Identifying Pseudo-Value Stocks To Sell

THIS IS A REPRINT OF AN ARTICLE THAT INITIALLY APPEARED ON FORBES.COM

What, exactly, is Value?  

No, it’s not low P/E, or low Price to Sales, or low Price to Book (or as academicians rephrase it, high book to market), low price/cash flow or anything like that. It’s more accurate to say it’s the present value of cash we expect to receive as a result of share ownership (dividends and eventual proceeds from selling). There are varying ways to try to address this such as DCF (discounted cash flow modeling) or DDM (the Dividend Discount Model). Details aside, the important point is that valuation is not just a number; it’s based on a set of relationships between the stock price and a measure of what shareholders expect to get as a result of owning the stock. (It’s just like in the rest of the world, where a seafood meal at Le Bernardin can’t be bashed because it costs more than one at Long John Silver’s Seafood ; it’s not only what you pay but what you pay in relation to what you get.)

PEG (P/E-to-Growth) ratio is supposed to be an answer. It is, in fact, a giant step in the right direction. But it’s incomplete because there’s more to P/E than just growth.  Notice, for example, how P/E rises when interest rates fall and vice versa. Cost of capital is a huge part of the picture for the market as a whole and for individual stocks. Obviously, market rates of interest are a big part of cost of capital. But so, too is perceived risk. This makes sense. Junk bonds bear higher rates than Treasuries. We have to think the same way when we factor cost of capital into a stock valuation model.

Rather than get overly geeky here, I’ll move right to the punch line: An ideal P/E is equal to 1 divided R-G; 1 divided by the difference R (Risk as a stand-in for Required Rate of Return) minus G (expected Growth).

NOTE: Click here if you want to get wonkier. It takes several steps to get from the dividend discount and capital asset pricing models to the simple formulation I presented. And even that is not meant as something that can be set up in a spreadsheet and into which you input numbers (such a thing is not really possible). It’s offered as a framework to help recognize the dynamics that make P/E ratios what they are, and more importantly, help you recognize when an observed P/E is likely to be unreasonable – that being the what value investors seek. 

So the definition of value is a stock whose actual P/E is less than its “warranted” P/E. (We can articulate similar concepts for other value metrics.)

Building Value Models

Value modeling aims to find stocks that are more likely than not to have valuation metrics too low given risk and growth prospects. This is not science. It can’t be since we’re dealing with future growth and future risk. It’s a combination of art, creative thinking, and detective work, looking for clues upon which we’re stuck relying due to the absence of eye-witnesses. (It’s odd so many mathematicians and scientists have found their ways into Wall Street. Investing is more compatible with the mind-sets of police detectives seeking career change, or better still, ex police detectives who studies art school before their parents made them get “real” jobs).

Value models can and do incorporate factors relating to growth potential, but I’m going to skip that today. It’s old hat. Many work this way (see, e.g. widespread love for the PEG ratio).

Instead, I want to focus on risk. This is the aspect of value that is widely misunderstood in two important ways.

First, many don’t even realize it’s relevant and focus instead on safety margins, which, actually winds up causing many to double down in the wrong direction. Protection from risk is something for which one is supposed to pay (according to the laws of supply and demand): We routinely recognize this when we buy insurance (homeowners’ insurance, auto insurance and yes, even health insurance). In stock market terms, the formula for ideal P/E is such that P/E goes up as R, risk, goes down. (So when you look for margin of safety by investing in super-low P/E stocks, you’re actually taking on a lot more risk by getting into worse companies). 

Second, many are addicted to the quant-driven lazy way of measuring risk, beta (a statistical relationship between a stock’s historic returns and those of the market). Beta is correct insofar as it considers a stock’s relative volatility, but it’s wrong to the extent it naively assumes past performance will be replicated in the future. We need to know about future share-return volatility. That will be caused by future earnings volatility and clues leading to that are most likely to come from classic fundamental analysis (the sort of thing Warren Buffet does; rather than chasing cheap stocks, he buys businesses he believes to be attractively valued relative to their fundamental quality). Because so few recognize the link between value and quality, with many getting it exactly backwards (“great company, wonderful fundamentals, but the P/E is high so stay away; better to cut risk by investing in low/P/E dumpster fires”), I see this as a fruitful approach to value modeling.

Looking for selling Opportunities

Lately, I’ve been a lot more interested in looking for things to sell rather than for things to buy. To do that in terms of value-quality, I built a model on Portfolio123 that does the following:

• I screen for stocks favorably ranked under my Portfolio123 Value ranking system (which works with the old standards; P/E, P/Sales, P/Book and P/Free Cash Flow). Chances are these stocks are in favor on the Street given the widespread tendencies of many to naively assume lower value ratios are automatically better than higher ratios. When looking for sell ideas, favorably-regarded stocks tend to make for a good hunting ground. (By the time the stock is hated, the price will likely have already fallen at which time one should be analyzing in the context of possible purchase.)
  
• I look for generally high quality stocks as per a different Portfolio123 ranking system (one based on Quality – returns on capital, margin, turnover and finances). This suggests that those who own the stock as value plays had logic (quality; lower risk) on their side.
  
• Now for the selling catalyst: I look for stocks for which the Quality rank deteriorated over the past three months. If the market was as sensitive as to the value-quality relationship as it is to the value-growth connection, I suspect the model would not be effective. My goal is to catch investors asleep at the switch and failing to \recognize or appreciate the impact of declining quality, especially since quality metrics often move slowly.

Testing the Idea

Figure 1 shows the result of a conventional 10-year backtest of the screen. Remember, I’m looking for stocks that ought to be sold. So I hope to see that the hypothetical portfolio fared worse than the market, which is what happened -- see Figure below.

The results of rolling backtests (which examine a lot of independent 3-month holding periods each of which begins on successive Mondays) are depicted in Table 1.

Table 1

During good times, times when we’re less likely to be looking to sell, the model does not have a meaningful impact. But in down times, it shows the potential to make our lives a lot easier. Past results are never dispositive of future outcomes, but when playing probabilities, the only thing we can ever really do, it seems reasonable to jettison stocks like these (high quality value stocks that have started to experience deterioration in quality) when we’re nervous about the market. The test suggests a low probability of punishment if our caution is misplaced, but a high probability of big reward if we were right to feel antsy.

The Stocks

Table 2 lists the stocks that currently make my Value-Deteriorating Quality sell list.

Table 2