by Amanda Repp, Rob Weigand and Cheng Xi.
August 2009 has been a good media month for Proctor & Gamble (PG). Morningstar declared the stock was undervalued, Barron’s included PG on a list of “12 Quality Stocks Ready to Rally,” and last week Dividends Value and iStockAnalyst recommended PG based on the company’s record of increasing dividends for 55 straight years. In light of all this recent interest in the stock, we decided to evaluate PG’s financial health and relative valuation. We’ll start with a recap of PG’s 5-year and 6-month returns vs. the S&P 500. The chart below shows that PG’s returns lagged the S&P 500 from 2004-2007, and the stock has matched the market’s 5-year return only because it exhibited less of a decline during the 2008-09 bear market. Overall, it’s been a lackluster stock for the past 5 years.
Like many other “high quality” stocks, PG has been left in the dust over the last 5-6 months as the market rallied off its lows from March 2009:
Several MBA students starting our Applied Portfolio Management program ran PG through our fundamental analysis process to determine if the stock was legitimately undervalued. Our modeling process includes forecasting a company’s financials using a set of stressful, below-average assumptions, and then determining if, under these assumptions, the company still appears financially healthy and their stock registers as undervalued based on a discounted cash flow (DCF) model. (We obtain our data via our subscription to Thomson/Reuters Baseline Direct.)
The table below shows the key assumptions we used in forecasting PG’s financials. The main stressor we threw into the forecast was growing future revenues more slowly than the “high single digits” expected by several of the articles cited above.
We also increased PG’s forecasted beta to 0.8, higher than the 5-year historical value of 0.6, which increases the cost of capital and dampens the DCF valuation estimates. We also took some energy out of the future dividend growth rate, which bloats the forecasted balance sheets with excess cash — this suppresses some of the forecasted value creation metrics such as Net Operating Profit After Tax (NOPAT), Free Cash Flow (FCF), and Economic Value Added (EVA).
PG’s relative valuation appears attractive compared to other brand-management and personal care stocks such as Clorox (CLX) and Avon (AVP). PG’s price-to-cash flow of 10 is lower than both of these stocks, whose P/CF ratios are over 14.
PG also trades at a lower P/E multiple than either CLX or AVP.
PG’s EPS and DPS display good historical growth, although earnings were flat in 2009, and the dip in 2010E reflects our conservative modeling assumptions. After 2010E, however, our model indicates that PG will be able to resume growing profits and dividends.
PG has large and stable profit margins historically. Consistent with a conservative modeling approach, our model results in a slight contraction of PG’s gross, operating and net margins in the forecast period. At an average operating margin of 18% and average net margin of 12%, however, PG should exhibit the same consistent profitability as it has in the past.
PG’s Return on Invested Capital (ROIC) is consistently above 40%, and exceeded 50% in 2008 and 2009. Our model tapers ROIC back down to the low 40s throughout the forecast period. The spread of ROIC over the cost of capital is a key component of value creation; PG’s spread of over 30% is large and significant. Return on Assets (ROA) and Return on Equity (ROE) are stable and healthy between 8-10% and 15-18%, respectively.
PG’s NOPAT and FCF declined slightly in 2009; these metrics are forecasted to decline again due to sluggish sales growth in 2010. Beyond 2010, however, we forecast that, even with sales growth averaging well below 5% per year, PG can continue growing NOPAT and FCF, which will drive long-term shareholder value creation.
The chart below shows that PG is on pace to create over $10 billion in Economic Value Added (EVA) in 2009, despite a difficult macroeconomic environment. We forecast that PG’s EVA will rise steadily from 2011-2019, fueling gains in Market Value Added (MVA). PG’s MVA is expected to rise from $130B to $160B over the next decade.
Below we overlay PG’s historical year-end stock price 2005-2009 (2009 price as of 08.28.09) with our year-by-year forecasted price from a discounted cash flow model 2010-2019. PG closed at $53 on August 28 — we forecast a 2010 fair DCF price in the range of $65-$67, with their DCF price ranging as high as $87 by 2019. These capital gains are in addition to the 3.3% dividend, of course. Further notice that this modest price path is forecasted along with contraction of PG’s Price/Sales and Enterprise Value/EBITDA ratios over the next 10 years. These DCF valuations can therefore be interpreted as more of a worst-case scenario for PG.
As an important part of any “Buy” thesis for PG rests on their ability to maintain and grow dividends, we also run several earnings quality tests, including the Piotroski 11-point Financial Fitness Scorecard (historical and forecasted values shown below) . . .
. . . and the Altman Bankruptcy Z-score. PG averages 8 out of 11 on the Piotroski test, and consistently scores in the low Safe Zone and/or high Grey Area based on the Altman test. We interpret these results — along with the company’s 55-year record of growing dividends — as evidence that PG is sufficiently financially stable to maintain and grow dividends according to investors’ expectations.
