GFX Tech
AI-Powered Intelligent
Copy Trading Infrastructure
GFX-LLM World-Class Financial Decision Large Language Model + AI-MAM Intelligent Copy Trading System
What We Build
Two AI Engines Form Complete Decision-Execution Loop
GFX-LLM | World-Class Decision Large Model
Finance is not "language prediction", but constrained decision-making under state space. GFX-LLM models markets as non-stationary, high-noise, strongly-constrained dynamic decision systems (MDP / POMDP), outputting not opinions, but executable, risk-controllable strategy structures (Policy under Constraints).
State
Microstructure, volatility, liquidity, order flow, macro events, risk exposure
Action
Direction, position, leverage, order type, stop-loss/take-profit, downgrade
Constraint
Drawdown, margin, slippage, impact cost, correlation, tail risk
Objective
Long-term Risk-Adjusted Return
Three-Layer Model Architecture
Representation Layer | Market Representation
Compress raw market data into learnable structures
Reasoning Layer | Structured Reasoning
Causal inference and uncertainty quantification
Decision Layer | Decision Core
Output auditable strategy objects
XYZ Factor Stack (Composable Models)
Trend / Regime
Trend strength, structural breaks, switching probability
Order Flow / Liquidity
Fill probability, impact cost, short-term drift
Events / Tail Risk
Jump diffusion, extreme risk, black swan threshold
Fusion Engine
Training & Evaluation (Production-Grade)
Training
Offline RL / Imitation Learning + Distribution Drift Detection + Extreme Market Curriculum
Evaluation Dimensions
• Risk: Maximum drawdown, tail loss
• Execution: Slippage, fill rate, impact cost
• Robustness: Performance across market regimes, anomaly recovery time
Explainable & Auditable
AI-MAM | Intelligent Copy Trading Execution System
Copy Trading failures stem not from strategies, but from risk transmission and execution deviation. AI-MAM uses engineering systems to ensure replication consistency, risk tiering, and execution quality control.
Five-Layer Execution Pipeline
Signal & Intent
Receive GFX-LLM strategy objects
Risk Orchestrator
User risk profiles, budget allocation, circuit breakers
Allocation Engine
Asset allocation by capital/risk, netting positions
Execution Engine
SOR, multi-algorithm execution, slippage & latency control
Post-Trade & Audit
Trade-to-trade monitoring, PnL decomposition, audit logs
Replication Consistency Metrics (Engineered)
ΔP
Price Deviation
ΔT
Time Latency
Fill Ratio
Fill Rate
Cost Overrun
Cost Over Budget
Consistency Score
Auto downgrade/pause basis
Risk Tiers (Same Strategy, Multiple Risk Levels)
Conservative
Conservative
Low leverage, strong stop-loss
Balanced
Balanced
Standard risk budget
Aggressive
Aggressive
Higher risk, but stricter tail protection
Each tier has independent risk limits, execution strategies, and circuit breakers
Stability Engineering
Multi-region Active-Active disaster recovery
Replayable execution pipeline
Anti-replay order protection
Backpressure & rate limiting
Quantifiable SLA / SLO
Our Principles
Mission | Why We Exist
Transform institutional-grade financial AI decision-making and execution infrastructure into accessible intelligent copy trading capabilities for the public. Enable users to participate in markets through rational, controllable, and systematic approaches rather than relying on emotions and experience.
Vision | Our Vision
Serve 1,000,000 household users over the next decade, building low-drawdown, stable, and sustainable participatory experiences through AI-MAM. We don't chase short-term narratives; we build financial infrastructure for long-term use.
