Tag: Stock market forecast

Stock market prediction: Monthly S&P 500 Forecast

Monthly S&P 500 forecast for July 2026

July 1st, 2026

Our monthly S&P 500 forecast for July is a 0.81 percent increase over the average of June 2026.

The model-based forecast takes into account the changes in oil prices and wages. However, a forecast model cannot possibly capture the full impact of uncertainty caused by tariff wars and geopolitical tensions, such as the war in the Middle East.

S&P 500 forecast July 2026, Aktienprognose Juli 2026
Price returns, the historical data from June 30th 2026

Mid-June jitters fade away

Market optimism, despite ongoing geopolitical tensions, dominated the first two months of the second quarter. At the end of May, the S&P 500 index was 5.1% higher than at the end of April. June had some mid-month jitters, which eased toward the end of the month. The index ended June 0.9% below its end-of-May level.  

The US economy has not shown clear signs of weakening as the labor market remains resilient and GDP growth is respectable by historical standards. That said, May’s inflation numbers, despite being in line with expectations, caused market tremors. Any optimism regarding a rate cut this year evaporated. The US dollar index reached a 13-month high after the Fed meeting.

As new Fed Chairman Kevin Warsh emphasized his commitment to price stability at the Fed’s June 16–17 meeting, investors interpreted his first speech as the Chairman as hawkish. Warsh also abandoned the Fed’s so-called ‘forward guidance’ communication policy about hinting at forthcoming interest rate changes. Our own research in the quarterly forecast section reveals that ‘forward guidance’ did not have a measurably significant effect on reducing market volatility. Overall, markets have to adjust to the new style of communication. After the June 17 ceasefire agreement between the US and Iran, stock markets recovered some of the early-month losses.

Although the S&P index remains slightly overvalued by historical standards, the earnings potential of the AI-fuelled boom is not easy to judge by the historical trajectory of company earnings. This explains why investors do not seem to be worried about the high forward P/E ratios.


PMI deteriorates, and consumer confidence slightly improves

The Chicago Purchasing Managers’ Index (PMI)  fell to 56.7 in June from 62.7 in May. The index averaged 54.25 between 1967 and 2026. The contraction in business activity has been a theme over the last two years. The latest dip in the data was caused by the fall in new orders.

The Conference Board’s consumer confidence index ticked up by 0.6 points to 91.2 (1985=100) in June, up from a downwardly revised 90.6 in May. The Present Situation Index—based on consumers’ assessment of current business and labor market conditions—fell by 3.0 points to 116.4. The Expectations Index—based on consumers’ short-term outlook for income, business, and labor market conditions—rose by 3.0 points to 74.4. The survey period for this month’s preliminary results was June 1–23. The US-Iran ceasefire agreement and falling oil prices have eased future inflation worries. However, consumers are feeling less optimistic about the prospects of getting a job. 

Inflation rises sharply, and Q1 GDP growth is revised up

The annual inflation rate in the US increased to 4.2% in May from 3.8% in April 2026, in line with market expectations. This was the highest rate since April 2023.  Increasing energy and materials prices were the main drivers of the higher inflation rate.

The personal consumption expenditures (PCE) index, a key barometer of inflation and consumer spending, rose at a 4.1% annual pace in May, in line with the market consensus.

Core PCE, which excludes the more volatile food and energy categories, grew 3.8% in May, up from 3.3% in April, also in line with market forecasts.

The third and final estimate for 2026 Q1 GDP growth was revised up to 2.1% from the second estimate of 1,6 %. The upward revision was mainly caused by a downward revision to imports. However, consumer spending was revised down to 0.5% from 1.4% (Source: Bureau of Economic Analysis (BEA)).  

No rate cut is expected in July

After the 25 bp rate cut in December 2025, the Fed’s target range for interest rates is 3.50% to 3.75%.   

As Kevin Warsh became the new Fed Chairman, he sent hawkish signals to investors in the June meeting. He stressed that the Fed has failed to achieve its target 2% inflation for five years. His commitment to lowering inflation by employing a more flexible monetary policy is something investors need to adjust.

Although energy prices have fallen more than 20% with the opening of the Strait of Hormuz, consumer prices will likely remain elevated at least in Q3. Therefore, we believe it is unlikely that the Fed would cut interest rates before next year. A hawkish monetary policy stance would even demand a rate increase. This would indeed be justified, as the Fed’s slow post-pandemic policy actions were blamed for a prolonged period of elevated prices.

S&P 500 index is close to fair value

According to FactSet Insights from June 26, the forward 12-month P/E ratio for the S&P 500 is 20.1. This P/E ratio is above the 5-year average (19.9) and above the 10-year average (19.0). For 2026 Q2 reports that the blended (year-over-year) earnings growth rate for the S&P 500 is 23.1%. If 23.1% is the actual growth rate for the quarter, it will mark the second-straight quarter of earnings growth above 20%.

Our monthly S&P 500 forecast is a model-based fair-value estimate. Announcements of tariffs and cancellations cannot be captured in our model unless the impact appears in historical data. The possible impact of geopolitical tensions is fed into the model through keyword searches (Google clicks) and the advanced retail sales index. However, these variables perform better in normal times. Our quarterly S&P 500 forecast discusses these issues in more detail.

About us

This blog presents the S&P 500 forecasts based on fundamental econometric models and historical economic and financial data.

Our blog refers to a quote attributed to Mark Twain, with the conviction that a thorough study of the past data throws some light into the future, as long as one is aware of the caveats that the future is not an exact replica of past events. Thus, our mission is to detect the ‘rhyming’ signals by fitting the best model to the historical data, bearing in mind that the future never plays out exactly the same; there are forecast risks associated with ‘’known unknowns” and “unknown unknowns”.

Our data is based on official sources, and not third-party data providers. Our facts are regularly checked for inconsistencies.

Thinking outside the black box of machine learning

In contrast to the various websites that present the forecasts of hundreds of financial instruments ranging from stock market indices to crypto-currencies (e.g. tradingeconomics), our forecasts are focused on a few instruments and are labor-intensive. Our forecasts are the product of meticulous analysis of the data, composed of carefully chosen economic indicators based on theory and expert knowledge. Furthermore, our forecasts entail vigorous analysis via sophisticated econometric methods that have been back-tested and cross-validated. We ensure that the coefficient signs of the explanatory variables are in line with our economic intuition.

Our empirical findings are not an output of a black-box optimization process. Having said this, we also test the explanatory power of all the chosen economic indicators using machine-learning algorithms. We use algorithms such as Deep-learning, Logit, Random-Forest classifiers, K-nearest Neighbor, XGBoost, Extra Trees Classifier, and Support Vector Machine, to ensure that the choice of the indicators sufficiently discriminates the positive growth from negative growth signals in the forecast variables.

Our keyword algorithm predicts the US consumer sentiment

The S&P 500 predictions involve multi-equation models where some of the endogenous explanatory variables such as corporate profits and advance retail sales are themselves forecast using our proprietary models. Our models employ a totally original set of ‘keyword-based indicators. To the best of our knowledge, these indicators have never been used before. These indicators seem to capture the fluctuations in consumer tendencies rather well. Our models adjust all these indicators for seasonal variations. Thus, any changes in consumer tendencies due to various seasonal factors are taken into account.

The model outputs shown in this blog are point forecasts computed on the date shown in the graphs. They should be viewed as positive or negative signals for the direction where the markets are headed. The confidence intervals with regard to the accuracy of the forecasts refer to a wider range of possible outcomes. Depending on various irregular events/news, the actual outcome can be closer to the lower or upper confidence bound.