Suggesting a stock should be sold is not meant as an insult to the company. But it is often a touchy emotional subject and one often guided more by competing folklore (i.e., ride your winners and sell losers versus take winnings off the table and average down on losing positions) than substance. Let’s change that. I’ve prepared a list of sell recommendations based on the same method I use to identify ideas for buying, data, screening rules, and ranking factors.

What it Means to Say “Sell”

This depends on your goals.

In its most basic sense, it means eliminating a stock from your portfolio because you expect it to drop in price. Or, you might eliminate a stock from your portfolio because you expect it to underperform; i.e. it may still go up, but there are others you believe likely to appreciate more. Also, and perhaps most significantly for many larger and institutional investors, it means continuing to hold but “underweighting” the position (i.e. if the stock’s target percentage within the portfolio is, say, 2%, it might be reduced to 1 or 1.5%).

Whatever the reason, it’s important to recognize that a Sell recommendation absolutely positively does not imply a negative view of the company. One must always separate an opinion of the company from an opinion of the stock. Sometimes the two go hand in hand. Often they don’t. Great companies can have unattractive stocks and vice versa. In fact, many of the stocks got onto this screen largely because the companies are good and well respected. The only reasons they make this list is because of some dysfunctional Wall Street approaches to investing in successful companies.

Why Run a Screen Like This Now?

Certain times seem better for active sell hunting than others, and I think the present is such a time.

I’m too chicken to predict a bear market. The natural tendency is for stocks to go up over the long term, based on the interplay of rising population, rising education, productivity and living standards all of which translate to better economic activity and corporate profits and all that is good on the whole for ownership of productive assets – which is what stocks are. But we all know these things go in fits and starts rather than in a straight line the result being that some periods are less favorable for stock ownership. Looking ahead from where we are now, I can’t help but focus on the end of the approximate 35-year plunge in interest rates which had the effect of pushing stocks higher regardless of the impact of other important factors such as profit growth and risk.

We may still see stocks rise from here, but for that to happen, we’ll need much larger contributions from profit growth and/or diminished risk than we’ve needed at any time since the 1970s. Maybe we’ll get that. Maybe we won’t. I’m not sure of the latter. But I sure as heck don’t want to bet the farm on the former.

The possibility of better news in terms of growth and risk makes me reluctant to say “Sell everything.” But my concerns there, as well as my convictions regarding interest rates, suggest that at the very least, we ought to be going portfolio to portfolio rounding up potential troublemakers; i.e. stocks likely to be more vulnerable than many to down markets. It would be a lot easier to maintain equity portfolios, as many gurus suggest we always should, if we can at least eliminate or trim issues that seem more vulnerable than most.

Choosing Sell Criteria

This is hard, not because of any emotional attachment to stocks but because the number of potential sell triggers is vast.

For me, when I use pure screening to select stocks, it can be a failure, when the model is refreshed, to meet all of the original Buy criteria. The advantage of this is logical purity: If the stock isn’t good enough to be purchased right now, there’s no reason to not get rid of it. The downside is turnover. Data changes continually so this can lead to a lot of trading, sometimes for seemingly trivial reasons (i.e. If my screen requires a P/E below 20 and a growth rate above 15%, I’d have to sell if the growth rate was 22% but the P/E had risen to 20.3, and repurchase shortly thereafter if the P/E drops to 19.98.) Personally, I can live with this because I trade at Folioinvesting.com and, hence, need not worry about per-trade commissions.

When turnover is a concern, it’s best to have independent sell rules. For example, I may need a growth rate of at least 15% and a P/E below 20 to buy, but I won’t sell unless the P/E jumps to 25 or the growth rate drops to below 10%. Or I may sell if analyst estimates drop, if short interest rises, is a balance sheet deteriorates, if margins deteriorate, if a 50-day moving average drops below a 200-day moving average, etc., etc., etc.

The screen I’m using today is a simple one that came about based on ideas into which I bumped while working on another project, specifically, a tendency on the part of Wall Street to be way too naïve in projecting historical rates of growth into the future; i.e. a tendency on the part of growth investors to be careless about using what they learn when they study company track records.

One would think firms with really great histories of producing growth ought to be favored. Actually, such companies should be deemed guilty until proven innocent. Natural tendencies in business and business life cycles suggest that high growth rates are most likely to decelerate. Apple, for example, does not have a growth problem. The ones who have problems are the commentators and investors who express angst over the fact that the company isn’t replicating the growth it achieved back when the “i” stuff was first being introduced. Rather than pointing accusatory fingers at executives like Tim Cook, we can and will try to profit from data suggesting that such cluelessness (on the part of the investors, not the executives) can lead us to sell candidates.

