Whether coincidentally or not, from the beginning of the Great Bond Bull Market in the fall of 1981, bank and financial services profits gained a greater and greater share of total profits. Financial sector debt as a percent of all debt was fairly steady at around 10% until the early 80s. But it reached almost a third of all debt at the peak of the credit crisis. From the early 80s the biggest increase in bank lending was in mortgages and “related instruments,” the latter the province mainly of the mega financial companies deeply involved in creating trillions of derivative mortgages that artificially expanded the mortgage finance market. Bank and brokerage earnings performance was mirrored in the stock market. The financial sector had represented anywhere from four to six percent of total market capitalization before 1980. But that number steadily climbed until it was well more than a quarter of the market at the peak in the summer of 2007.
The US is financialized
Analysts have called this period from the early 80s the “financialization” of the US economy. But a Forbes magazine columnist last year said it had “run amok.” Bruce Bartlett, a senior economic advisor in the Reagan administration, labeled it a cause for economic malaise. It seemed as if the financial sector had morphed from reflecting the economy to directing the economy.
Of course, these views can be contentious. But there are ways to just measure whatever the phenomenon is and see if there are useful investment consequences. In its most severe form, one can separate income that comes from the “rent” or use of capital versus income that comes from a return on labor, products or services. Such a dichotomy seeks to contrast risk essentially from financial credit and artful management compared to risk from genuine non-financial enterprise.
A Rentier Index
We created what we call a “Rentier” index. The term rentier comes from the French for a “holder of rental properties or investments that pay income.” The index is derived from the performance of different sectors and indices of the stock market. It attempts to characterize and contrast the performance of those stocks and indices that benefit from getting rewards for “renting” capital to those stocks and indices that get rewards for genuine or organic risk taking. The four components of this particular index measure the relative performance of stocks/indices exposed to:
- Share buybacks vs. earnings and sales growth
- Mega banks/brokers vs. regional banks
- Gold vs. industrial metals
- Periods of high correlations between stocks vs. periods of low correlations
Factor 1 has as its numerator the performance of a basket of companies that have very high levels of share buybacks. This financial engineering has the effect of lowering the total number of shares outstanding for a corporation and therefore seeking, all else equal, to increase the value of the company per share while total earnings and/or sales might not be confirming. The denominator of the first factor is a basket of stocks that have relatively very high growth of earnings and sales.
Factor 2 is just a Wall Street vs. Main Street sample on the theory that Wall Street mega firms and brokerages are mostly renting returns while Main Street’s regional banks are attempting to help create returns directly for their enterprise clients. The ratio is normalized for the changing relative share of commercial and industrial loans for the large and smaller banks.
Factor 3 compares the performance of a “precious” metal, gold, to industrial metals like copper and aluminum. This factor seeks to separate periods when the real economy is more or less important to investors than gold, which has no intrinsic return of its own.
The final factor was the subject of our last report (http://www.qas-service.com/news.php?id=28). We argued that when correlations between stocks are high, investors care relatively less about individual company developments. In contrast when correlations are low, important distinctions between presumably good and bad companies get reflected in stock prices and in the subsectors of the aggregate averages. So this factor moves down as specific, company returns are sought or, at the other extreme, moves up when systemic/macro risks are paramount for investors and they tar all stocks with the same brush.
The chart below shows the combination of the four factors into the Rentier Index.
Think of the line rising when macro concerns are greatest and falling when animal spirits begin to suggest macro risks are receding. Any number of other factors also fit the general concept. For example the performance of event-driven (like mergers) hedge funds vs. the performance of long/short equity hedge funds would be another way to illuminate the process. The purpose here, however, is to demonstrate that each of the four sets of factors can be fairly readily invested in, particularly using ETFs. (The Appendix gives details of the index and its constituents.)
After the Dotcom bust, financialization continued apace. The bust, after all, was isolated in the technology space. Instead, financialization spread globally. To top it all off (and likely inevitably) that period was marked by what ultimately turned out to be the calamitous growth of financially engineered mortgage derivatives. That fever and the overall rentier index peaked at the beginning of the bull market six years ago. But even though the index has fallen, it has not fallen to a more midway point or, obviously, all the way to the lowest levels before the Dotcom bust. We have remained in mostly a sideways pattern, but one suggesting that there is still a substantial degree of caution for taking on enterprise risk.
Many indicators confirm there is continued caution, eight years after the onset of the credit crisis and crash. About a trillion dollars more has flowed into bond mutual funds than stock mutual funds since the bottom in 2009. Endowments, foundations, pension funds, ultra-high net worth funds and hedge funds are on average substantially underexposed to stocks compared to the averages in the decades before the Dotcom bust. The most popular investment products are still ones which promise downside protection and minimum volatility. Some investors even accept negative interest rates just for asset protection. And even though the data shows that correlations between asset classes and between investment styles are still elevated, money continues to flow into these “alternatives.” They are, in fact, “alternatives” to investing in individual companies and in subsectors of the most aggregative of market averages.
A change in the wind?
There may be some hints of change in this very big picture. First, as the US economy gathered steam and seemed to reach a new level of growth last summer, the Rentier Index dropped substantially (but only to rise again in the fourth quarter as a fear of deflation – largely emanating from Europe and the collapse in crude oil - swept through the global asset markets). Still, as we reported, within the stock market, correlations between stocks have receded since last summer and continued to recede even during the deflationary scare of the fourth quarter.
Next, there is some evidence that investors who are taking on active stock and sector risks are being rewarded. After lagging passive index funds badly, active fund management has enjoyed a relative performance revival in the last six or so months. One marker of this may be the evidence of a recent risein overall equity trading activity as shown below, after having peaked at the Dotcom highs.
In the weeks and months ahead it should be important to watch for the signs that either the general prevailing caution will be resolute or, more tantalizingly, that those who do their homework and have the talent will begin to be handsomely rewarded for taking on enterprise risk.
Factor 1. PKW vs. RPG
Factor 2. IAI vs. KBWR
Factor 3. GLD vs. JJM
Factor 4. The index in “Dig We Must” (http://www.qas-service.com/news.php?id=28)
PKW – PowerShares Buyback Achievers® ETF
RPG - Guggenheim S&P 500 Pure Growth® ETF
IAI – iShares US Broker-Dealers® ETF
KBWR – PowerShares KBW Regional Bank® ETF
GLD – SPDR Gold Shares® ETF
JJM - iPath DJ-UBS Industrial Metals Sub-Index® ETN
The procedure was to (1) construct each factor separately and then (2) standardize* each factor and then (3) calculate the average standardized score for each day.
*Standardizing: Subtract from each data point the average of all the data points and then divide by the standard deviation of all the data points.
For more information about QAS ETF Strategist Online services please visit: