Several Models Highlight The Case For Downgrading The 10-Year Return Outlook For US Stocks

By James Picerno | The Milwaukee Company

• US stock market performance is expected to downshift over the next decade vs. recent history.

• The S&P 500 is projected to earn 5.5% annualized over the next ten years, based on the average estimate for five models.

• The market’s downgraded forecast compares with a 10%-plus annualized gain over the past decade.

Forecasting the US stock market’s performance is always laden with caveats, but framing the outlook in binary terms arguably offers a bit more confidence for projecting what the future might deliver.

There are no guarantees, of course, but a review of history suggests that the surge in rolling 10-year performance for the S&P 500 Index over the past decade or so will give way to softer results in the years ahead.

Part of the logic for this view is that the market’s rolling 10-year return has experienced a loose but discernible cyclical pattern. Although the market’s ebb and flow is uneven, it’s reasonable to assume that it will continue. Why? For the same reasons that have driven a quasi-cyclical patterns in the past: economic, financial and political trends evolve, providing catalysts that encourage investors to continually revise expectations.

Estimating ex ante performance is, of course, prone to error for the simple reason that the future is forever surprising. Nonetheless, generating forecasts can be useful as the first step in managing expectations for looking forward. On that score, TMC Research presents five models to project the S&P 500’s 10-year return (a brief summary of each model is discussed below). The average forecast (red line in the chart below) is a relatively moderate 5.5% (annualized return). The individual estimates for the decade ahead range from a low of around 2% up to 7.4%.

Although any market forecast should be viewed with a dose of skepticism, it’s striking that the mean estimate shown in the chart is roughly half the 10.4% annualized increase for the S&P 500 over the past decade. The exact return outlook is always a guesstimate, at best, but the fact that the average of several models – each with a different set of pros and cons – is projecting a substantial haircut for performance offers a basis for managing expectations down relative to recent history.

Here's a quick review of each of the five models used to generate the forecasts in the chart above:

CAPE Ratio Model: this stock market valuation indicator, maintained by Professor Robert Shiller, is calculated using real earnings per share for the S&P 500 based on a rolling 10-year window. TMC Research uses the CAPE ratio to generate an implied return for the stock market via linear regression.

Earnings Yield Model: the stock market’s implied ex ante performance is derived from the S&P 500’s earning yield, defined as the inverse of the price-to-earnings ratio. A linear regression model calculates the implied expected return from the relationship between prices and yields.

ARIMA Model: In contrast with the two models above, which use valuation to infer future return, this estimate uses statistical analysis to generate a forecast. An autoregressive integrated moving average (ARIMA) model is a type of regression analysis that’s run on a rolling window of the market’s return history to estimate future results.

Bayesian Model: This statistical model uses lags as a basis for updating so-called “prior beliefs” on a rolling basis to estimate the effects of previous effects on the S&P 500 to forecast return.

Average Historical Return Model: This naïve estimate is a simple average of all the rolling 10-year returns since 1960.