SOXL 1-day forecast by Gemini 1.5 Pro
Gemini 1.5 Pro's 1-day forecast for SOXL, made 2026-09-25: expected range $146.00 to $156.00 at 60% confidence. Settled at $136.05: direction called correctly, score 71.8.
| Asset | SOXL |
|---|---|
| Model | Gemini 1.5 Pro |
| Recorded by | Forecastnest |
| Forecast made | |
| Horizon | 1-day (Equity / ETF 1D: the stored target below is authoritative; it may be a session close or an intraday instant.) |
| Window closes | |
| Price when asked | $151.05 |
| Price the model reported | $151.44 |
| Expected range | $146.00 to $156.00 |
| Confidence | 60% |
| Prompt style | No data |
| Status | Settled |
| Actual close | $136.05 |
| Traded range in the window | $135.21 to $153.90 |
| Result | Direction called correctly |
| Score | 71.8 of 100 |
The model's reasoning
(1) Live pricing sourced via Google Search from NASDAQ and financial data platforms shows SOXL trading near $151.44 as of 15:24 UTC on September 25, 2026, climbing over 3% on the session.
(2) The current market regime for semiconductors remains in a structurally bullish but volatile consolidation phase. Mega-cap tech and AI hardware names continue to attract bids, supporting intraday momentum in this leveraged ETF.
(3) The 1-day price range of $146.00-$156.00 accounts for the outsized volatility of a 3x leveraged product. Support is well-defined near the recent $146 floor, while sustained momentum could test overhead supply and resistance around $156.
(4) There are no major scheduled economic data prints or sector earnings reports in the immediate 24-hour window. Price action will primarily be governed by broader tech index flows and standard Friday afternoon institutional positioning.
(5) The strongest counter-argument to this mild bullish view is late-day profit-taking ahead of the weekend. Because of the 3x multiplier, a minor fade in the underlying semiconductor index could quickly trigger a steep drop below the $146 support, invalidating the upside target.
(6) Confidence is set at 60% because single-day forecasting on a highly leveraged ETF leading into a weekend close is particularly vulnerable to passive algorithmic rebalancing and random market noise rather than fundamental shifts.
Other models on the same question
| Model | Expected range | Confidence | Result | Score |
|---|---|---|---|---|
| GPT-5.6 Sol | $136.00 to $158.00 | 56% | Direction called incorrectly | 9.8 |
| Perplexity | $137.00 to $154.00 | 46% | Direction called incorrectly | 2.7 |
| Claude Opus 5.5 | $138.00 to $164.50 | 50% | Direction called incorrectly | 10.2 |
| Muse Spark 1.1 | $141.00 to $160.50 | 62% | Direction called correctly | 77.6 |
| DeepSeek | $99.00 to $118.00 | 55% | Direction called incorrectly | 0.1 |
| Grok 4.5 | $138.00 to $165.00 | 42% | Direction called incorrectly | 11.1 |
How this forecast is measured
Sends only the baseline price and the output format; your AI researches the asset itself. Best with a model that can search the web — it can reach news, filings and positioning we do not carry. Costs no market data, at generation or at settlement — you record the closing price yourself when the window shuts. The monthly allowance is what a membership buys, not a data bill.
Every model answering the same prompt is measured from the same starting price over the same window, and scored on its range and its call. How scoring works · All shared research.
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