Situation: It has been difficult for us to set objective standards for stock-picking this year. In an overheated market, there are few stocks that meet our standards for safety. And those that do often have issues that end up explaining why they’re attractively priced. So, we’ve emphasized long-term metrics (see Week 199 and Week 206). Our goal in those two blogs has been to uncover “unicorns” -- the few companies that achieve above-market long-term returns at below-market risk. In this week’s blog we continue the hunt, hoping that enough such companies are out there to allow us to categorize the sub-sectors of the economy where they might be found.
Mission: Develop an algorithm for identifying which Barron’s 500 stocks have risk metrics that do not exceed those of the S&P 500 Index while also having 16-yr returns that beat the S&P 500 Index.
Execution: Screen the 2015 list of Barron’s 500 companies by applying a set of short- and long-term risk measurements. For example, stocks with a 5-yr Beta over 1.00 are excluded, since those have a variance higher than the S&P 500 Index. Instead of using volatile P/E values as the other tool for assessing short-term risk, we use Enterprise Value divided by Earnings Before Interest, Taxes, Depreciation and Amortization or "EV/EBITDA" and exclude stocks with a value higher than 11, which is the EV/EBITDA value for the S&P 500 Index. In other words, a company’s market capitalization (EV) is the current value of the bonds and stocks that it has issued; its earnings (EBITDA) exclude the complex and powerful effect that interest (paid on those bonds) has in lowering taxes. EV/EBITDA gives the kind of price/earnings information that investors need, one that eliminates distortions introduced by sources and sinks for cash.
To assess 16-yr returns, we primarily use the statistical (Standard Deviation of weekly prices) records found at the BMW Method website. That data set also generates estimates for the percent loss (or gain) in price that can be expected to occur at a variance of one or two Standard Deviations. For example, a drop of -2 SD is the loss that can be expected to occur in a future Bear Market. To supplement this “price only” data, we use the Buyupside website to calculate the added benefit that comes from dividends paid (i.e., Total return) from making a single stock purchase 16 yrs ago (see Column C in the Table). We also use that website to assess risk by calculating the Lehman Panic total return (10/07-4/09), which is recorded at Column D in the Table for each of our weekly blogs.
To help you gain perspective on these methods of analysis, we’ve made two additions to our list of BENCHMARKS: 1) Coca-Cola (KO), because it is the only specific stock recommendation that Warren Buffett has made for retail investors; 2) the Exchange-Traded Fund (ETF) for the Dow Jones Industrial Average (DIA or ^DJI), which has 10% better returns than the S&P 500 Index (VFINX or ^GSPC) over 3-4 market cycles with 5% less statistical risk of loss at -2SD: see 30-yr data for ^DJI vs. ^GSPC at the BMW Method website.
Bottom Line: We’ve found 10 companies that meet all of our standards for rewards vs. risk over the past 16 yrs relative to the S&P 500 Index. Five are monopolies in heavily regulated industries: Union Pacific (UNP), NextEra Energy (NEE), Eversource Energy (ES), AGL Resources (GAS), DTE Energy (DTE). Three derive the largest portion of their revenues from food: Wal-Mart Stores (WMT), Kimberly-Clark (KMB) and Sysco (SYY). It is unlikely that all 10 of these companies will continue to outperform the S&P 500 Index over the next 16 yrs, since that performance will attract more buyers and thereby elevate the short-term risk metrics (5-yr Beta, EV/EBITDA). But you get the idea: 1) “Bet with the house” which would be the government-regulated monopolies; 2) prioritize food-related investments.
Risk Rating: 4
Full Disclosure: I dollar-average into WMT and NEE, and also own shares of ITW and UNP.
Note: Metrics are current as of the Sunday of publication; metrics highlighted in red denote underperformance relative to our key benchmark, the Vanguard Balanced Index Fund (VBINX).
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