How companies have spent their cash over the past 25 years. Interesting to note is that they spend on average, about 60% of their total spend on capital expenditures, 20% on M&A, and about 10% each on dividends and executed buybacks. The total amount of spend bounces around a bit but is a fairly consistent 20% of market capitalization. Note that buybacks exceeded dividends in 7 out of the past 10 years

I've shown that valuation matters numerous times over the years when it comes to long-term equity returns (see here, here, and here for some of my favorite examples). The below post uses the same concept in that it compares valuation (i.e. yields) with forward returns, but in this version we compare the relative performance of equities vs. bonds.

While I refuse to state that returns will be anywhere near this 9.5%, by almost all measures stocks appear cheap on a relative basis to Treasury bonds. Unless earnings collapse back to a "normal" percent of the overall economic pie abruptly (definitely possible, but in my view not likely) or the economic pie contracts abruptly, stocks are going to outperform bonds over the next ten years.

Back in January I posted a pair of VIX / S&P 500 tables that outlined the performance of the VIX and the S&P 500 given recent changes in the VIX, as well as the current level of the VIX. In response, reader Nazumo asked:

A few weeks back I outlined the Ugly Bond Math that an aggregate bond index with a 2% yield to maturity means for investors:

It means that investors should not expect more than 2% annualized from your bond allocation over the next five years, UNLESS you are willing to reach for yield via lower quality credit, non-US exposure, or increased duration.

It also means that if you have a 60% equity / 40% bond allocation, to reach an 8% all-in annualized return your equity allocation needs to return roughly 12% / year over the next 5 years.

This is based on my post Equity Valuation Based on GDP Growth with a slight twist.

Update: the Yahoo Finance data for LMVTX that I had used appears to be wrong (no clue why and quite frankly concerning). The chart has been replaced by one from Morningstar.

Following the Legg Mason announcement that Bill Miller will step down as CIO after a 30 year run with the firm, Abnormal Returns details the difficulty of providing consistent above average equity returns:

Bill Miller co-manager of Legg Mason Capital Management Value Equity announced he was stepping down as CIO of LMCM effective April 2012. Like Woods Miller had a fifteen year period where he was seemingly unstoppable. His fund topped the performance of the S&P 500 every year over this time period.

Bill Miller has managed the Legg Mason Capital Management Value Equity fund (LMVTX) since 1982 and results of that data (relative to the S&P 500) is shown below. The data now shows the average performance pre-1991, the remarkable performance from 1991-2006, and the underperformance since due to the misplaced bets on financials.

Back to Abnormal Returns on the potential danger of allocating to outperforming managers:

In investing a fall from grace is a common occurrence. In 2011 we have seen both John Paulson who conducted the “The Greatest Trade Ever” and Bruce Berkowitz, Morningstar’s manager of the decade both stumble badly.

Source: Morningstar

The WSJ reports:

U.S. industrial production grew in September but the gain was small, underscoring the economy's lack of vigor.

Production rose by 0.2%, with a modest gain in manufacturing and a sharp drop in utilities caused by moderating weather. The Federal Reserve report on Monday showed overall production was flat in August, revised down from a previously estimated 0.2% increase.

Manufacturers in the U.S. have been feeling the weight of a lackluster economy, hamstrung by high unemployment. While it is still growing, the factory sector has, with the overall economy, slowed.

Along with taking a deeper look at macro trends / releases to try to figure out this whole economy thing (in these all-too-interesting times), I spend quite a bit of my time creating (long-term oriented) trading models. The goal? To better allocate my investments by taking away some of my emotion.

The following model I will walk through is a simple model (available for download here) based on my friend Meb Faber's (of World Beta blog and Cambria Investment Management) Timing Model.

What is it...

It is an Emerging Market "EM" timing model that allocates between two EM sectors... fixed income and equities. As a way of background, since 1999 (I could only pull data for both indices as of December 1998 - due to the methodology below, the start of the model is 10 months later), both EM fixed income and equities have had very similar returns, but have had VERY different ways of getting there (see chart below). At a high level, EM equity tends to outperform when both are trending higher, but EM fixed income outperforms when EM beta struggles.

With that in mind... what is the model? On an end-of-month basis:

• If EM Equity Total Return index > 10-Month moving average, allocate to EM Equities
• If EM Equity Total Return index < 10-Month moving average, allocate to EM Fixed Income

The result? Over this time frame, the rotation strategy has significantly outperformed both EM fixed income and equities with volatility and drawdown levels right between the two (note that a 50/50 blend had returns of around 10.7% with slightly less volatility than the rotation strategy).

