(English Version Below)

以無限資金為前提的馬丁格爾或對沖等手法一律不採用。最大停損設為23 pips，並基於人工智能學習設計與最佳化。 

由頂尖AI研究人員提供、在頂級AI國際會議（ICML KDD EMNLP ECCV等）發表大量論文

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本系統透過結合多個AI模型的集成學習，分析市場並自動進行交易，為下一代外匯交易系統。

在開發時，使用過去數百萬筆外匯市場數據作為學習資料，分析價格變動、趨勢、波動性、市場結構變化等。並非依賴單一的交易規則或技術指標，而是讓多個AI模型從各自角度評估市場，並將結果整合以做出最終交易判斷。

如上圖所示，本系統以以下流程執行交易。

① 大規模市場資料分析

DeepAgent FX會學習數百萬筆市場資料，解析多樣的行情環境。

不僅是價格變動，還包括

• 價格結構
• 趨勢強度 波動性
• 市場體制
• 動量
• 流動性

AI綜合理解市場整體特徵。這些資訊將成為日後所有買賣判斷的基礎。

② 趨勢策略引擎

在AI作出判斷之前，內部研發的趨勢策略引擎會產生交易候選。

持續分析市場情況，

• 趨勢延續
• 回檔/回測
• 突破
• 市場結構
• 進場時機
• 風險條件

等方面進行評估。

滿足特定條件的候選才會進入AI評估。

③ AI集成評估

DeepAgent FX採用多個機器學習模型的集成學習，而非單一AI模組。

各AI以不同角度評估市場，

• 勝率
• 風險回報
• 市場信心
• 與行情環境的適配性
• 過去模式的相似性

等指標。

最終的買賣決策由多個AI的共識（合意）決定。

④ AI信任度評分

所有交易候選皆附有AI信任度分數。只有達到一定信任度的信號才被採用，其餘自動排除。

以減少不必要的交易，專注於更高期望值的交易。

⑤ 動態部位最佳化

DeepAgent FX不以固定手數運作。

根據AI信任度與市場情況，

• 手數
• 部位比重
• 風險配置
• 利潤管理

實時進行最佳化。

在高信任度情況下積極、在較低信任度時較保守地交易。

⑥ 即時交易執行

經過所有判斷層級的信號，才在MT5上自動執行。

交易開始後，

• 下單管理
• 停損管理
• 追蹤管理
• 部位監控

等持續執行，因應市場變化。

持續學習循環

研究版的DeepAgent FX不同於固定參數的EA，會持續將實際市場資料與交易結果回饋進訓練管線。

在適應市場環境變化的同時，持續改進AI模型，追求長期表現提升。

※銷售版採固定訓練模型。

多個AI模型共同考慮，做出單一判斷，以大量市場數據學習而成的交易代理。

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This EA uses no Martingale, no hedging, and has a maximum stop loss of only 23 pips. The strategy is fully AI-trained. 

Developed by  Top AI Researchers ｜Author of Multiple Papers at Leading AI Conferences　(ICML • KDD • EMNLP • ECCV etc.)

🎉Special Launch Offer!
     First 10 Customers: JPY 40,000🔥Starting from the 11th Customer: JPY 80,000

DeepAgent FX is a next-generation automated trading system that leverages an ensemble of AI models to analyze financial markets and execute trades autonomously.

The system has been trained on millions of historical market observations, capturing patterns in price movements, trends, volatility, and changing market conditions. Rather than relying on a single trading rule or a handful of technical indicators, multiple AI models independently evaluate market signals and collectively contribute to the final trading decision.

① Large-Scale Market Data Analysis

DeepAgent FX is trained on millions of historical market records covering different market environments.

Rather than simply learning whether the market goes up or down, the system first extracts higher-level market characteristics including:

• Price Structure
• Trend Strength
• Volatility Regime
• Market Momentum
• Liquidity Conditions

These market representations provide the foundation for every trading decision.

② Trend Policy Engine

Before AI begins making predictions, a proprietary Trend Policy Engine generates candidate trading opportunities.

Instead of opening trades randomly, the engine continuously evaluates:

• Trend Continuation
• Pullback Quality
• Breakout Confirmation
• Market Structure
• Entry Timing
• Trading Constraints

Only qualified trading candidates proceed to the AI evaluation stage.

③ AI Ensemble Filtering

Rather than relying on a single AI model, DeepAgent FX combines multiple machine learning models through an ensemble architecture.

Each model evaluates the same opportunity from a different perspective, including:

• Win Probability
• Market Confidence
• Expected Reward
• Risk Assessment
• Historical Pattern Similarity

The final decision is produced through an ensemble consensus process, reducing overfitting while improving robustness.

④ Trade Confidence Scoring

Every candidate trade receives an AI confidence score.

Only opportunities that exceed predefined confidence requirements are allowed to enter the market.

This additional filtering layer significantly reduces unnecessary trades and focuses execution on higher-quality opportunities.

⑤ Dynamic Position Sizing

DeepAgent FX dynamically adjusts trading exposure according to market conditions.

Instead of using a fixed lot size, the system continuously optimizes:

• Position Size
• Maximum Exposure
• Risk Allocation
• Trade Management

Higher-confidence opportunities may receive larger allocations, while uncertain conditions are traded more conservatively.

⑥ Live Trading Execution

Once all decision layers are satisfied, DeepAgent FX automatically executes trades on MT5.

During live execution, multiple risk management modules continue monitoring:

• Order Execution
• Stop-Loss Management
• Trailing Protection
• Position Monitoring

The objective is not only to identify profitable opportunities but also to preserve capital under changing market conditions.

Continuous Learning Loop

Unlike traditional Expert Advisors with permanently fixed parameters, the research version of DeepAgent FX continuously incorporates newly observed market data into the training pipeline.

Trading performance, changing market dynamics, and new price behaviors are periodically fed back into the model development process, enabling the AI to evolve alongside the market.

(The marketplace version uses a fixed trained model, while the internal research version is periodically updated.)

At Last, our DeepAgent FX was built on multiple AI models with one trading decisiontrained on Large-Scale Market Data.