Indexology^® Blog

Thus far on the blog, we have written a few pieces about busts in the stock market. David Blitzer wrote, “Whenever this bull market ends, it is likely to be with a bang, not a whimper.” He also wrote about Deflation, Debt and Disaster where he pointed out we may be on the edge of deflation, which leads to stagnant economies and depression. I also pointed out the cycle of stock-to-commodity outperformance may be switching back in favor of commodities.

With the possibility of doom and gloom over the stock market, a natural question may be where to turn to protect your assets. Many consider gold a safe-haven, but is it really? My colleague, Reid Steadman, wrote about VIX – The Enforcer, where in a hockey analogy he pointed out that when other markets fail, VIX may be the last line of defense.  It is a decent argument that VIX may act as a strong safe-haven.

However, many might be hesitant to believe that VIX, a reflection of volatility, is a safe-haven since it’s not tangible. Despite the fact that not even the luckiest person can catch the leprechaun with the pot of gold at the end of the rainbow, at least everyone can dream that picture.  But what does a pot of VIX look like? Besides charts in a pot?

Although Reid does a good job of explaining what is VIX, as humans we possess irrational behaviors (besides believing we can catch a leprechaun with a pot of gold).  One of our behaviors is biased expectations or overconfidence that leads to misapprehensions about oneself and to the illusion of control.

In a published card game example, investors are more confident in the value of the cards they TOUCHED. The example is as follows:

• A game is played with two decks of cards, red and blue.  Players pay $1 and receive one card from one of the decks. The card is then returned to the deck, the dealer shuffles and draws one card. If the player’s card is drawn, the player wins $100.
• When the game is played with the blue deck, the dealer only shows the card to the player.
• When the game is played with the red deck, the player gets to touch the card and return it to the dealer.
• Players were asked to sell their cards prior to revealing the card chosen by the dealer.

The results show players valued the cards they touched more than they valued the cards they did not touch:

• Blue deck (no touching of cards): 19% were unwilling to sell their cards. Average asking price was $2
• Red deck (players were able to touch cards): 37% were unwilling to sell their cards. Average asking price was $9

Why does this matter?  It is since investors may value the tangible property of gold as a store of value, or currency, that it has been considered a safe-haven asset as throughout history. But the question is at what price? Is gold as a safe-haven really more valuable than VIX at protecting your portfolio in hard stock market times?

That all depends on how we measure time frames and what we consider protection, but from the look of it, we put much too high of a value on the tangibility of gold.

Let’s take a look at the overall cumulative return chart of S&P GSCI Gold, VIX, S&P GSCI and S&P 500.  Gold looks pretty attractive relative to VIX but we need to dig deeper to see which does a better job as a safe-haven.

Using monthly data in the time period from Jan 1990, the only negative years for the S&P 500 were 2000, 2001, 2002 and 2008.  The results of protection are mixed. In 2000 and 2008, VIX returned higher than the S&P GSCI Gold, but the opposite was true in 2001 and 2002.

However, the results become more clear when evaluating other metrics. VIX has the lowest correlation to the S&P 500 of -0.63, compared to -0.01 of S&P GSCI Gold with the S&P 500 and 0.18 of the S&P GSCI with the S&P 500.  This implies VIX has stronger diversification properties that could potentially lead to greater capital preservation when mixed with stocks.

Further, on average of 287 months measured, 103 months were negative for the S&P 500 and 27 of those lost more than 5% in the month. While gold protected, VIX seems to have done a better job. An average monthly loss for the S&P 500 was 3.6% with a 15% gain from VIX and only 56 basis points from gold.

VIX also has the best record of positive months when the S&P 500 lost. In 79% of down months for the S&P 500, VIX was positive.  The S&P GSCI Gold and S&P GSCI didn’t do a bad job but came up short again versus VIX.

Finally, maybe when it counts most, we measure two crisis periods during this time: the tech bubble burst and the global financial crisis.  Once again both gold and VIX protect but VIX wins.

As investors, and humans, we really might price the value of the golden touch too highly.

Whenever this bull market ends, it is likely to be with a bang, not a whimper. The bull market began on March 9^th, 2009, five years ago.  The last bull market lasted exactly five years from October 2002 to October 2007; the one before that – the great tech boom – lasted 10 years. This bull market isn’t that old. Aside from the passage of time, the next concern people raise is valuation – are stock prices “too high?”  While valuations, measured by price-earnings ratios, are above long run averages, they are modest or almost reasonable compared to the technology boom of the 1990s. Moreover, the S&P 500 is not concentrated in a few stocks or one sector. Technology is closer to a fifth of the index value today than the third it was at the end of the 1990s. The index itself is not that concentrated either: the largest stock is less than 3% of the total market value.

In keeping with the title, guessing the end of the bear market probably means guessing the next economic, political or financial upheaval.  The situation in the Ukraine is not likely to end the bull market unless the US becomes involved in military action – an extremely remote possibility.  A more likely scenario that might send the market lower would be large default of one or more junk bond issues.  The long period of low interest rates has made people more adventurous with credit risk.  Equity investors, especially after the bear markets in 2002 and 2007, should recognize that stocks can nose dive; bond investors would need memories extending back to the 1970s to understand some of the dangers.  We seem to be nervously safe for the moment.

The charts show how the S&P 500, the Dow and the tech sector in the 500 have developed since 1993. The blue line is the index; the red is the PE ratio.

Today’s Wall Street Journal brought the latest in a string of articles suggesting that we have entered a period of particular opportunity for active investment management — a so-called “stock-picker’s market.”  Because the average correlation of stocks within the S&P 500 or other major indices has declined, it’s argued, “active managers are going to do better” as the “cream rises to the top.”

