Optimize Nifty Options Trading Bot

My intraday bot has been paper-trading Nifty options successfully, but before I let it handle real money I need its decision logic sharpened. I already have the full source code; what I’m looking for is a developer who can study the existing entry-exit rules and make them statistically tighter so that every live signal is based on sound, test-backed probabilities.

Key focus
• Improve the rule set: refine indicators, filters or pattern-recognition modules so the bot avoids low-quality setups.
• Embed a hard stop-loss on every position so risk is capped automatically.
• Keep the current framework intact—no need to change the language or architecture unless that directly boosts accuracy or execution speed.

Deliverables
1. Revised code with the enhanced trading logic and per-trade stop-loss parameter.
2. Back-test report showing performance over at least the past six months of Nifty options data, contrasted with the current version.
3. A brief hand-off note explaining new parameters so I can tweak them later.

I will provide the repository, past trade logs and my metric targets the moment we start. If your improvements beat the benchmark on win-rate and max drawdown, we are good to go for live deployment.