Upgrade Existing MT5 CatBoost EA

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Tempo di esecuzione 5 giorni
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Great work! A highly professional developer.
Feedback del dipendente
Very considerate and give you the best offer.

Specifiche

Upgrade Existing MT5 CatBoost Angle EA → Add Self-Learning Engine + Multi-Symbol + Prop-Firm Risk Layer (with 5-Year High-Quality Tick Backtests)

Project Overview

I already have a fully functional MT5 EA based on a CatBoost Angle Strategy (3-model ensemble).
This project is NOT about rewriting from scratch.

I need an experienced Senior MQL5 Developer to upgrade and extend the EA’s architecture by integrating:

A Self-Training Engine (pattern-score reinforcement learning)

Multi-Symbol independent learning (6 symbols)

A full Prop-Firm Challenge Risk-Control Layer

High-quality (99% modeling) tick-data backtests for 5+ years

Clean, modular OOP architecture

CSV-based model persistence per symbol

All CatBoost logic, angle features, and ensemble prediction must be kept exactly as they are.
Your job is to extend the EA with new modules and integrate them cleanly.

Scope of Work
1. Integrate the Self-Training Engine (Reinforcement-Style, MT5 Internal)

No Python needed.
All learning is inside MQL5.

Includes:

Feature builder
Feature binning → pattern hashing
Pattern table per symbol
Online score update (win/loss smoothing + decay)
MAE/MFE tracking
Model persistence (CSV)
Learning must run in parallel with CatBoost, not replacing it.
Final Decision = CatBoost Prediction + Pattern Score + Risk Layer

2. Multi-Symbol Learning Engine
Must support the following symbols independently:
XAUUSD
EURUSD
GBPUSD
USDJPY
US30
DAX40

Each symbol has its own:
Pattern table
MAE/MFE
Model CSV
Score history
Learning cycle
No cross-contamination allowed.

3. Prop-Firm Challenge Risk Layer
Must include:
Account-Level
Daily loss limit
Max drawdown limit
Equity guard
Account shutdown mode
Execution Level
Spread filter
Slippage filter
News/time blocked windows
Min seconds between trades (anti-HFT)
Max lots per symbol
Max total exposure
Strategy-Level
Swing mode (minimum holding time)
Risk Layer must wrap the trading engine:
CatBoost → Self-Training → RiskEngine.AllowNewTrade → Execution

4. High-Quality Tick-Data Backtests (Mandatory)
Modeling Quality: ≥ 99%

Symbols (≥ 5 years each):
XAUUSD
EURUSD
GBPUSD
USDJPY
US30
DAX40

Timeframes:
M15
H1

Files required per backtest:
HTML report
Equity curve PNG
Monthly returns table
Raw trade history CSV
Tick-data source info
Modeling quality screenshot

5. Architecture Requirements

Must follow a clean module design:
[ Prop-Firm Risk Layer ]
        ↓ allow/deny
[ CatBoost Predictions ]
        ↓
[ Self-Training Engine ]
  ↓ Feature Builder
  ↓ Pattern Hash
  ↓ Pattern Table (per symbol)
  ↓ MAE/MFE Tracking
  ↓ CSV Persistence


No monolithic OnTick code.
Clean classes required.

Deliverables

Updated EA (.mq5 + .ex5)

Self-Training Engine (integrated with existing CatBoost logic)

Multi-Symbol learning engine

Prop-firm-safe risk layer

Model persistence per symbol

All 12 required backtests (6 symbols × 2 TF × 5 years)

Documentation

Clean, extensible OOP architecture

Con risposta

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Informazioni sul progetto

Budget
550 - 700 USD
Scadenze
a 10 giorno(i)