Or maybe not.  The argument in favor of active management in 2014 has to contend with at least three inconvenient truths.

First, the average cannot be above average.  If all asset owners own all the assets there are to be owned, the average asset owner will earn the return of the average asset (i.e., the market return).  If we array the asset owners in rows and the assets they own in columns, the sum of the rows must equal the sum of the columns, and the sum of the changes in the rows must equal the sum of the changes in the columns — so the average return across the rows equals the average return down the columns.  William Sharpe called this “The Arithmetic of Active Management” more than 20 years ago, and the laws of arithmetic still hold.

Of course, there can still be periods when the average institutional manager outperforms a market index — but they occur only when the rows and the columns don’t match.  For example, if individual investors control 80% of the assets, and institutions control 20%, it’s entirely possible for most of the institutions to do better than the market average.  (This may be a fair description of the 1950s and 1960s.)  If a market index doesn’t describe the managers’ entire opportunity set, it’s also possible for the average manager to outperform — perhaps by buying small- and mid-cap stocks while being compared to a large-cap benchmark.

But if the index is sufficiently comprehensive, and the census of all investors is sufficiently accurate — the inexorable arithmetic of active management will hold.  Empirical studies have amply verified the theoretical argument.

Second, correlation is primarily a measure of timing, not of investment opportunity.  Assets which are positively correlated go up and down at the same time; negatively correlated assets move in opposite directions.  It’s not hard to put together an example of two stocks with perfectly negative correlation but with identical returns over the course of a month.  An omniscient day trader would benefit from trading these stocks.  For the rest of us, the benefits are less clear.  The fact that correlations declined in 2013 means that (other things equal) the market will be less volatile in 2014.  It does not mean that active manager performance will improve — the average is still average.

Finally, dispersion — which is a measure of investment opportunity — remains low. Unlike correlation, which measures whether assets go up and down at the same time, dispersion reflects the degree of difference between the best and the worst performers.  In a high dispersion environment, there’s a large gap between the “best” stocks and the “worst” stocks; when dispersion is low, the gap is small.  In 2013, dispersion in the U.S. market — despite falling correlations — was at its all-time low:

Although dispersion ticked up modestly at the beginning of 2014, it’s still well below its historical average level.  This doesn’t mean that a skillful (or lucky) manager will be less skillful (or lucky) than he would otherwise be.  Dispersion says nothing about the level of a manager’s skill, but it signifies something important about the value of that manager’s skill.  The fact that today’s dispersion levels are quite low implies that the rewards to successful stock picking are likely to be small by historical standards.

Which does not sound like a “stock-picker’s market” to me.

Copper is reputed to have earned a Ph.D. in economics because of its ability to predict turning points in the global economy.  This is since copper is so broadly used across industries from building construction, machinery, power generation and transmission, electronic product manufacturing and in transportation vehicles. As the demand for copper rises, its price likely increases and suggests a growing global economy. Conversely, declining copper prices may indicate sluggish demand and an imminent economic slowdown.

Given the recent drop in the S&P GSCI Copper, down 3.7% on Friday March 7, bringing the YTD loss to 7.5%, might that be an indicator of China’s slowing economy?  It has been shown that (lagged) copper has a correlation of roughly 0.4 with world GDP growth, which can be considered moderate at best. Further, while copper returns appear highest in the strong expansion phase and lowest in the strong recession phase, what is interesting is that returns seem to hold up quite well during periods of weak recession. Please see the chart below from my colleague, Daniel Ung, published in this paper on the S&P GSCI Cash Copper.

Further, below is a chart of yoy% GDP growth from the U.S., China and the U.K. with the S&P GSCI Copper lagged one year, which again shows some relationship but not a super compelling case that copper should earn a Ph.D. from predicting turning points in the economic cycle.

Unfortunately, the idea that the of the economy can be predicted by the demand reflected in the price of copper, is not the full picture of health. The supply side of the price equation is just as important and economic theory dictates that demand strength does not automatically translate into price hikes. Instead, it is the lack of an adequate supply response coupled with a rise in demand for supply-inelastic products, such as copper, that results in price inflation. It follows from this, that in many ways, supply is arguably more important than demand in explaining the recent behavior of the copper market.

This assertion is borne out by statistics. Over the last decade, according to World Bureau of Metal Statistics (2012), primary mine production grew by a meager 1.8% per year compared to demand, which rose by 2.4%. The copper market was in supply deficit for seven years in the last decade.

Below is a chart of the S&P GSCI Copper versus the roll yield, which is a measure of the term structure indicating a shortage or backwardation with a positive return and an excess or contango with a negative return.  Why it is more interesting than the chart above that shows copper versus GDP, is that it shows the the relationship of copper to its inventory situation. Copper was one of the few commodities with strong shortages prior to the financial crisis, but eventually the demand decline was too strong for the shortage to have an impact. Eventually the inventories caught up to and surpassed the demand as suppliers had rushed to bring more copper to the market. By the time the worst of the crisis passed, there was significant contango or excess inventory despite the rise in copper price.

However, unlike stocks that recovered well after their dip in 2011, copper can’t seem to comeback.

This might change though despite the reports of worries about the Chinese economy in light of the first default on a bond from a company traded in mainland China, and also after the official manufacturing PMI in Feb fell to an eight-month low of 50.2, just above the 50 level that separates contraction from expansion.

China accounts for 40% of global copper consumption, and even a small drop in demand could leave the market awash in extra metal.  However, given there has been a shortage (as shown by the roll yield) for 4 months straight now, it is possible copper could rebound.

As I have mentioned in prior notes, there are great opportunities for individual commodities now from the shortages that create low correlations across the spectrum.  It may or may not be time for copper but what is certain is that its supply shocks differ from the current shocks of agriculture and energy.