DTAITrading

The trading ideas will come mainly from a self-programmed AI engine, which is going to be continuously improved by an AI engineer and a senior quant analyst. The trading logic of the application is built on a "Multi-Layered Filter" architecture, designed to distill high-frequency market data into focused, high-convidence trade "suggestions." 1. The system is grounded in Wyckoff Market Analysis. Rather than following a single indicator, it categorizes the market into distinct stages (e.g., Accumulation, Markup, Distribution, and Capitulation). By identifying the current "regime," the system applies specific technical filters to identify high-quality "breaks" and "momentum" signals tailored to that specific market context. 2. To be considered a "valid" trade, a candidate must survive a three-stage sieve: Quant Score: A mandatory threshold (typically >0.15) ensuring the move has significant "robustness." Risk-Sizing Adjustment: The system automatically shrinks the trade commitment (sizing) during high-volatility phases (like "Distribution") to protect against "false" moves. Contextual Overlays: The system applies filters for Squeeze Fuel (short interest), Volume Ratio (liquidity), and Sentiment to differentiate between a "valid breakout" and a "exhausted" price move. 3. Trade duration is Dynamic and State-Aware. Instead of a fixed-time exit, the app utilizes a "Hold" logic that scales the duration (in bars) based on the Wyckoff stage and "Transition" status. For example, it may allocate a longer hold period (e.g., 25 bars) for a "Markup" play that occurs in a transitioner window, whereas a standard trade would have a shorter cap. 4. The system aggregates data from a suite of professional-grade providers.