My Portfolio123 Sell screen has a single rule. It selects companies ranked 80 or better in a basic Sentiment rank consisting of factors relating to estimate revision, earnings surprise, and bullish analyst ratings. From among passing stocks, I select the top 25 under a Growth oriented ranking system that considers Sales and EPS growth over the past five years, the latest 12-month period and the latest quarter as well as acceleration. I apply these criteria to a broad universe of readily liquid and tradable stocks based on dollar value of shares traded and market capitalization.

Valuation and Momentum are not specifically built into the model, but it should come as no surprise that the combination of strong historical growth and bullish analyst sentiment combine to cause many of these issues to show poor ranks for Value and/or strong ranks for Momentum. I didn’t start out looking for hot overpriced stocks; instead, I screened for the conditions that often cause stocks to get that way.

Testing the Screen

A conventional backtest of the screen shows that this is hardly the sort of portfolio many would want to own (that’s good; this is something for which I was aiming), it’s not exactly the worst collection of stocks on the planet. It underperforms the market by a bit but shows tendencies to be horrifically volatile.

Figure 1

But this is one test with a single start date and a single set of refresh dates (every three months). What happens if I advance the start date from 1/2/99 to, say, 1/9/99? If the model is sound, it shouldn’t have a significant impact. But if I got lucky, re-running the model with a new start date and a new set of refresh dates could produce meaningfully different results.

I can test for that sort of thing quickly on Portfolio123 through a “rolling backtest.” This does not make any attempt to simulate or even approximate a real-life portfolio. It starts by running the model with a 1/2/99 start date and measuring performance for three months, at which time the test ends and the results recorded. Then, it starts again a week later, on 1/9/99, and holds another portfolio for three months at which time the test ends. A week later, on 1/16/99, it launches another portfolio that will be held for three months. And so on and so forth all the way up through 7/23/16, the most recent date as of which I could begin and finish a three- month test. I then compare all of these independent three-month portfolios to benchmark performance during those same intervals.

Table 1 shows the quick headline result.

Table 1

The numbers suggest an imperfect but blandly and barely OK portfolio. But first impressions can be deceiving. Look again at Figure 1. It looks like results were influenced heavily by some powerful rally periods. If one expects another such upsurge in the near future, then there it is; there would be no reason to consider selling anything. But if you have a more cautionary view of the market, as do I, then we have to pull those bull rushes out of the test. The easiest way to do this is to look at a sub-periods.

Table 2 carves out the early portion of the overall period, 1/2/99 through 10/24/06.

Table 2: 1/2/99 – 10/24/06

That was a pre-financial crisis golden age when not only did housing seem invincible, so, too, did almost any remotely tolerable screening-ranking based investment discipline (this stuff was much newer back then and fewer were engaging in it, making for much less crowded trades). The last ten years have been much more challenging on both counts.

Table 3 shows what happened in the past ten years, the period 10/24/06 through 10/24/16.

Table 3: 10/24/06 – 10/24/16

Ouch. . .or rather hooray since I’m trying to prove out a model that identifies selling candidates.

During up markets, we want to stay with historical growth (the continuation of which is probably an important driver of strength) supported by sentiment. But when things turn down, the market punishes these stocks harshly. Most important, the magnitude of the bad-times pain is three times as great as the joy of riding a rising tide. Once again, we see that if you’re bullish, you should not sell this list of stocks and might even consider buying. But if you’re cautious about the market, you may want to think twice or three times, before continuing to hold these kinds of good-times stocks.

Table 4, which examines various sub-periods within the last ten years, reinforces this idea.

Table 4

Interestingly, and alarmingly perhaps, if you own a lot of highly favored growth stocks, the latest year, the one in which the market has been all over the place in terms of expectations regarding what may be ahead, has been especially awful for these stocks, with the down-market hits on average accelerating to more than ten times the magnitude of the supposedly good-times mini-hits.

Nobody can tell from any model what is going to happen in the future. But models can reveal important sets of probabilities and the ones I’m seeing associated with favored growth stocks such as these look awful. It’s one thing to remain bullish and stay in stocks. It’s quite another to stay with stocks for which probable down-market losses are so much greater than potential up-market rewards.

The Stocks

Here are my 25 top sell candidates as per the growth-sentiment approach used in this particular screen. They are sorted from highest to lowest in terms of the Growth ranking.

Table 3