Additionally, PG has not attracted significant interest from short sellers since 2005. Many firms experienced a similar surge in short interest in Fall 2008 after the failure of Lehman Brothers.
As shown by the chart below, the surge in short interest in 2008 was proportional to an increase in PG’s volume, which explains why PG’s Days to Cover ratio has been stable for the past 3 years.
The last chart shows PG’s cumulative insider trading since 2004. For a large company, cumulative selling of $50 million in stock is not significant; insiders of most large companies are net sellers over time as they attempt to diversity their holdings. Since September 2008, PG’s insiders have actually slowed their selling; insiders of many comparable companies have been increasing selling over the same period.
Overall, our analysis suggests that, from a fundamental perspective, PG is a solid play for dividend-focused investors. The stock’s dividend yield of 3.3% is approximately equal to the yield on a 10-year T-note (about 3.5%). Of course, the company faces potential headwinds if consumers shy away from the premium brands in their portfolio and resist the company’s “trade up” strategy. Even if sales growth over the long term is half of what it’s been in the past 5 years, however, our analysis indicates the company is likely to be a slow and steady, albeit unexciting, value creator over the long run. We rate the stock a tepid “Buy.”
by Rob Weigand.
One of the things I find puzzling about the recent bear market is investors’ incredible sense of denial — a deep-seated unwillingness to believe that equities can lose 50% of their value in a matter of months. In my conversations with investment advisors, individual investors and endowment and pension officers, the question of “how could this have happened?” comes up again and again.
The simple answer to their question is that equities tanked because this is what they do from time to time. The behavior of equities isn’t what changes — what changes is our willingness to believe that our portfolios can be devastated by a “super bear” market tsunami from time to time.
The chart below depicts the annualized real 10-year return (dividends reinvested) that a buy-and-hold investor in U.S. equities would earn from each starting date on the x-axis (data courtesy of Robert Shiller). For example, someone who bought at the peak in 1929 and reinvested all dividends would have underperformed inflation by about -3% per year for the next decade. Conversely, an investor who bought at the market bottom in 1982 would have beaten inflation by about 13% per year for the next 10 years. A lot of investors’ current angst is probably due to the fact that buying and holding from the 1999-2000 peak yielded inflation-adjusted returns of about -6% per year. Thus the popularity of the phrase “the lost decade.”
The chart makes it clear that investors in past times have also experienced persistently negative real returns. It’s my impression that some of investors’ disbelief regarding the carnage visited upon their portfolios — and some of what’s driving the bull run from March-August 2009 — is a continued belief in the “culture of equities” propaganda that was perpetrated on investors throughout the 1990s and early 2000s.
Jeremy Siegel’s Stocks for the Long Run propagated a belief that equities were less risky than bonds in the long run. Now we realize that the research he conducted for the book was started when stocks were consistently beating inflation by double digits. It’s fair to assume that equities’ amazing performance over this period influenced his views a bit — and his unwaveringly bullish stance probably didn’t hurt his money management aspirations, either. Glassman and Hasset’s Dow 36,000 reinforced Siegel’s point of view — equity premiums have been too large historically! Stock values should be much higher! Hey, they were only off by 30,000, give or take a few Dow points.
Even Ben Bernanke told us that we were in a period he dubbed “The Great Moderation” just as the wheels were starting to come off the global economy and financial markets. Nice call, Ben. The point is that if these experts can get it so wrong — Siegel’s an esteemed Wharton professor, Glassman is a senior economist with J.P. Morgan, and Bernanke’s the Chairman of the U.S. Fed, for goodness sakes — we shouldn’t feel so bad about getting it wrong as well. But maybe, going forward, we can learn that during euphoric periods approaching market tops, popular cultures’ alleged “experts” also tend to get it wrong and give us bad advice, again and again.
I’ve redrawn the above chart with 36 month smoothing to take out some of the shorter-term wiggles and emphasize the longer-term trends. (The chart has an eerie sort of “Elliott Wave” appeal, don’t you think?) A few noteworthy things stand out.
First, stocks’ long-term real returns can be below average — and below zero — for extended periods. Investors buying in during the 1910s, 1920s-30s, 1960s-70s, and 1990s have repeatedly suffered these agonizing fates. The returns aren’t what’s nuts — they’ve happened again and again. For me what’s nuts is the fact that, collectively, we are so eager to ignore history and embrace the delusional messages of Siegel, Glassman and Bernanke. If you instead followed the John Bogle equity allocation (100 minus your age) you still lost some wealth in the recent bear market, but not nearly as much as a culture-of-equities asset allocator.
Second, if you’re a market-timer, you’ve got to be good. If you can’t call a market bottom within a few months, the outsized real returns will pass you by. You might still perform a few points above average, and miss a few market crashes, but to do this repeatedly you need to live to be about 150 years old.
