A simulation-based valuation of the S&P 500: October 2022

The figure below shows two simulation-based valuations of the S&P 500. They assume a fair price-to-earnings (PE) ratio for the S&P 500 that is the inverse of half of the 10-year U.S. Treasury yield. The price (at the top) is the most recent top value of the S&P 500.

The numbers on the left consider a rather benign scenario: S&P 500 earnings in 2022 are up by 10% from the previous year, and the 10-year U.S. Treasury yield is at 3.00%. The numbers on the right refer to a more likely scenario: S&P 500 earnings are up by 5%, and the 10-year U.S. Treasury yield is at 4.00%.

The second scenario takes us to a fair price for the S&P 500 of 2,693.12, which is 44.11% down from the most recent high. The video linked below discusses these simulations, some of the most recent values for the simulation inputs, and a few other options.

A simulation-based valuation of the S&P 500: August 2022

A simulation-based valuation of the S&P 500: July 2022

The figure below shows two simulation-based valuations of the S&P 500. They assume a fair price-to-earnings (PE) ratio for the S&P 500 that is the inverse of half of the 10-year U.S. Treasury yield. The price (at the top) is the most recent top value of the S&P 500.

The numbers on the left consider a rather benign scenario: S&P 500 earnings in 2022 are up by 10% from the previous year, and the 10-year U.S. Treasury yield is at 2.50%. The numbers on the right refer to a more likely scenario: S&P 500 earnings are down by 10%, and the 10-year U.S. Treasury yield is at 3.50%.

The second scenario takes us to a fair price for the S&P 500 of 2,638.16, which is 45.25% down from the most recent high. A sobering thought, given the rally that we are in right now, which many believe to be nothing more than another bear market rally.

The recent negative GDP growth figure was revised down to -1.6%

As it turned out, the negative GDP growth figure mentioned in our last post was revised down to -1.6%, from -1.5%. This is related to our recent post on the Atlanta Fed. From Tradingeconomics.com:

  

"The American economy contracted an annualized 1.6% on quarter in Q1 2022, slightly worse than a 1.5% drop in the second estimate. It is the first contraction since the pandemic-induced recession in 2020 as record trade deficits, supply constraints, worker shortages and high inflation weigh. Imports surged more than anticipated (18.9% vs 18.3% in the second estimate), led by nonfood and nonautomotive consumer goods and exports dropped less (-4.8% vs -5.4%). Also, consumer spending growth was revised lower (1.8% vs 3.1%), as an increase in spending on services, led by housing and utilities was partly offset by a decrease in spending on goods, namely groceries and gasoline. Meanwhile, private inventories subtracted 0.35 percentage points from growth, much less than a 1.09 percentage points drag in the second estimate. Fixed investment growth remained robust (7.4%) but housing investment was subdued (0.4%, the same as in the second estimate)."

Is the Atlanta Fed predicting an imminent recession?

Fed funds rates, 10-year Treasury rates, and recessions

Can 10-year compound annual S&P 500 returns help predict market crashes?

As someone interested in applying data analytics techniques to finance and economics, I tend to look for leading indicators that contribute new insights when compared to existing ones.

It also helps if they are not obvious, and go somewhat against consensus; e.g., in interviews on media covering financial markets issues, frequently experts express the opinion that recent market gains do not influence future performance.

If we put this opinion to the test against data, we find that the opposite is what usually happens, as you can see from the graph below, which shows annualized 10-year compound changes in the S&P 500.

Dividends are not considered in this depiction. The graph is based on monthly data points from January 1910 to March 2022, where the annualized changes are calculated for each month as follows.

SP10(T) = ( SP(T) – SP(T-10y) ) ^ (1/10) – 1

In this equation we have:

SP10(T): the annualized 10-year compound change in the S&P 500 at a given point in time (T).

SP(T): the value of the S&P 500 at a given point in time (T). For this illustration, we used the average value of the S&P 500 for each month.

SP(T-10y): the value of the S&P 500 exactly 10 years prior to the time T.

This is a fairly easy calculation, which relies on a single variable. The graph seems to show that periods in which the SP10 moves quickly above 10% typically precede market crashes.

As a leading indicator (not a cause), the SP10 may not be precise enough to be used alone. Nevertheless, it can be used together with other indicators (e.g., Shiller’s PE10 ratio) in a more complete predictive model.