2017 Top stock picks? Use My Time Machine

No, don’t buy those ‘best stocks to own in 2017’
Barry Ritholtz
Washington Post, December 11 2016




Each year around this time, the headlines blare about what you should do with your cash. Click around any of the usual financial media sites, and you will find all manner of experts detailing the “must own” stocks you should be buying right now if you want big returns in the year ahead.

The lists certainly look slick and professional; they seem to be expertly assembled. They also tend to have a similar makeup: Usually a few highfliers (Apple, Google, Netflix, Tesla); some more modest technology names (Microsoft, Qualcomm); a bank or two (JPMorgan, Goldman Sachs); some conservative dividend plays, a health care or ­pharma, a mid- or small-cap, as well as a few companies you never heard of.

With the right charts and narratives, they look impressive. And why not? Many of the companies have had a bang-up year, or were recently in the news. You probably don’t realize this, but that’s precisely how those companies landed on the lists. That basis of assembly — what pops into the minds of editors, reporters and others — is often why this clickbait tends to bode poorly for future returns.

As an experiment, try a Google search on the phrase “best stocks to own in 2017” — you will find all manner of recommendations. If only you knew how they would perform, you might be able to pull the trigger on one, deploying your hard-earned capital for best effect.

As it turns out, you can find out how they did: Feel free to borrow my time machine.

If we were to take hundreds of lists, some would outperform, most would not and the average would be below the index. It is not a coincidence that these lists tend to underperform the benchmark. Here are the primary reasons:

Methodology: There doesn’t seem to be much of one; at least not one that is coherent or rigorous. There certainly isn’t anything close to academic research supporting the approaches taken. The articles suggested the top 10 lists are assembled by a panel of experts or chosen by the editors and staff. Surveying people who are in your general proximity and may or may not have any stock-picking skill seems to be a pretty random way to make a decision about where to put your money. The results reflect that.

Losers: One of the keys to stock picking is recognizing that over periods of time, two of three stocks will underperform their benchmark.

That is according to a study by Eric Crittenden and Cole Wilcox, formerly of Blackstar Funds. They reviewed their database, looking at every company in the Russell 3000 from 1983 to 2006. They found that 64 percent of its component stocks underperformed the broad Russell 3000 index over that period. It should come as no surprise that a list that is somewhat random in its assembly will similarly underperform a broad index.

Its not merely underperformance — over those 23 years, 4 in 10 stocks (39 percent) were unprofitable.

Winners: Conversely, it turns out that index performance is actually driven by a very small number of holdings. The entire performance of the index was driven by just 25 percent of its members.

What are the odds that a very short list — say nine or 10 holdings — will have any of those winners? It’s fair to say about 1 in 4. Now what are the odds of the list being overrepresented with those outperforming names? Once you understand how a small number of stocks are driving broader indexes, it is easy to see why it is so challenging to pick out those names.

One hitch, though, it only goes backward. Thus, I can show you how you would have done had you put money into recommendations made by these same folks a year ago for 2016.

How did they did do? For the most part, pretty mediocre.

I grabbed three “top 10 stock lists” — Barron’s, Forbes and CNBC — which came up near the top of a Google search. (If we wanted to be statistically pristine, we could assemble hundreds of such lists and track their performance, individually and in total.)

How did these do? With three weeks to go in the year, stock markets are up about 10 percent in 2016. The stock picker lists saw performances that ranged from 2 percent on the low end to about 15 percent on the high end — and that was before costs. I assumed the impact of dividends was about the same.

Too concentrated: Unlike a benchmark of 500 or 3,000 equities, 10 stocks is very concentrated. It’s too few to reap the benefits of proper diversification; any one stock can drive down total performance of the group by having a bad year. Some of the performance downside was caused by the disaster stocks, ones that were down 30, 40, even 50 percent. Recovering from that is mathematically daunting, even if your list has some big winners on it.

It’s not just the financial media whose stock picking is lackluster. Consider the Ira Sohn conference, one of the biggest finance events held each year, attended by a who’s who of hedge-fund managers. People pay $5,000 to attend (it raises money for a good cause — pediatric cancer research and treatment), and you get to hobnob with rock-star hedge-fund managers. Just remember that their stock tips are no better than anyone else’s. A broad index beat the experts in 2012, 2013, 2014 and 2015, too. (2016 is not looking so hot, either.)

And here is the even bigger challenge. Let’s say you track hundreds of lists, and one does especially well. Was it the skill of the list-maker, or just dumb luck? How could you tell? That is a question that Michael Mauboussin, chief strategist at Credit Suisse, has spent decades considering. Most investors overestimate their ability to discern between the two.

This time of year is fraught with temptations — overindulging at holiday parties, spending too much shopping for gifts, having a little too much nog. Perhaps the most expensive mistake are these silly exercises in stock picking. Crossing them off your list will save you a bundle.


Ritholtz is chief investment officer of Ritholtz Wealth Management. He is the author of “Bailout Nation” and runs a finance blog, The Big Picture. On Twitter: @Ritholtz.

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