Comprehensive Stock Trading Algorithm Development

I need an end-to-end algorithm that trades a single share-market instrument entirely on technical chart analysis. The core logic must follow a technical trading approach, relying on candlestick patterns, moving averages, RSI, and manually-defined trend lines to decide entries, exits, and position sizing. Scope The build starts from raw market data ingestion, moves through signal generation, and finishes with live order execution and performance reporting. All elements—data cleaning, feature engineering, back-testing, walk-forward validation, risk controls, and real-time monitoring—should sit inside one coherent codebase so I can flip from historical tests to live trading with minimal re-configuration. Implementation Notes • Python is my preferred language; common libraries such as pandas, NumPy, TA-Lib, and matplotlib are ideal. • Please structure the project so that broker connections (for example Interactive Brokers, Zerodha Kite, or a similar API) can be swapped out without touching strategy code. • Configuration files or a simple UI for parameter tweaks (MA lengths, RSI thresholds, candlestick filters, position limits) will keep things flexible. Deliverables 1. Well-commented source code with modular architecture. 2. Back-test report covering at least five years of data, including equity curve, drawdown, and key ratios. 3. Documentation explaining setup, parameter tuning, and how to switch from paper to live trading. 4. A short video walk-through (screen-recorded) showing the algorithm running in both back-test and simulated live modes. Acceptance Criteria • Trade signals must match the specified candlestick, moving average, RSI, and trend-line logic. • Historical tests replicate when rerun on the same dataset. • Live mode places, modifies, and closes orders automatically without manual intervention. Once these items are met, the project is complete and ready for hand-off.