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Euro Stoxx 50

Equity index · Monthly series · IX-SX5E

Latest, October 2026

6,131.3 pts

-2.2% from September 2026

Open interactive chartEuro Stoxx 50 in the app

775652722787November 2016October 2027
History through October 2026, the forecast path to October 2027 (dashed) and its 80% interval (shaded).

Forecast

Forecast for October 2027: 6,151.4 pts, with an 80% interval of 4,365.3 pts to 7,650.2 pts.

Forecast path. Intervals are shown where available.
PeriodForecast80% low80% high
November 20266,182.1 pts5,747.3 pts6,650.3 pts
December 20266,217.4 pts5,607.8 pts6,839.8 pts
January 20276,267.4 pts5,687.7 pts6,801.0 pts
February 20276,306.2 pts4,949.8 pts7,487.5 pts
March 20276,312.4 pts4,822.3 pts7,585.5 pts
April 20276,318.6 pts4,868.8 pts7,580.7 pts
May 20276,316.7 pts5,052.7 pts7,377.1 pts
June 20276,301.2 pts4,602.7 pts7,756.5 pts
July 20276,272.0 pts4,583.7 pts7,679.9 pts
August 20276,200.3 pts4,844.3 pts7,361.0 pts
September 20276,180.9 pts4,520.9 pts7,564.0 pts
October 20276,151.4 pts4,365.3 pts7,650.2 pts

Model: State-space model, 167M (foundation model). Forecast generated 2026-11-14.

AI confidence

Mixed evidence

The tests show no consistent, material advantage over the no-change baseline.

Model: State-space model, 167M (foundation model)

Accuracy vs naive
-1%Matches the no-change baseline over 6 tests (6 tests, 3 won)
Direction
50%No clear edge over a coin flip (36 of 72 calls right in 6 tests)
Turning points
10 of 27Anticipated some turns (27 turns in 6 tests, 0 without a turn)
Error vs baseline
1% higherError ratio 1.01; 1.00 is a tie.
Tests won
3 / 6Complete recent tests excluded from model selection; ties count as no win.
Test period
2020-11-01 to 2026-10-0112 observations ahead per test.
80% band coverage
80%Observed outcomes inside the band across all stored test windows.
How this assessment is made

AI confidence describes historical evidence for this forecast, not a probability of being correct. Each backtest fits on data available before its test window. The baseline carries the last value forward. Supported evidence requires at least six complete, non-overlapping tests, an error ratio below 0.90 (rounded to two decimals), and wins in a majority of tests. Ratios from 0.90 to below 1.10 are on par; 1.10 or above is weak evidence. Inconsistent wins produce mixed evidence. For a selected model, only the recent tests excluded from model selection determine this label. These are historical simulations using the available data, not a live trading track record; revisions and foundation-model pretraining can limit how closely they reproduce a past decision. Past performance can change.

Replay past tests

Model comparison

5 of 5 models evaluatedModels are selected on older tests and evaluated on separate recent tests. All four classes completed their backtests.

Models tested

State-space model, 167M scored lowest on the 6 older tests (0.98) and was chosen. The 6 recent tests played no part in the choice and give its grade (1.01). The search for a model that beats the naive forecast on both sets of tests goes on. Scores are MASE: a model's errors divided by the naive forecast's, so 1 is a tie.

4 model classes completed the tests: Foundation model, Machine learning, Statistical, Neural network.

Every model tested on this series.
ModelClass and computeOlder testsRecent testsRole
ci-proto (foundation model)Foundation model · CPU0.981.01Serving
Timestral (foundation model)Foundation model · CPU0.991.06Tested
Naive forecast (last value held)Benchmark · CPU1.001.00Benchmark
CatBoost (machine learning)Machine learning · CPU1.021.12Tested
AutoETS (statistical)Statistical · CPU1.070.93Tested
N-HiTS (neural network)Neural network · CPU1.301.26Tested

Uses ci-proto, released by Continuous Intelligence. Continuous Intelligence does not endorse or approve this product or service. (ci-proto is shown as State-space model, 167M.)

Reading

It is above 96% of the 119 earlier readings since November 2016.

Written from the figures by a fixed template; no AI model is involved.

Recent history (24 observations)
The 24 most recent observations, newest first.
PeriodValue
October 20266,131.3 pts
September 20266,269.0 pts
August 20266,420.2 pts
July 20266,358.0 pts
June 20266,328.1 pts
May 20266,050.6 pts
April 20265,881.5 pts
March 20265,569.7 pts
February 20266,138.4 pts
January 20265,947.8 pts
December 20255,791.4 pts
November 20255,668.2 pts
October 20255,662.0 pts
September 20255,530.0 pts
August 20255,351.7 pts
July 20255,319.9 pts
June 20255,303.2 pts
May 20255,366.6 pts
April 20255,160.2 pts
March 20255,248.4 pts
February 20255,463.5 pts
January 20255,286.9 pts
December 20244,896.0 pts
November 20244,804.4 pts

Source

Data: public market data feeds.

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