Stock Price Prediction and Trading Strategy using Machine Learning with Python

This project utilizes machine learning techniques in Python to predict stock prices and implement a basic trading strategy.

Chart Preview:

Final Result :

The final result of the Stock Price Prediction and Trading Strategy using Machine Learning with Python has been displayed below ,

Technical Report

The project has been published as an technical report in Open Science Framework, to which the link is provided below.

                    https://osf.io/zj4b3/?view_only=cb6705ac505e4f769e82b25ec0bf5b6c

Citation

For now, cite the Open Science Framework paper:

@misc{vasudevan2024stockprice,
      title={Stock Price Prediction and Trading Strategy using Machine Learning with Python}, 
      author={Vasudevan Swornampillai},
      year={2024},
      month={February},
      publisher={Open Science Framework},
      doi={DOI 10.17605/OSF.IO/ZJ4B3}
}

Key Features:

Data Preparation: Extracts relevant features from historical stock data.

Model Training: Trains a linear regression model to predict closing prices.

Model Evaluation: Evaluates the model's performance using mean squared error and R-squared score.

Model Saving: Saves the trained model for future use.

Trading Strategy: Implements a simple trading strategy based on the model's predictions.

Getting Started:

Install Dependencies: Install the required Python libraries listed in the requirements.txt file.

Prepare Data: Load your historical stock data into a Pandas DataFrame.

Train Model: Run the code provided in the model_training.py script to train the linear regression model.

Evaluate Model: Analyze the model's performance metrics to assess its effectiveness.

Implement Trading Strategy: Use the trained model to make predictions on new data and execute trades based on those predictions.

Prerequisites:

Python 3.x

Pandas library

scikit-learn library

joblib library

Disclaimer:

Trading stocks involves significant financial risks and is not suitable for all investors. This project provides a basic framework for stock price prediction and trading strategy implementation, but it does not guarantee profits. Use this information at your own discretion.

Installation:

1. Clone this repository to your local machine:

          git clone https://github.com/your-username/automated_stock_trading_ml_model.git
   

2. Install the required Python libraries:

          pip install -r requirements.txt
   

Usage:

1. Run the trading script:

          python automated_stock_trading_ml_model.py
   

2. The script will pull historical forex data for a particular stock, train the Linear Regression model, and start placing trades automatically based on the model's predictions.

Tech Stack:

Language - Python 3.10.12

License:

This project is licensed under the Apache License 2.0.

Share with the community

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Conclusion

In this project, we’ve utilized machine learning techniques in Python to predict stock prices and implement a basic trading strategy. The model, a beacon of performance, awaits those go into the beautiful world of Python.