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man trading-systems

Trading Systems Lab

Name

trading-systems — Python · MQL5 · Automated systems

Synopsis

trading-systems --status=research --year=2026

Discipline, compiled.

PID
05
Status
R&D
Year
2026
Role
Design & development

no public link

fig.05 ea[1..9]
The nine MetaTrader 5 Expert Advisors as waveforms, plus KrakenBot Pro’s WebSocket v2 stream. Illustrative.

Description

My test bench for automated systems: KrakenBot Pro, a modular Python platform for Kraken, and a pack of nine MetaTrader 5 Expert Advisors built for research and backtesting.

Problem

A bot that works on a chart isn’t a system. A system needs API limits, reconnection, capital allocation across strategies, circuit breakers and an honest way to measure improvement.

How it works

  1. KrakenBot Pro: WebSocket v2 with reconnection and CRC32, token-bucket rate limiter per tier.

  2. A capital allocator that resolves conflicts between algorithms by scoring.

  3. A macro news engine with lightweight sentiment analysis, and backtesting on real OHLCV.

  4. Scheduled auto-optimisation with semantic versioning and a real-time React dashboard.

  5. MT5 pack v2: shared cycle state, portfolio cap, global trade lock and structural stops.

Architecture

Architecture · Trading Systems Lab
No. Layer Technology
L0 Core Python · asyncio · WebSocket v2
L1 Risk Capital allocator · circuit breakers
L2 Data OHLCV Kraken · backtesting
L3 Dashboard React · equity & P&L per algorithm
L4 MT5 MQL5 · 9 standalone EAs
L5 Deploy Docker Compose

Stack

  • Python
  • MQL5
  • React
  • Docker
  • WebSockets

Status

R&D

Research and backtesting. Built to validate ideas — not as a promise of returns.

Author

Written by Andrés Felipe Rodríguez Molina <[email protected]>

Design & development.

See also