Grid trading is one of the few strategies that can profit during a market crash. I built a production-grade grid bot for Solana that trades on Jupiter DEX, and backtested it through a major downturn.
Results
- +11.7% return while SOL dropped 37%
- 100% win rate on completed grid cycles
- Realistic fee model including Jupiter, Orca, and Solana base fees
How Grid Trading Works
Grid trading places buy and sell orders at regular intervals around the current price:
- Buy low: Place buy orders below current price at each grid level
- Sell high: When price rises to the next grid level, sell
- Repeat: Each completed buy-sell cycle captures the spread
- Both directions: Works whether price goes up, down, or sideways
The key insight: you profit from volatility, not direction. A crashing market with lots of bouncing is actually ideal for grid trading.
Architecture
- Python async — non-blocking I/O for all network calls
- Pyth Network oracle — real-time on-chain pricing
- Jupiter V6 — optimal swap routing
- Dynamic Grid Reset (DGR) — automatically re-centers the grid when price moves too far
- Geometric spacing — wider grids at extreme prices, tighter at center
Built-in Backtester
The bot includes a 576-configuration sweep backtester:
- Test different grid sizes (5, 10, 20, 50 levels)
- Compare geometric vs arithmetic spacing
- Optimize rebalance thresholds
- Model realistic fees
Deployment
Comes with a guide for deploying on Oracle Cloud free tier — runs 24/7 at zero cost.
Get It
Full source code + backtester + deployment guide: devtools-site-delta.vercel.app/sol-grid-bot
Also check out my free Solana trading bot for Telegram: @solscanitbot — copy trading, sniping, DCA, and 40+ commands.
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