If anyone can pull data for EM indices going back further in time, please send my way as I'd like to see how this performs over the longer term.

Source: MSCI, JP Morgan, World Beta

My recent post Corporate Profits, Economic Growth, and Equity Valuation outlined that equity performance can be quite volatile, but over the long-run tends to mean revert back to its underlying factor... economic growth.

Which brings me to a model created by the great Eddy Elfenbein (of Crossing Wall Street), which I initially came across in his post What if the Stock Market Were a Bond, back in October 2010. Eddy's explanation of that concept:

I took all of the historical market performance of the S&P 500 (including dividends) and invented a hypothetical long-term bond that matched the market’s monthly gains step-for-step.

I assumed that it’s a bond of infinite maturity and pays a fixed coupon each month.

The result, which starts December 1925, is the following (reproduced) chart.

Crossing Wall Street Model for Stocks (12/1925 - 8/2011)

While I expected a strong relationship between the above chart with forward equity returns (the model is driven by equity performance, but accounts for the market being rich / cheap to its long-term trend and normalizes returns using backward and forward looking performance), I was surprised by how closely it tied (data was pulled from Irrational Exuberance).

Crossing Wall Street Model vs Ten Year Forward Equity Returns

Same Chart, but a Change in Scale to the Right Hand Side

The likely question is how well this model will predict the future as it shows a 12%+ annualized ten year forward return. My initial thought is don't read too much into the model for predictive power UNLESS the underlying factors that drove the last 85 years of equity performance are expected to continue (and at the same level). In addition, Eddy lays out one more issue:

There’s one hitch, though. I have to choose a starting yield-to-maturity for the beginning of the data series in December 1925. So this isn’t a completely kosher experiment because the starting point is based on my guess.

This issue can be seen in the below model which goes back further... all the way to 1871. Rather than predict a forward ten year equity return of more than 12+%, the model predicts returns of less than 5% (due to lower equity returns between 1871 and 1925).

Source: Irrational Exuberance / Crossing Wall Street

Scott Grannis asks:

Corporate profits are fantastic—what's wrong with equity prices?

As I've discussed numerous times (an example is Equity Valuation Matters), over the long run, earnings matter for equities and those earnings are very closely tied to underlying economic activity. However, over the short-run, earnings (and equity prices) may dislocate from the underlying economy due to a number of factors. In the current market where earnings have dislocated in a positive direction, some reasons may include cost cutting, accounting that allows banks to smooth write downs, low taxes, cheap financing, and a lack of competition for corporations (i.e. the struggles we've seen within the small business sector).

This is another way of saying that all earnings are not created equal. If earnings could in fact consistently grow faster than the underlying economy, then earnings would eventually be larger than the economy itself (a mathematical impossibility). A warning sign is that in the most recent data, as shown in Scott's chart, corporate earnings as a percent of GDP are above 10%, 4% above its 50+ year average.

While this 10% level is unprecedented over the past 50+ years, dispersion between earnings and/or equity performance and nominal economic growth is not. However, in the long-run (sometimes a very long-run), the relationship tends to be very tight. The chart below shows this connection in a chart normalizing data going back to 1951 (the BEA has data going back three more years to 1948, but the relationship is the same).

After I wrote my post on Monday about the huge divergence in yields between stocks and bonds, I wondered just how historically unprecedented this divergence was. And now, with the help of this fabulous chart (many thanks to Nick Rizzo, Dan Burns, and Stephen Culp), it’s pretty easy to see: we’re at levels which match those at the height of the financial crisis, and which are otherwise historically utterly unprecedented.

Indeed, from 1985 through about 2002, it was just as common for the S&P earnings yield to be lower than the Treasury yield as it was for the yields to be the other way around. The two tracked each other, and the spread between them almost never moved beyond 2 percentage points either way.

I've been researching and analyzing a number of rotation / momentum strategies of late (details potentially to follow), which is one reason why I was so interested in the recent GLD / SPY Rotation Strategy posted by Michael Gayed over at The Big Picture. In a nutshell the strategy attempts to follow rolling monthly momentum to allocate between gold and the S&P 500. He concludes:

Of course, past performance is not indicative of future results, but the simple binary decision of being either long SPY or long GLD depending on which is outperforming the others does seem to suggest alpha can be generated.

What I Like

Before I dive into the issues I have with the analysis, here is what I like...

