAPITAL

Earnings Growth

12

4%

8%

16%

24%

4%

6.1x

12.5x

15.7x

16.7x

6%

1.3

12.5

18.1

20.0

8%

NM

12.5

21.3

24.2

10%

NM

12.5

25.5

29.9

Assume all equity finance; 8% cost of capital; 20-year forecast period

*SOURCE: LEGG MASON CAPITAL MANAGEMENT. For financial professional use only. Do not distribute to the public.

The ROIC Curve Versus Traditional Valuation Anomalies

Beyond all of the shortcomings related to earnings and growth-based measures of valuation, there is one additional problem related to valuation multiples that use equity market price and/or book value as a component of valuation: They do not differentiate firms by financial leverage (debt), and they do not account for excess cash held by a firm. For example, two firms with identical operating profiles might trade at far different P/E multiples because one uses far higher financial leverage. The firm with higher leverage justifiably trades at a lower multiple because it has increased bankruptcy risk and equity earnings volatility due to the high degree of financial leverage.

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Beyond a discrepancy in debt levels, two firms could have identical operating profiles but one firm has a significant amount of excess cash. The firm with excess cash could justifiably trade at a higher P/E multiple, assuming all other fundamental factors about the two firms were identical. Thus the existence of different amounts of debt in the capital structure and excess cash would diminish the reliability of comparative valuation using P/E multiples. This problem is mitigated using the ROIC Curve because valuation is measured using Enterprise Value, which accounts for debt and cash.

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Conclusion & References

CONCLUSION Given GIV’s long-term investment horizon and concentrated position sizes, it is critical that our investment professionals maintain an intimate understanding of each of our investment positions. The rigorous depth of research conducted on each investment opportunity is both enabled and focused by having a screening mechanism that allows our team to narrow their research to opportunities that are pre-disposed to outperform and subject to extensive fundamental research, and have a high probability

of inclusion into the investment portfolio. Thus we avoid wasting resources researching securities with low-probability of success and utilize that time honing our research on better opportunities. The ROIC Curve provides that small subset of promising opportunities to our investment professionals and also yields initial insights about the fundamental quality of a company that serve as a starting point for our fundamental research.

REFERENCES Cao, Bing; Jiang, Bin; and Koller, Timothy, "Balancing ROIC and Growth to Build Value," McKinsey on Finance, Spring 2006. Mauboussin, Michael J., “M&M on Valuation,” Mauboussin on Strategy, 14 January, 2005. Miller, Merton H. and Franco Modigliani, “Dividend Policy, Growth, and the Valuation of Shares,” The Journal of Business, October 1961.

The information provided here is intended to be general in nature and should not be construed as investment advice nor a recommendation of any specific security or strategy. You cannot invest directly into an index. The information herein has been obtained from sources believed to be reliable, but Guggenheim Investments does not warrant its completeness or accuracy. Prices, opinions and estimates reflect judgment and are subject to change at any time without notice. Any statements which are nonfactual in nature constitute current opinions, which are subject to change. Projections are not guaranteed and may vary significantly from the results indicated. This information does not represent an offer to buy or sell securities of any Guggenheim Investments product. Consider the investment objectives, risks, charges and ongoing expenses of any investment product carefully before investing. Guggenheim Investments represents the investment management businesses of Guggenheim Partners, LLC. Services offered through Guggenheim Funds Distributors, LLC. and Guggenheim Distributors, LLC. Guggenheim Distributors, LLC and Guggenheim Funds Distributors, LLC. are affiliated with Guggenheim Partners, LLC. This material is prepared for financial professional use only. It may not be reproduced or shown to members of the general public or used in written form as sales literature; any such use would be in violation of FINRA Conduct Rules. For financial professional use only. Do not distribute to the public.

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