Meta Sophie Agapova / 个人资料
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Hello, I’m Meta, a senior quantitative developer with over 12 years of experience in the fields of neural network design, algorithmic trading, and AI-driven market analysis.
My professional background includes work in machine learning model optimization, Deep Learning architecture development, and real-time data interpretation for financial systems.
Together with my small but highly specialized team of data scientists and quantitative analysts, we now focus on developing intelligent Expert Advisors (EAs) that merge artificial intelligence,
market logic, and adaptive learning systems into one coherent trading framework.
(Our Focus)
- Advanced Neural Network Integration (DeepSeek, GPT-based & custom LSTM architectures)
- Market Microstructure Analysis – liquidity flow, tick pattern recognition & order book modeling
- Adaptive Trading Logic – systems that learn from both profits and losses
- Big Data Pattern Evaluation – continuous feedback models for real-time optimization
- Cross-Platform Development (MT4, MT5, Python API integrations)
(Our Vision)
We strong believe that the future of trading automation lies in self-learning systems that evolve with every trade.
Our goal is to build Expert Advisors that don’t just follow static rules - they think, adapt, and improve over time, becoming more accurate and intelligent with every market phase.
Each EA we publish is individually trained, live-tested, and continuously improved based on real market conditions.
Transparency, precision, and innovation are at the heart of our work.
(Contact)
We’re always open to constructive discussions, feedback, and collaboration ideas.
If you have any questions about our systems or wish to test one of our projects, feel free to reach out anytime.
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META i9 – 量子自适应交易引擎 - 技术参考 META i9 是一个基于三层架构的全自动交易智能体(EA): Quantum-State Pattern Analysis (QSPA) 量子态模式分析 Neuro-Fractal Engine (NFE) 神经分形引擎 Self-Correcting Trade Memory (SCTM) 自校正交易记忆系统 购买 META i9,即可免费获得 META i7!(限时一周) 虽然 META i7 使用两个协同神经网络,但 META i9 更进一步: 其神经架构经过大幅扩展和优化,使其能够进行更深层次的模式识别,并每秒执行更多决策。 除了强化的神经网络系统外,META i9 还会实时建模市场分形、价格周期、流动性流向和隐藏市场力量,以生成高度精准的交易决策。 META i9 不仅仅是做预测——它以更高的认知层级解析市场结构,并根据市场的变化动态调整策略。 学习系统 SCTM 已被完全重构并技术优化。 它现在能够存储更大规模的数据集,使 EA 能捕捉微观市场结构并从中提取更细粒度的信息用于决策。 与
META i7 – 智能交易的进化 - 技术参考 META i7 是一款全自动智能交易顾问(Expert Advisor),基于两套强大且协同工作的神经网络。这两个网络在实时环境下运行, 负责生成、评估并持续优化交易决策。两个神经网络通过内部的 META 层(META Layer)进行处理与分析。 这是一个完全集成在 EA 内部的接口,能够整合两个模型的输出,分析并形成最终一致的交易决策。 EA 会从每一笔交易中主动学习--无论是盈利还是亏损--所有结果都会直接纳入其决策过程。 这种学习机制清晰可见,因为随着时间推移,交易风格显著改善,EA 对重复的市场行为反应也更加精准。 它会根据当前市场状况动态调整策略,并通过经验避免重复性的错误。 为什么在回测中看不到亏损: META i7 使用一种先进的、数据驱动的学习系统,基于广泛的 大数据分析 和历史 交易绩效数据集 。 每笔交易都会在实时中进行 量化分析 ,根据效率与上下文参数进行分类,并存储在内部的 经验数据库 中。 当在真实交易中出现盈利或亏损时,相应的决策模型会自动 重新校准 ,并被替换为 优化后的 行为模式 ,

