Inside the Engine: How Our AI Analyzes Markets

Many "AI" trading bots are just simple if-then scripts in disguise. TradingMaster AI is different. It uses a Deep Learning Neural Network trained on 7 years of historical data.

The 3-Layer Architecture

Layer 1: Data Ingestion (The Senses)

The engine consumes 50+ data points per second for every pair:

• Price Action: Open, High, Low, Close.
• Order Book: Bid/Ask depth.
• Alternative Data: Sentiment, Correlation matrices.

Layer 2: Feature Extraction (The Brain)

Raw data is useless without context. The AI converts noise into "Features":

• "Is Volume anomalous?"
• "Is volatility contracting (Bollinger Squeeze)?"
• "Is there an On-Chain Divergence?"

Layer 3: Probability Weighting (The Judgement)

Unlike a human who thinks in absolutes ("Buy now!"), the AI thinks in probabilities.

• Output: "78.4% chance of price incrase >1% in the next 4 hours."

Continuous Learning

Every night, the model "retrains" itself on the day's data. If it made a mistake, it adjusts its weights to avoid that mistake tomorrow. This is why our performance improves over time.