Values | Core Values
- Engineering First: Production environment long-term operation priority
- Risk Before Return: Risk first, return second
- Explainable & Auditable: Logic explainable, results traceable
- Risk Profiling: Dynamically adjust based on user profiles
- Long-Term Infrastructure: Designed with a 10-year cycle
Execution Pipeline
Five-layer pipeline ensures replication consistency
Signal & Intent
Strategy object generation
Risk Orchestrator
Profiling/budget/circuit breaker
Allocation Engine
Allocation/netting
Execution Engine
Routing/slippage/latency
Post-Trade & Audit
Deviation monitoring/audit logs
Consistency Metrics
Past · Present · Future
From cognition to systems, from systems to globalized infrastructure
Cognition Before Product
GFX Tech originated from a clear judgment: financial markets are not prediction problems, but long-term operating systems with high noise, non-stationarity, and strong constraints.
Models Deployed as Systems
GFX Tech has completed the critical leap from models to systems, providing subscription-based AI decision-making and execution infrastructure.
Long-Termism × Globalization × Strong Compliance
Become globalized AI financial infrastructure through pure technology, pure subscription, and strong compliance model.
We build infrastructure, not promises.
We build infrastructure, not promises
Elite Engineering & Financial Systems Team
GFX Tech is an elite cross-disciplinary team spanning AI decision systems, distributed engineering, quantitative finance, and trading execution infrastructure,
with core capabilities covering the complete chain of models, systems, risk, and execution.
Dr. Marcus Anderson
Former Research Scientist
Google DeepMind
Expert in reinforcement learning and complex decision systems, responsible for modeling and convergence mechanism design of GFX-LLM decision core
David Thompson
Senior Engineer
Meta AI (LLaMA Program)
Participated in large-scale language model training architecture, inference optimization, and model compression, responsible for GFX-LLM low-latency inference structure
Dr. Natalie Brooks
Distributed Systems Engineer
OpenAI
Specializes in large-scale distributed training, fault tolerance mechanisms, and consistency control, ensuring AI systems have financial-grade long-term operational capability
Robert Williams
Former Quantitative Researcher
J.P. Morgan FX
Deep research in FX market microstructure, liquidity behavior, and order flow mechanisms, building GFX Order-Flow Model
Kevin Zhang
Senior HPC Engineer
NVIDIA
Expert in GPU parallel computing, low-latency systems, and numerical computation acceleration, responsible for real-time risk assessment and high-frequency computing underlying computing architecture
James Mitchell
Former Execution Systems Consultant
Citadel Securities
Expert in high-frequency trading execution, slippage control, and multi-liquidity source routing, responsible for trading execution engine and AI-MAM copy trading consistency control
Frequently Asked Questions
Clarifying Boundaries, Building Trust
No, we do not engage in proprietary trading or promise returns. We focus solely on the development and operation of AI-powered copy trading infrastructure.
We address common issues in copy trading such as risk distortion, execution deviation, and system instability for long-term operation.
To transform institutional-grade financial AI decision-making and execution infrastructure into accessible intelligent copy trading capabilities for the public. Enabling users to participate in markets through rational, controllable, and systematic approaches rather than relying on emotions and experience.
To serve 1,000,000 household users over the next decade, building low-drawdown, stable, and sustainable participatory experiences through AI-MAM. We don't chase short-term narratives; we build financial infrastructure for long-term use.
Based on historical data and risk model assessments, monthly performance typically ranges between 5%–15%. However, financial markets are uncertain, and past performance does not guarantee future results.
No, all funds remain in trading accounts under the user's own name, custodied by regulated brokers.
Through regulated broker custody, multi-broker distributed deployment, and system-level risk control mechanisms working together to ensure fund security.
The system monitors and controls through engineered consistency metrics including price deviation, execution latency, fill rate, and cost in real-time.
No, the system provides different risk tiers and corresponding execution and protection mechanisms based on each user's risk profile.
Yes, all decision-making and execution processes are traceable and auditable, with support for strategy version management and rollback.
Controllable risk, transparent explainability, and long-term stable operation of the system in real production environments.
We use engineered AI to build intelligent copy trading infrastructure that can operate long-term.
The system currently integrates with MetaTrader 5 (MT5) trading platform. All trades are executed in accounts under the user's own name, custodied by regulated brokers.