Why Python for Algo Trading?
- Beginner-friendly syntax and fast learning curve
- Powerful libraries: pandas, numpy, matplotlib, zipline
- Direct connectivity to all major Indian broker APIs
- Large community and free resources
- AI and ML integration for advanced strategies
Popular Strategy Types Built in Python
Moving Average Crossover
One of the simplest strategies — buy when the short MA crosses above the long MA. A great starting point for beginners.
RSI Mean Reversion
Buy when RSI falls below 30, sell when it exceeds 70. Simple and effective in range-bound markets.
Breakout Strategies
Trade the breakout above resistance or below support with volume confirmation.
Essential Python Libraries
- pandas — for data manipulation and time series
- numpy — numerical calculations
- matplotlib — charting and visualisation
- requests or broker SDK — for API connectivity
- backtrader or zipline — for backtesting
Learning Path
- Python basics (variables, functions, loops, OOP)
- Working with OHLCV data using pandas
- Coding your first MA crossover strategy
- Backtesting it with BackDesk or backtrader
- Connecting to a broker API
- Deploying and monitoring live