Tag: Stock market forecast

Stock market prediction: Monthly S&P 500 Forecast

Monthly S&P 500 forecast for October 2026

October 1st, 2026

Our monthly S&P 500 forecast for October is a 0.83 percent increase over the average of September 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 monthly forecast S&P 500 September forecast Aktienprognose
Price returns, the historical data from September 30th 2026

Self-Fulfilling Prophecy of the ‘September Effect’?

September is historically known as the worst-performing month in stock markets, with the S&P 500 index posting negative returns 56% of the time since 1928. Some of this seasonality has a reasonable basis. Investors try to reduce their tax bill by selling loss-making stocks, and fund managers quite often rebalance the asset mix of their portfolios after their holiday break. However, mostly any discernible impact has to do with behavioural biases of investors.

Despite the ongoing Middle East conflict and surging energy prices, the S&P 500 ended September flat over the end of August. The September average of the index was down 0.5% compared with the August average.

US economic indicators were generally good in September: a resilient labor market, strong (Q2) GDP and consumer spending growth, and steady inflation. What spoils the positive picture is rising energy prices and rising US Treasury yields. The recent sell-off in government bonds indicates that markets are not optimistic about inflation cooling further without further rate hikes.

Big Tech is under scrutiny

The 10-year Treasury yield rising above 5% for the first time since the global financial crisis has implications for the massive long-dated bond issuance by big tech funding their planned capex spending. Big Tech’s increased vulnerability to the pitfalls of debt financing is making investors more cautious concerning the tech stocks. If Big Tech struggles to pay back its bond obligations, the systemic risk to the US and global economy would be tremendous. High interest rates also reduce equity valuations.

Overall, investors are scrutinizing gross margins and earnings expectations more closely as their anxiety grows over a possible AI bubble-bust scenario.  

As we stated before, although Big Tech’s ambitious AI CapEx carries some systemic risk, this is really the worst-case scenario. Unlike the 2008 financial crisis, Big Tech firms finance most of their AI investment with solid cash flows. Although the Fed lists AI as a top systemic risk to financial stability just behind geopolitical risks, this is because the sheer scale of AI investments affects US GDP growth.

As we enter October, quarterly earnings season for 2026 Q3 gets underway. Microsoft, Alphaber/Google, Meta, Amazon and Apple are expected to report in October. Markets will no doubt scrutinize whether cloud and AI capex are already generating better revenue growth to justify the high valuations.


PMI jumps, but consumer confidence deteriorates

The Chicago Purchasing Managers’ Index (PMI)  jumped to 58.8 in September from 47.1 in August 2026. This was well above the market forecast of 51.2. The latest data pointed to a renewed expansion in business activity. After last month’s significant contraction, the latest expansion in business activity has been the strongest pace since May.  The expansion was due to increases in production, new orders, and supplier deliveries.

The Conference Board’s consumer confidence index fell by 6.7 points to 81.9 (1985=100) in September, down from 88.6 in August. The Present Situation Index—based on consumers’ assessment of current business and labor market conditions—retreated by 7.9 points to 109.3. The Expectations Index—based on consumers’ short-term outlook for income, business, and labor market conditions—fell by 5.9 points to 63.6. This was a third consecutive monthly decline. The survey period for this month’s preliminary results was September 1-23.

Already in June, US consumers were feeling pessimistic about the prospects of getting a job. This was when the US-Iran ceasefire was in place. The ceasefire violation and the restart of the conflict contributed to the deterioration in consumer sentiment. Consumer appraisals of current business conditions became negative for the first time since September 2024.

Inflation remains steady, and Q2 GDP growth is revised up

The annual inflation rate in the US remained steady at 3.4 % in August. This was in line with market expectations. Despite the renewed conflict in the Middle East and rising energy prices,  August’s inflation did not edge up. However, the lag effects of the elevated energy prices are expected to keep September inflation sticky.

Personal consumption expenditures (PCE), a key barometer of inflation and consumer spending, rose 3.4% in August on an annual basis, also steady with the revised down July (from 3.7% to 3.4%)

Core PCE, which excludes the more volatile food and energy categories, was also unchanged at 3% in August, as the July figure was revised down.

US Q2 gross domestic product (GDP) grew at an annualised rate of 2.2 per cent, revised up from the second estimate of 1,5 %, down from the revised 2.5 per cent growth in the first quarter.  This was the final estimate for Q2. The reading was above economists’ expectations (Source: Bureau of Economic Analysis (BEA)).

Another rate hike in October?

The Fed’s target range for interest rates is 3.75% to 4% after the 25 bp rate increase in September.   

Energy prices have increased about 28 percent because of the renewed hostilities in the Middle East since the end of June. Despite the steady August inflation, consumer prices will likely remain elevated till the end of 2026.

Fed Chair Kevin Warsh’s commitment to lowering inflation to the central bank’s 2% target would have lost its credibility if the Fed had left the rates unchanged in September. In the post-pandemic period, the Fed’s monetary tightening was criticised for being too slow and causing a prolonged period of elevated prices. It is unlikely that Warsh would repeat the same mistake. We believe if September inflation is up in October, the Fed may increase the federal funds rate by another 25 bp.

S&P 500 index is fairly valued

According to FactSet Insights from September 25, the forward 12-month P/E ratio for the S&P 500 is 19.2. This P/E ratio is below the 5-year average (19.8) but above the 10-year average (19.0).

For Q3 2026, the estimated (year-over-year) earnings growth rate for the S&P 500 is 29.1%. If 29.1% is the actual growth rate for the quarter, it will mark the third straight quarter of earnings growth above 25%.

Overall, the index is close to fair valuation, owing to high earnings forecasts, driven by the AI boom. Investors are realizing that company earnings potential cannot be judged by historical standards. Indeed, the AI revolution is increasing productivity and reducing unit costs of most companies in the S&P 500 index. However, a sharp revival of inflation and higher Treasury and credit spreads are the potential threats to this best-case scenario.

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 enters 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.