Many #tradingview strategies look strong in backtests — but fail quickly once they go live.
The reason usually isn’t the strategy idea itself.
Real deployment introduces challenges that backtests often miss:
• Slippage
• Exchange execution delays
• API reliability
• Position sizing errors
• Risk controls
• Live monitoring
A profitable backtest does not automatically mean a strategy is ready for real capital.
This is where many traders underestimate the true complexity of automation.
A more realistic process often looks like:
#tradingview / #pinescript strategy
→ strategy conversion
→ backtest
→ paper trading
→ small live deployment
→ full automation
The biggest gap in automated trading is often not strategy creation.
It’s execution.
We’ve been closely focused on this strategy-to-execution gap at #VegaXArchitect , especially around simplifying how traders move from TradingView strategies to live deployment.
How are others here validating their strategies before going live?