I trade listed options and want to convert my discretionary trend-following style into a fully automated system. The goal is to read handpicked list of nse stocks on daily basis from CSV file. Place order to buy put option if first 5 min time frame candle is closed above bollinger bands base line. I want to add target as 15 % rise in put price and stop loss as 5 % below buying price , and run the strategy hands-free once it is live. Here is what I need from you: • Design clear, rule-based trend-following logic suitable for options (e.g., price action, moving averages, or momentum filters) and translate it into clean, well-commented code. • Source or connect to reliable historical options data, run walk-forward back-tests, and share detailed performance reports so I can see win-rate, drawdowns, and risk-adjusted returns before we go live. • Recommend the most practical execution environment. I have no firm preference yet, so feel free to propose MetaTrader, NinjaTrader, Interactive Brokers API, or a Python-based stack—whichever best handles options order routing and live monitoring. • Deploy the strategy into a paper-trading or demo environment, iron out any edge-case errors, and then guide me through a small-size live launch. • Provide concise documentation: core logic, parameter ranges, and an easy way for me to tweak inputs as market conditions evolve. Acceptance criteria: the code runs end-to-end without manual intervention, matches the documented back-test metrics within an agreed tolerance on fresh out-of-sample data, and submits live orders correctly through the chosen broker interface. If this fits your expertise, I’m ready to get started and iterate quickly toward a production-ready options trend-following algo.