How to Forecast S&P 500 Earnings Using Macro Inputs

For this note, we’re setting out to do three things:

• Demonstrate how to use select macro variables to forecast S&P 500 earnings growth for end-2026.
• Use the projected earnings growth to forecast those for each of the GICs sectors.
• Highlight which sectors are undervalued on a forward price-to-earnings ratio (P/E) basis.

Of course, there are several different ways to forecast S&P 500 earnings. Equity analysts will generally use a mix of bottom-up metrics to varying degrees. But in our role as macro analysts, we tend to put more of an emphasis on top-down variables. In particular, we rely on three important U.S. economic data points.

The first is the U.S. Consumer Price Index (CPI) – which tends to move pro-cyclically with earnings. Recall, that earnings are reported in nominal terms (meaning that they’re not adjusted for inflation). So, when CPI rises, the prices that firms charge should also increase to maintain margins. Additionally, including this variable pays tribute to the fact that prices will often adapt much quicker to economic realities than costs will (i.e., labour). CPI impacts earnings via the price channel.

The second is the unemployment rate – which is an indicator of where we are in the business cycle and tends to move inversely with earnings growth. To illustrate, remember that the unemployment rate can be framed as a demand indicator. When it rises, consumers will typically cut discretionary spending which leads to slower volumes for businesses. When it falls, consumers will more likely ramp up spending leading to increased business volumes. The unemployment rate impacts earnings via the volume channel.

The third is the Institute for Supply Management (ISM) sentiment gauge – which gives us a sense of the breadth of business optimism and earnings. Our preference is to use a variation of the index compiled by Bloomberg, which weighs the contribution from the manufacturing and services sector based on their relative size in the economy. Simply put, when the ISM gauge is above 50 and increasing, more firms are likely to be expanding activity. Indeed, breadth improvement is often a lead indicator for earnings expansion (and vice versa).

We can take the year-over-year changes in each of the above variables and regress them against S&P 500 earnings growth. This rudimentary model has a reasonably tight fit (r-square value of 0.75), which tells us that the combination of the three does offer some predictive value for earnings growth. In Table 1, we use the relationships from our model to look at two hypothetical scenarios for where things could go by the end of this year, and what the corresponding growth for earnings looks like. For instance, under a recession scenario where inflation declines and the unemployment rate rises, our model would suggest earnings would drop by 11.3%. Conversely, if the economy continues to grow, we’d expect upside pressures to inflation to persist while the unemployment rate could drop to a degree. 

A reasonable base case here would be for earnings to increase by 15.6%. What Table 1 also tells us is that if we assume there will be no changes to any of the three variables by the end of the year, then a reasonable expectation for earnings growth is around 10% (which is just below what the market is expecting).

Table 1 – Projected S&P 500 Earnings Growth Under Our Model 

Source: BMO Global Asset Management, as of January 19, 2026.

From here, we can use the long-term relationships (or regressions) between S&P 500 and each sector to project earnings growth for the latter. Keeping things simple, let’s assume that the current values remain unchanged for our three macro variables. Table 2 shows us what we should expect for earnings growth for each sector under this scenario relative to what the market is expecting. From here, we can see that sectors like Materials, Consumer Discretionary, Health Care and Financials could outperform relative to street estimates (note that we’re overweight Financials and Health Care in our sector portfolio). Conversely, there’s reason to believe that sectors like Tech, Communications Services, Energy and Utilities could underwhelm.

Table 2 – Earnings Estimates: Model output using current levels for macro variables vs Market expectations

Source: BMO Global Asset Management 

Taking this one last step further, Chart 1 shows a scatter plot of the current forward P/E versus the Street’s estimates for earnings in 2026. This additional screen tells us that Materials is already underpriced. And if the above model is correct, then the scale of undervaluation could increase for that sector (ditto for Financials and Health Care). However, the Consumer Discretionary sector already looks as if it’s overvalued – even with the projected increase in earnings surprise.

To summarize the key takeaways:

• Keep an eye on CPI, the unemployment rate and the ISM composite to get a feel for top-down earnings shifts for the S&P 500 in real time.
• Given the current macro set-up, materials, financials and healthcare feel undervalued.

Chart 1 – Materials, Financials and Health Care Are Undervalued

In terms of allocation decisions, consider the following: 

• BMO SPDR Financials Select Sector Index ETF (Ticker: ZXLF)
• BMO SPDR Health Care Select Sector Index ETF (Ticker: ZXLV)
• BMO SPDR Materials Select Sector Index ETF (Ticker: ZXLB)

For more market insights and commentary from BMO ETFs, please visit and bookmark Basis Points.