Natural Gas
Energy · Monthly series · OANDA:NATGASUSD
Latest, October 2026
2.61 USD (exchange quote)
-10.0% from September 2026
Recent history
| Period | Value |
|---|---|
| October 2026 | 2.61 USD (exchange quote) |
| September 2026 | 2.89 USD (exchange quote) |
| August 2026 | 2.92 USD (exchange quote) |
| July 2026 | 2.80 USD (exchange quote) |
| June 2026 | 3.22 USD (exchange quote) |
| May 2026 | 3.14 USD (exchange quote) |
| April 2026 | 2.65 USD (exchange quote) |
| March 2026 | 2.95 USD (exchange quote) |
| February 2026 | 3.08 USD (exchange quote) |
| January 2026 | 6.00 USD (exchange quote) |
| December 2025 | 3.84 USD (exchange quote) |
| November 2025 | 4.61 USD (exchange quote) |
| October 2025 | 3.60 USD (exchange quote) |
| September 2025 | 3.08 USD (exchange quote) |
| August 2025 | 2.93 USD (exchange quote) |
| July 2025 | 3.06 USD (exchange quote) |
| June 2025 | 3.35 USD (exchange quote) |
| May 2025 | 3.19 USD (exchange quote) |
| April 2025 | 3.25 USD (exchange quote) |
| March 2025 | 4.12 USD (exchange quote) |
| February 2025 | 3.92 USD (exchange quote) |
| January 2025 | 3.37 USD (exchange quote) |
| December 2024 | 3.69 USD (exchange quote) |
| November 2024 | 3.11 USD (exchange quote) |
Forecast
Forecast for October 2027: 2.66 USD (exchange quote), with an 80% interval of 1.09 USD (exchange quote) to 4.24 USD (exchange quote).
| Period | Forecast | 80% low | 80% high |
|---|---|---|---|
| November 2026 | 2.66 USD (exchange quote) | 1.59 USD (exchange quote) | 3.74 USD (exchange quote) |
| December 2026 | 2.66 USD (exchange quote) | 1.42 USD (exchange quote) | 3.91 USD (exchange quote) |
| January 2027 | 2.66 USD (exchange quote) | 1.53 USD (exchange quote) | 3.80 USD (exchange quote) |
| February 2027 | 2.66 USD (exchange quote) | 1.39 USD (exchange quote) | 3.94 USD (exchange quote) |
| March 2027 | 2.66 USD (exchange quote) | 1.48 USD (exchange quote) | 3.85 USD (exchange quote) |
| April 2027 | 2.66 USD (exchange quote) | 1.11 USD (exchange quote) | 4.21 USD (exchange quote) |
| May 2027 | 2.66 USD (exchange quote) | 1.09 USD (exchange quote) | 4.23 USD (exchange quote) |
| June 2027 | 2.66 USD (exchange quote) | 1.31 USD (exchange quote) | 4.02 USD (exchange quote) |
| July 2027 | 2.66 USD (exchange quote) | 1.06 USD (exchange quote) | 4.27 USD (exchange quote) |
| August 2027 | 2.66 USD (exchange quote) | 1.09 USD (exchange quote) | 4.24 USD (exchange quote) |
| September 2027 | 2.66 USD (exchange quote) | 1.26 USD (exchange quote) | 4.07 USD (exchange quote) |
| October 2027 | 2.66 USD (exchange quote) | 1.09 USD (exchange quote) | 4.24 USD (exchange quote) |
Accuracy: On par with the naive forecast, more accurate in 5 of 6 test years. Its errors were 1.00 times those of the naive forecast (MASE). The 80% band held 81% of outcomes. The naive forecast keeps the latest value for every future period (a random walk).
AI confidence
Mixed evidenceThe tests show no consistent, material advantage over the no-change baseline.
Model: AutoETS (statistical)
- Error vs baseline
- About the sameError ratio 1.00; 1.00 is a tie.
- Tests won
- 5 / 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
- 81%Observed outcomes inside the band across all stored test windows.
- Band coverage uses all stored test windows, including model-selection windows when present; it does not determine the confidence label.
- Evaluated 2026-11-04 against the cached history through 2026-10-01.
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.
Model comparison
4 of 4 models evaluatedModels are selected on older tests and evaluated on separate recent tests. All four classes completed their backtests.
Models tested
AutoETS scored lowest on the 6 older tests (1.00) and was chosen. The 6 recent tests played no part in the choice and give its grade (1.00). 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: Statistical, Foundation model, Neural network, Machine learning.
| Model | Class / library | Older tests | Recent tests | Role |
|---|---|---|---|---|
| Naive forecast (last value held) | Benchmark · CPU | 1.00 | 1.00 | Benchmark |
| AutoETS (statistical) | Statistical · StatsForecast · CPU | 1.00 | 1.00 | Serving |
| Timestral (foundation model) | Foundation model · Timestral · GPU | 1.01 | 0.98 | Tested |
| N-HiTS (neural network) | Neural network · NeuralForecast · CPU | 1.28 | 1.26 | Tested |
| CatBoost (machine learning) | Machine learning · MLForecast · CPU | 1.30 | 1.14 | Tested |
Reading
Natural Gas was 2.61 USD (exchange quote) in October 2026: -10.0% from September 2026 and -27.6% from October 2025. It is above 29% of the 119 earlier readings since November 2016.
The AutoETS forecast puts it at 2.66 USD (exchange quote) in October 2027, +2.2% from the latest, with an 80% band from 1.09 USD (exchange quote) to 4.24 USD (exchange quote). It is on par with the naive forecast: its past errors were 1.00 times as large, and it was more accurate in 5 of 6 test years. The 80% band held 81% of outcomes. The naive forecast keeps the latest value for every future period (a random walk).
Source
Data: OANDA feed via TradingView.
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