What makes GPTChart completely different from different buying and selling instruments isn’t simply the automation—it’s the reasoning behind each commerce concept.
Take this instance from the platform (see picture above). On the 1H timeframe, the AI recognized a Double Prime sample forming round a key resistance degree. However it didn’t cease there.
Right here’s what GPTChart truly does beneath the hood:
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Analyzes worth motion: Acknowledges patterns like engulfing candles, rejections, and market construction shifts.
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Reads indicators in context: Makes use of Bollinger Bands, EMA, and the Stochastic Oscillator to verify momentum adjustments.
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Defines structured commerce ranges: Entry, Cease Loss, Take Revenue, and Validation zones are calculated based mostly on assist/resistance, Fibonacci retracement ranges, and up to date highs/lows.
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Applies threat logic: Calculates the risk-reward ratio routinely and ensures setups observe logical commerce buildings—like a 2.5 R:R ratio on this case.
Every commerce concept features a full rationalization, not simply chart ranges. GPTChart doesn’t pull knowledge from random web sources. It’s educated utilizing market knowledge from APIs, mixed with curated buying and selling logic and methods—like break and retest, validation zones, and sample recognition.
The objective is to provide merchants an edge via structured confluence—not obscure alerts.
See it in motion: https://gptchart.ai
