A Stock Picker's Market? Not So Much

| About: SPDR S&P (SPY)

One of my biggest pet peeves when listening to the talking heads on TV (meaning that I’ve accidentally unmuted CNBC or Bloomberg) is when a guest comes on and talks about this being a “stock picker’s market.”

First of all, for the most part, these guys and gals all run mutual funds and are basically paid to pick stocks. As such, it would seem to always be a stock picker’s market for this crowd. Second, and much more importantly, nothing could be farther from the truth right now as this is most definitely NOT a stock picker’s market! No, research shows that “timing” trumps “selection” these days – and by a very, very wide margin.

In essence, a stock picker’s market would be defined as one where the correlation among stocks is quite low, meaning that there is a wide disparity between the performance of stocks and the overall market. When the correlation is low, a manager can add significant value to a portfolio by selecting companies that outperform the S&P 500.

However, when correlations among stocks are high, a chimpanzee throwing darts at the stock pages of the WSJ (assuming they still print those pages) is just as likely to outperform the market as all the PhD’s and mutual fund stock pickers in the world. In short, when correlations are high, all stocks tend move in the same direction of the market and “selection” doesn’t add as much value.

Stock Correlations at Record Highs

According to the folks at Ned Davis Research, the average correlation among stocks in the S&P 500 over the past 40 years has been approximately 0.45 (a reading of 1.0 would mean that stocks are perfectly correlated to the movements of the S&P 500). And based a quick glance of the data, anything above 0.56 has been considered high in the past while anything below 0.34 was low – and indeed a stock picker’s market.

The problem is today’s correlation reading of stocks to the S&P 500 is 0.82!

Why the exclamation point, you ask? The 0.82 reading is fairly amazing since there has only been one reading higher since 1972 – and that occurred during the ‘Crash of ‘87’ where the computers took anything and everything down about 30% in a matter of a couple days.

Over the nearly 40 years of data, there have only been a total of three readings over 0.80 (including the current reading) and only five reading over 0.67! Thus, the current correlation of stocks to the market is indeed quite rare.

It is also interesting to note that the current reading is ABOVE that seen during the Credit Crisis Bear Market of 2007-09. During this time, the correlations rose from an average reading in the vicinity of 0.56ish to a smidge over 0.80. However, it is important to recognize that both the recession and the bear market are now over. And history shows that after a big bear market, correlations tend to fall, not rise.

Why Are Correlations So High?

There may be several explanations for the correlations being so high these days. First, we’ve just experienced a meaningful correction, during which all stocks were hit fairly hard. Yet, while corrections of -15% or so are fairly normal, correlations of stocks to the S&P over 0.80 are most definitely not. This tells us that something else is going on here.

We believe there are three reasons behind the current high correlations among stocks: The advent of High-Frequency-Trading, the growth of ETF’s, and the globalization of the securities markets. And from where we sit, it would appear that the combination of these three have led to this becoming a singular “stock market” as opposed to a “market of stocks.”

First and foremost, we need to recognize that computerized program trading volumes make up a significant share of NYSE volume. Program trading volumes on the NYSE have been on the rise since 2000 and now account for nearly 40% of the daily activity. In addition, we’ve seen studies showing that High-Frequency-Trading (HFT) now totals close to 70% of daily volumes on all exchanges (note that program trades are likely included in the HFT totals).

Now toss in the explosion in growth of ETF’s, which have become the hedge funds favorite way to play, and it is easy to see that the fast-money crowd is not betting on earnings of a company or sector these days; no, they are making a directional bets on the overall market on a daily basis – and what easier way to do that than with a nice, easy to use, leveraged ETF?

This “risk on, risk off” type of environment is expanding around the globe as well. NDR tells us that correlations have also increased among the world markets with 44 of the 45 world market correlations rising significantly.

How Should We Proceed?

So, how does one manage money in this highly correlated world? First of all, toss that book on MPT (MPT = modern portfolio theory, which, by the way, was written in 1952) aside. Diversifying across asset classes that are highly correlated tends to be a little like owning 8 buckets of white paint.

Next, unless you are willing to buy only when there is “blood in the streets” you can also forget about the old mutual fund favorite: buy-and-hold. It’s been quite some time since that has worked well for investors. Our point here is that if you are willing to blindly buy in 2002 or early 2003, and in the dark days of February 2009, then a buy-and-hope approach may work great. But for anyone buying since 1998, it hasn’t been such a winning idea.

It seems to us that in an environment where the macro backdrop is a secular bear market and asset classes are highly correlated, good old fashioned tactical asset allocation (something we used to call “market timing” before the mutual fund industry discredited the concept) is the way to go. In short, we believe this remains a buy-and-sell type of market.

The bottom line is we believe that putting risk on and taking risk off is the way to play the mini bulls and mini bears that will likely dominate the scene for the next several years.

Disclosure: Author long AAPL

About this article:

Want to share your opinion on this article? Add a comment.
Disagree with this article? .
To report a factual error in this article, click here