Welcome to the Quantitative Trading with Bollinger Bands project! This algorithm leverages the power of Bollinger Bands and Moving averages to make informed decisions on buying and selling stocks.

This algorithm takes the concept of investing $1 and simulates its growth using the Bollinger Bands and Moving Averages strategy within a specified time frame for a given stock. By doing so, it provides an insightful glimpse into the potential returns this strategy could yield.

• Bollinger Bands: Benefit from the volatility indicators of Bollinger Bands.
• Moving Averages: Leverage the smoothing effects of Moving Averages.
• $1 Simulation: Visualize the growth of a $1 investment using the selected strategy.
• Customizable: Define the time frame and stock to tailor the simulation according to your preferences.

1. Clone: Clone this repository to your local machine.
2. Dependencies: Ensure you have the required dependencies installed.
3. Configuration: Set the desired time frame and stock for the simulation.
4. Run: Execute the algorithm and witness the simulated results.
5. Visualization: Gain insights into the strategy's potential success through visualizations.

Follow these steps to analyze the potential of Bollinger Bands and Moving Averages in your trading strategy.

bash

git clone https://github.com/bhishek29/Quant-trading-using-bollinger-Bands.git
cd Quant-trading-using-bollinger-Bands
# Set up dependencies (instructions in the documentation)
# Configure the time frame and stock in the settings file
python bollingerband_code.py

The algorithm not only provides numerical results but also visualizations that illustrate the simulated investment's growth potential.

While this algorithm showcases the power of Bollinger Bands and Moving Averages, remember that trading involves risks. Make informed decisions and exercise caution.