Adapt cTrader Bots, Kazan Programmer Needed
Budget: $15 – $25 USD
There is a suite of pre-configured Python bots that currently run on cTrader. I now want them fully aligned with my own trading system and expanded in two key areas:
• Introduce a robust trend-following strategy that fits the logic and data feeds I already use.
• Bolt on solid risk-management controls—hard stop-loss orders, dynamic position sizing, and trailing stops—so every position automatically respects my predefined exposure limits.
All code must remain within the cTrader Automate (cAlgo) environment while leveraging Python connectors where necessary. Clean, well-commented modules and a brief “how-to” document for deployment are required once the work is complete.
I’m based in Kazan and would strongly prefer a local, English-speaking developer so we can meet in person if any nuances need quick clarification. Remote collaboration is still fine for day-to-day commits (GitHub or Bitbucket), but proximity will speed up testing on my live account.
Acceptance criteria
– Trend-following logic triggers entries/exits exactly as specified in our first briefing session.
– Stop-loss, position-sizing, and trailing-stop rules activate reliably on both back-test and forward-test sessions.
– Code passes a one-week paper-trade run with no critical errors.
If you have previous cTrader bot experience and can drop by a local café to hash out details, let’s get started.
• Introduce a robust trend-following strategy that fits the logic and data feeds I already use.
• Bolt on solid risk-management controls—hard stop-loss orders, dynamic position sizing, and trailing stops—so every position automatically respects my predefined exposure limits.
All code must remain within the cTrader Automate (cAlgo) environment while leveraging Python connectors where necessary. Clean, well-commented modules and a brief “how-to” document for deployment are required once the work is complete.
I’m based in Kazan and would strongly prefer a local, English-speaking developer so we can meet in person if any nuances need quick clarification. Remote collaboration is still fine for day-to-day commits (GitHub or Bitbucket), but proximity will speed up testing on my live account.
Acceptance criteria
– Trend-following logic triggers entries/exits exactly as specified in our first briefing session.
– Stop-loss, position-sizing, and trailing-stop rules activate reliably on both back-test and forward-test sessions.
– Code passes a one-week paper-trade run with no critical errors.
If you have previous cTrader bot experience and can drop by a local café to hash out details, let’s get started.
Related categories:
Python
Financial Markets
AutoHotkey
Software Development
Risk Management
Backtesting