Weight Watchers Intl. (NYSE: WTW) is enjoying a banner year.
Shares are up 211% year to date.
Subscribership is up a whopping 16% in the latest quarter, to 3.6 million.
The result of such vertical growth has swung EPS from a loss of $0.18 to a profit of $0.20.
Free Reports:
Management just raised earnings guidance for the rest of the year, too.
OK. So we have a company thriving in the “healthy lifestyle” niche of the market.
Meanwhile…
Vitamin Shoppe Inc. (NYSE: VSI) is getting its butt kicked.
Shares are in free fall — down 54% so far this year.
Margins have plummeted to 28%.
Cash flow is dwindling to worrisome levels. And as malls get less and less traffic, the company’s customer base is disappearing.
Wait, what? Isn’t Vitamin Shoppe in the same “healthy lifestyle” niche as Weight Watchers International?
In the biz, we call such a phenomenon a “divergence.”
Divergences can be profitably traded by using a pairs trading strategy.
The idea behind pairs trading suggests that Weight Watchers International and Vitamin Shoppe should trade in a reasonably similar pattern. That is, since they exist within the same niche.
Small fortunes supposedly await those who play the imbalance between the two stocks.
But does pairs trading truly work?
I asked my senior analyst, Martin Hutchinson, to take a peek under the hood.
His full report on pairs trading is below.
Ahead of the tape,
Louis Basenese
Chief Investment Strategist, Wall Street Daily
Pairs trading is a market-neutral strategy that matches a long position in one stock with a short position in another closely related stock.
If two stocks are highly correlated and then you look when one of them has been much weaker and you buy that and you sell the stronger one under the assumption that they’ll move back together.
High correlation is calculated by something called the correlation coefficient, which goes between minus one and plus one, and pairs traders usually look for correlations of 0.8 or more.
The idea behind pairs trading is that this eliminates market risk and industry risk, because you’re short one stock and long another stock that’s similar. And that reduces this to an arbitrage between the two stocks.
It’s one of a collection of arbitrage strategies. It was one of the first quantitative techniques developed by investment bankers in the 1980s.
Inevitably, however, as the number of hedge funds has increased, the profitability of pairs trading, like other quant techniques, has declined.
Morgan Stanley made $50 million from this in 1987 but then lost it all back again in the next two years and disbanded the pairs trading group. So much for that.
Today, obviously, the individual investor has the data and the technology to be able to do this, and you could look for events that trigger a weakness in the correlation to cause one stock to drop.
For example, big insider sales, mergers, information about a new product, legal or regulatory issues or a big accident or disaster affecting a product. Those would make one stock go either down or up against another closely related one.
The problem is that pairs trading assumes that the correlation will re-establish itself.
In the real world, highly correlated stocks often diverge.
One may be better managed, one may have a reputational problem, one may have a product that goes obsolete or one may suffer a revolution in one of its major operating centers so it has to shut that operation down. There are all sorts of reasons why closely correlated stocks can diverge.
My conclusion is that this is not a very smart strategy for individual investors.
In particular, the correlations may be random due to data mining, which is where you compare 5,000 stocks over the last 30 years. There are bound to be some correlations that don’t mean anything at all. In that case, they’re bound to diverge again if they’re random.
It’s an area in which the individual investor has a real disadvantage, and even the professional investors like hedge funds don’t do too great, either.
This is Martin Hutchinson signing off. Thank you.
Smart investing,
Martin Hutchinson
Senior Analyst, Wall Street Daily
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