Monthly Archives: March 2014

Earnings & Returns: A Longer Look (03/31/14)

In the last post I explained how stock returns can be explained by earnings growth and changes in P/E multiples. Josh Brown had a similar post on his Reformed Broker blog (“Earnings drive the market” LOL) that got me thinking about other ways to show this relationship. Frankly, after trying dozens of approaches (index, smooth, correlation, R-square, inflation-adjustment, etc.) I couldn’t really come up with anything very compelling. So what follows is my best attempt to take a look at the long-term relationship between earnings, prices and P/Es.

For this analysis I’m using Online Data by Robert Shiller. The data goes back to 1871 and was used in his seminal book “Irrational Exuberance”. Exhibit 1 shows S&P Price, Earning and P/E ratios on the logarithmic scale. They are indexed starting with 100 in 1871. There appears to be relatively clear relationship between price (blue line) and earnings (red line). While P/E multiple has been slightly trending up, it generally oscillates back and forth based on the investor sentiment (Exhibit 2). Please note that these P/E ratios are based on reported earnings and will be different from my last post which used operating earnings data from S&P.

Exhibit 1 – S&P Price, Earning and P/E Ratios


Source: Online Data by Robert Shiller; PlanByNumbers

Exhibit 2 – S&P P/E Ratio with Its Trendline


Source: Online Data by Robert Shiller; PlanByNumbers

Another approach would be to look at the rolling 10-year correlation of S&P Returns with Earnings Growth and Annual % Changes in P/E Ratios. This allows us to step back from the exact relationship for each year as described in Reformed Broker post and analyze it in 10-year increments. The calculation is a little convoluted so I’ll attempt to explain it in Exhibit 3. Columns 2-4 have the raw metrics, I then calculated the Year-Over-Year % Change for each of them in columns 5-7. The final calculation is the correlation over the last 10 years between 5 and 6 resulting in column 8; then between 5 and 7 for column 9. A quick refresher: a positive correlation means the two variables move together, while a negative correlation indicates that they move in the opposite directions. A higher correlation number (positive or negative) means that the relationship is stronger.
Exhibit 3 – Calculating Rolling Correlation Example


The resulting chart is shown in Exhibit 4 with blue line representing column 8 and red line showing column 9. As is often the case with correlations, it changes over time going from positive to negative relationship several times over the 150 years. Interestingly, from 1975 to 2000 earnings had negative correlation with prices while P/E was strongly positive. This would suggest that the index was driven by expanding P/E ratios while earnings growth wasn’t as important. Than in 2000 there was an abrupt change in regime and earnings became an important driver of index performance. At the same time, P/E ratio correlation plummeted and turned strongly negative. This situation peaked in 2008 and has been slowly abating since.

Exhibit 4 – Rolling 10-Year Correlation of S&P Returns with Earnings Growth and Changes in P/E Ratios


Source: Online Data by Robert Shiller; PlanByNumbers

I realize that this analysis was not highly scientific, but the general takeaway is that: Yes, over time there is a positive relationship between earnings growth and index returns.  Market’s mood does change and sometimes it cares more about P/E multiples while others are driven by earnings growth.

Simple Math of Earnings, Multiples & Returns

Professional investors like to throw around fancy words to make themselves feel smart and important.  One of those terms is “Multiple Expansion”.  I figured that 2013 was a great example to illustrate what they mean.

P/E ratio or Price-to-Earnings multiple is probably the most common way to value a stock or a market index.  Let’s take a look at Exhibit 1 and decompose what happened in 2013.  Bear with me here,  The S&P 500 Index closed the year at 1,848.36 up from 1,426.19, so return was (1,848.36 ÷ 1,426.19) – 1 = 29.6%Note: This is the price return which excludes the 2.5% dividend yield.  Operating Earnings grew from 96.82 to 107.07 last year, a jump of 10.6%P/E multiple at the end of 2013 was 1,848.36 ÷ 107.07 = 17.3 times.  This means that the investors were willing to pay 17.3 dollars for each dollar of earnings.  This number went up from 14.7x a year ago – BINGO! – we got MULTIPLE EXPANSION of 17.2%.  Now we can also calculate that multiple expansion accounted for about 62% of the 29.6% return for the year.

Exhibit 1 – Earnings, Multiples and Return Breakdown for 2013


Exhibit 2 shows the same data for each year since 1990. Exhibit 3 displays the middle three columns of this table in a chart format for the more visually-inclined readers.  There are some interesting takeaways from this analysis (at least interesting for a data geek like me).  Earnings tend to increase over the years while P/E multiples tend to jump around a lot.  There were only 5 years out of 24 where earnings decreased year-over-year.  Earnings are typically driven by the business cycle and economic growth, so they closely resemble GDP growth trajectory.  P/E ratios, on the other hand, are largely driven by investor sentiment which is quite fickle.  Investors might be willing to pay 25 times earnings one year and then balk at the 15x multiple the next.

Exhibit 2 – Annual Earnings, Multiples and Returns Since 1990


Exhibit 3 – Annual Earnings, Multiples and Returns Since 1990 – Chart Illustration


Now that we understand how multiples and earnings growth work together to produce price appreciation, we’ll take a look at the longer history of those metrics in a future post.

Data Note

Standard & Poor’s provides free regularly-updated spreadsheets with a wealth of date about the S&P 500 index earnings, dividends, constituent companies, etc.  This detailed information is one of the reasons so many people use the index in their market analysis.   The spreadsheets can be found by going to  Then click on ADDITIONAL INFO dropdown and select “Index Earnings” – this will open an excel spreadsheet with multiple tabs containing variety of earnings data.