I like that while the strategy was only allocated to gold about 50% of the days, it still tracked the performance of gold with a correlation of .70 on a monthly basis. That is pretty staggering. Why do I like that? Because it opens up the possibility that it closely tracks gold when gold outperforms and may track equities when equities outperform.

Issues

That said, here are my main issues with the model:

• The data set is very limited
• The data is from a period in which gold significantly outperformed equities

If you were to have asked me prior to seeing the analysis if I was interested in a model that involved gold and equities that outperformed equities over the past 6 1/2 years, my response would have been a very easy no. Unless the model shorted gold, it would have been just about impossible NOT to outperform equities over that time frame (gold is one of the top performing asset classes since 2004; equities one of the worst).

As a result, I would have been much more interested in hearing about a model that outperformed gold over this time, rather than consistently underperform over its history (20.7% annualized returns vs. 17.9% annualized returns), without much of a reduction in volatility (21.1% vs. 20.3%).

Deeper Dive

Keeping those limitations in mind, lets dive into the idea that gold is a good momentum strategy. The below chart summarizes the performance of the model based on different periods of exhibited "strength" in the model as defined by the level that the GLD / SPY index was above its 20 day moving average and the corresponding one day forward average return in the price of gold and the S&P 500.

An interesting observation is that the only level that gold did not outperform was when the GLD / SPY index was greater than 10% above the 20 day moving average (note that this was less than 2% of all trading days) and GLD / SPY outperformed most when the GLD / SPY index was more than 10% below the 20 day moving average. This:

1. Indicates the GLD / SPY index outperformed the S&P 500 because gold in most instances outperformed the S&P 500
2. The model actually shows gold and S&P 500 exhibit mean reversion at extreme levels

Update:

I was able to find Gold prices going back to 1992 (the inception of the SPY) over at USA Gold and recreated the model using Gold rather than GLD. The results don't seem too promising prior to the beginning of the gold rally that started in 2001.

Source: Yahoo Finance

An update (with a small addition) of a post from May 2010

Below is a chart of just that going back to 1951 and the corresponding 60 year average.



Step 2)

Step 4) Calculate the percent the S&P 500 Index is over or under valued relative to each calculated index.

Note 1: under these methodologies, the S&P 500 is currently at or above fair value, still implying a decent ten year forward change in the S&P 500 plus dividends minus inflation.
Note 2: a change in the starting value of the FV Index would simply shift the x-axis to the right or left (i.e. it would not change the relationship between the two)

Source: Irrational Exuberance

The Big Picture notes that today's S&P 500 performance (-2.05%) was the worst in 6 months.



More interesting is the frequency of -2% days over the past 60 years. The chart below shows the number -2% days over 100 trading day periods over that time. As can be seen, while we had a "great moderation" from October 2003 through February 2007 (a whopping 850 trading days without a 2% down day), the frequency seems to be growing steadily since the early 1970's when there are periods of market duress.



Source: Yahoo Finance

Professor Damodaran (via World Beta and Abnormal Returns):

S&P's most recent update indicates that US companies, after a pause for about a year after the banking crisis, are back in the buyback game. In the third quarter of 2010, the S&P 500 companies bought back almost $ 80 billion of stock, up 128% from the third quarter of 2009.

While getting cash back to shareholders is the whole point of investing in stocks (timing of returning that cash is potentially a broader question), the higher buyback yield is not necessarily a great thing; it is a great thing if the cash is buying back stock when cheap... not when expensive. And when were corporations buying back the most? Q2 and Q3 2007 (i.e. the market peak). The lowest? Q1 and Q2 2009 (i.e. the market trough).

Professor Damodaran does provide some rationale / discussion into why the trend has moved to buyback vs. dividend:

• Manager compensation: buybacks increase the price of stock for manager option grants
• Uncertainty about earnings: buybacks are a lot more flexible than a steady dividend
• Changing investor profiles: investors that are more focused on stock price
• Higher earnings per share: less shares outstanding = more earnings per share (tested here)

Source: S&P

Floyd Norris (via The Big Picture):

Consider the performance of the Standard & Poor’s 500 in 1969, the year the Jets won their only Super Bowl. It was down 11.4 percent.

Contrast that to the market’s performance after victories by any of the other teams still in contention. The market has never gone down after any of them won the Super Bowl.

The iPhone is coming to Verizon! The iPhone is coming to Verizon! iPhone users sick of AT&T (i.e. me) have rejoiced. Should stock holders rejoice as well?

Lets rewind and see just how much AT&T has outperformed since that launch. To Wikipedia:

The first iPhone was introduced on January 9, 2007.