Third, after “super bear” market tsunamis, returns can languish for long periods. As a matter of fact, the only V-shaped long-term stock market recovery following a super bear began in the 1910s. The stock markets of the Great Depression and the late-60s early-70s were characterized by long, drawn-out periods of lackluster returns. So we really need a “perfect storm” type of recovery in corporate and residential real estate, credit markets, consumer spending and corporate earnings for the great bull market of 2009 to establish itself on an economically solid foundation. I’m not saying it can’t happen, but the recovery scenario needs to unfold according to a mainly positive narrative that’s occurred only rarely in the long-term history of the U.S. economy.
I recently teamed up with Steven Sapra from Analytic Investors and Larry Gorman from Cal Poly San Luis Obispo on a research paper that investigates the relation between stock market volatility, alpha and the information ratio. We find that measures of market volatility provide forecasts of when alpha-capture opportunities in U.S. equity markets improve or worsen. This article will present an executive summary of our findings; readers interested in the technical details can download the complete paper from SSRN.
Investors are apparently interested in the connection between volatility and the availability of alpha. For example, in his August 6 post on alpha/beta separation, Chris Holt mentions an article by Janet Rabovsky of Watson Wyatt that explores the proper balance between indexing and active management. In particular, Rabovsky’s article makes note of a connection between expected market volatility (measured via the VIX) and the effectiveness of active management:
Not surprisingly, the higher the volatility of the market, the more likely it was for active managers to perform better than the index.
Before presenting our findings, we’ll clarify a few terms. Volatility refers to the standard deviation of stock returns around their time-series mean from the previous year. Dispersion refers to the cross-sectional standard deviation of stock returns around their mean on a particular day. The VIX, of course, is the CBOE implied volatility measure, computed from the implied volatilities of various S&P 500 index options.
It makes intuitive sense that alpha-capture opportunities should improve with higher market volatility — particularly as the dispersion of stock returns around their daily, weekly, or monthly average expands. When active managers predict which stocks are likely to perform better than others, they are essentially forecasting the cross-sectional dispersion of returns. For a given level of skill, there should be a greater opportunity to add value as the return differential between high- and low-performing stocks becomes larger. This is true for both long-only and long-short strategies.
To formally test this idea, we first compute the daily alphas of every stock in the S&P 500 from 1980-2008 vs. a Fama-French 4-factor model. This means that our alphas are measured net of the risk-free rate of interest and 4 betas (market, size, value and momentum). We then document how the supply of alpha varies with the volatility measures mentioned above. Noteworthy results include:
The dispersion of returns is positively related to time-series volatility (correlation = +0.73)
and the VIX (correlation = +0.76).
Moreover, the dispersion of alpha is positively related to return dispersion:
The upshot of this finding is that the alpha spread, or opportunity to add value vs. a benchmark, is expanding and contracting in sync with return dispersion and the VIX (due to its positive correlation with dispersion).
Even better, this relation is not just contemporaneous — dispersion and the VIX provide forecasts of the dispersion of alpha over 3-month and 1-year horizons (3-month results, reported as annualized returns, are shown below). Active managers can calculate dispersion — or observe the VIX at zero cost — and obtain reliable signals of when the dispersion of alpha will expand and contract. The table below divides all the trading days from 1980-2008 into quintiles based on the daily value of cross-sectional dispersion (from low to high), and shows the median annualized alpha from the 10th, 50th and 90th percentiles over the next 3 trading months.
As dispersion increases, the performance in the 10th percentile worsens (from -52% to -76%) and the performance in the 90th percentile improves (from +53% to +86%). This means that the expected alphas from shorting stocks in the 10th percentile and going long stocks in the 90th percentile get larger as dispersion increases.
Grouping trading opportunities by quintiles of the VIX provides an even more powerful alpha signal.
Active managers can anticipate tighter alpha spreads over the next 3 months when the VIX is in its lower two quintiles (comprising 40% of the trading days from 1991-2008, a shorter time period than the dispersion results because the CBOE began publishing the VIX in 1991), and wider alpha spreads when the VIX is in its top two quintiles (comprising another 40% of the trading days over that time period).
The signals do not identify opportunities to earn higher information ratios, however. We find that active risk (tracking error) expands and contracts proportionately with market volatility. The volatility signals are therefore most likely to be useful to absolute return alpha-hunters or relative return investors simply trying to outperform a benchmark, but less useful to relative return investors who measure performance using the information ratio.
Our findings partially explain why active managers, as a group, have such a difficult time outperforming their benchmarks. The best time for skilled managers to hunt alpha is often during periods of declining equity values (because volatility is higher during bear markets) — exactly when investors desire to decrease their equity allocations and reduce their overall risk exposure.
On the other hand, active managers are not underperforming their benchmarks due to an inadequate supply of alpha. In the presence of skill, the alphas that can be earned in U.S. equity markets are large and economically significant. Our analysis shows that a manager who is skilled at going long stocks in the 75th alpha percentile and short stocks in the 25th alpha percentile could earn average gross alphas of approximately 28-30%. Skill is apparently the commodity that is in short supply.