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Unified Capital Intelligence

Institutional-Grade
Algorithmic Trading
Intelligence

A complete AI-powered trading platform — walk-forward validated strategies, HMM Markov regime detection, and multi-lane execution architecture built for precision.

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3.33
Peak Profit Factor
Practice Account
50+
Intel Sources
4
Strategy Lanes
MC
Monte Carlo Validated
Platform Overview

What is Unified Capital Intelligence?

UCI is a fully automated forex trading intelligence system combining machine learning regime detection, structure-based strategies, and a robust risk governor — every component walk-forward tested and Monte Carlo stress-validated before deployment.

🧠
AI-Powered Regime Detection
Hidden Markov Model trained on rolling return distributions identifies Bull, Bear, and Sideways regimes in real time. Strategy activation adapts automatically as conditions shift — no manual intervention required.
  • 20-day rolling return regime labelling
  • Transition matrix forecasting
  • Stationary distribution probability
📊
Walk-Forward Validated Strategies
Every strategy passes out-of-sample walk-forward testing before approval. Results are stress-tested with Monte Carlo simulation to confirm robustness beyond in-sample curve fitting. Only proven OOS profit factors get activated.
  • 70/30 IS/OOS split methodology
  • 1000× Monte Carlo simulation
  • PF ≥ 1.3 and MC ≥ 90% required
⚡
Multi-Lane Architecture
Four independent execution lanes — Ray (regime-driven), Native (CHoCH structure), Hermes (news/sentiment), and Neo (experimental) — each managed by a central Governor enforcing risk limits across all lanes simultaneously.
  • Centralised Governor risk system
  • Per-trade NAV fraction limits
  • Cross-lane position management
Core Technology

The Stack Behind UCI

Every layer — from data ingestion through signal generation to trade execution — built with institutional rigour and full observability.

Regime Engine
HMM Markov Model
hmmlearn-powered Hidden Markov Model with 20-day rolling return regime labels. Transition matrix forecasting and stationary distribution solving.
Entry Strategy
CHoCH Structure
Change of Character (CHoCH) market structure detection identifies genuine trend shifts. v3 (primary) and v2 (legacy) provide complementary signal coverage.
Intelligence Layer
Knowledge Library
50+ curated intelligence sources covering central bank communications, economic releases, sentiment data, and inter-market correlations.
Validation
Monte Carlo Stress Test
Thousands of randomised trade-sequence simulations confirm strategy robustness. Only strategies clearing the MC pass threshold are promoted.
Execution
Multi-Broker Support
Built on OANDA's REST API with an abstraction layer for multi-broker routing. Architecture supports plug-in broker adapters for future connectivity.
Risk Management
Governor System
Centralised Governor enforces maximum risk-per-trade, daily loss limits, maximum concurrent positions, and margin bounds across all strategy lanes.
Platform
UCI Web Dashboard
Bloomberg-style real-time monitoring dashboard. Live trade table, regime cards, backtest results, system health, and risk controls in one secured interface.
Data Pipeline
Walk-Forward Engine
Automated walk-forward backtesting with configurable IS/OOS windows. Results stored to the Knowledge Library for ongoing strategy evolution tracking.
Infrastructure
Always-On Service
Systemd-managed UCI service with NGINX reverse proxy, JWT authentication, and health monitoring. Designed for 24/5 forex market availability.
Observability
Real-Time Telemetry
CPU, RAM, disk, uptime, service health, and error counts surfaced live. API endpoints provide structured JSON for all system metrics and trade state.
Backtest Results

Practice Account Results

Practice Account Only. All results shown are from a practice (demo) account using OANDA's simulated execution. Out-of-sample (OOS) testing uses data the strategy has never seen. Past performance is not indicative of future results. These figures do not represent live trading performance and should not be used to make financial decisions.
PairStrategyOOS Profit Factor OOS Win RateMonte Carlo %AccountStatus
EUR/JPY CHoCH v3 3.3362.5%94.2% Practice Approved
AUD/NZD CHoCH v3 3.3358.3%91.7% Practice Approved
EUR/JPY CHoCH v2 2.6355.0%87.3% Practice Approved

OOS = Out-of-Sample. Profit Factor = Gross Profit ÷ Gross Loss. Win Rate = winning trades / total trades. Monte Carlo % = percentage of simulations maintaining positive expectancy. All tests conducted under practice account conditions with simulated fills.

Development Roadmap

Where UCI Is Headed

A structured multi-phase build from foundational research through institutional-grade live deployment.

Phase 1–10Complete
Foundation, Research & Strategy Validation
Broker integration (OANDA), data pipeline, HMM Markov regime engine, CHoCH strategy development, walk-forward backtesting framework, Monte Carlo validation, Knowledge Library, Governor risk system, multi-lane architecture, and practice account deployment.
Phase 11In Progress
Web Platform — UCI Dashboard
Full-stack web platform with Bloomberg-style real-time dashboard, JWT-secured API, live trade monitoring, system health telemetry, and public marketing presence. PWA-capable for mobile access.
Phase 12Planned
Live Trading Transition
Gradual transition from practice to live account. Micro-lot initial sizing, enhanced Governor constraints for live conditions, and enhanced execution quality monitoring.
Phase 13Planned
Multi-Broker Expansion
Broker-agnostic execution layer supporting multiple providers. Redundancy, best-execution routing, and cross-broker position netting capabilities.
Phase 14+Future
Strategy Expansion & Automation Deepening
Additional asset classes, automated strategy discovery via ML, enhanced sentiment integration, and portfolio-level optimisation across uncorrelated strategy combinations.
Early Access

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