Aurum AI Quantum Core
- Experts
- Lin Sheng Wu
- Versione: 8.1
- Attivazioni: 5
Dear trader, I am Aurum AI Quantum Core™ - the AI expert for gold trading created by the Quantitative Team.
Dear trader, I am Aurum AI Quantum Core™ - the AI expert for gold trading created by the Quantitative Team.
Conquer the XAUUSD market with deep neural networks. By integrating the LSTM-Attention model prediction engine with the reinforcement learning execution system, and combining the breakthrough fusion of artificial intelligence and hedge fund strategies through DeepSeek API, a new era of gold trading is initiated.
Aurum AI Quantum Core - Quantum-driven gold algorithmic trading system
real-time signal：https://www.mql5.com/zh/signals/2350384?source=Site+Signals+My#!tab=history
- 🌟 Core revolutionary technology
Triple AI Prediction Matrix ：
- Deep Neural Network (DNN): 72-layer LSTM + Attention architecture, capable of processing 7-dimensional market features per hour.
- DeepSeek Financial Big Model: Real-time API for parsing Federal Reserve policies / Geopolitical events / Market sentiments
- Quantum Oscillation Indicator: Self-developed volatility compression algorithm, accurately detecting pre-breakout signals
High-frequency hedging engine
- Intelligent Hedging Matrix System
- Cross-cycle hedging strategy: Main position (hourly trend) + Hedging position (minute-level reversal) - a three-dimensional protection network
- Self-destructive hedging order: 5-hour automatic closing mechanism to prevent excessive hedging
Dynamic Algorithm Position Management System
- 5-dimensional risk control model
- Risk = f(Volatility, Trend Intensity, Time Period Coefficient, Account Health, Signal Confidence)
suggest：
- Support for currency： XAUUSD
- time horizon：H1
- Minimum deposit amount：1000 USD
- Account Type：ECN, Raw or Razor, the spread is very low.
- pry - at least 1：100，suggest 1：500
- account type：hedging，neural network
- Use VPS to make EA work 24/7 (highly recommended)
After purchase, please contact the author. To activate the model prediction, the author needs to provide the model file.
The following backtesting results indicate the effectiveness of the model's predictive capabilities.
Note: To conduct model backtesting and testing, you need to contact the author to obtain the model files.
The upper management of platform EA does not allow the use of DLLs or model file collections. External files can cause differences in the backtesting of the products that are put on the market. You can refer to the product demonstration video (the purchaser needs to contact the author).
