SpencerOfwiti/StockML

Implementation of various machine learning algorithms in the prediction of Kenya's stock market performance. # Stock ML Implementation of stock market price prediction of various Kenyan companies' shares including Safaricom e.t.c. It utilizes various Machine Learning algorithms such as Long Short Term Memory(LSTM), Prophet and Auto-Regressive Intergrated Moving Average(ARIMA). It bases it's analysis on historical trading data dating back more than five years. ## Table of contents * Motivation * Build Status * Built With * Features * Code Example * Prerequisites * Installation * Tests * Deployment * Contributions * Bug / Feature Request * Authors * License * Acknowledgements * Reports ## Motivation This project was born out of the need to make financial literacy and investment options available for the common citizen. Over the years the number of individuals investing in the Kenyan Securities Market has reduced. More and more of the trading is being done by investment companies and wealthy investors. This provides a platform to lower the barriers to entry for everyone keen on investing in the securities market. It provides daily predictions on the stock price for the next day and an overview of what to expect in the coming week. ## Build Status ## Built With * Python 3.6 - The programming language used. * Pytest - The testing framework used. * Travis CI - CI-CD tool used. ## Features - Aggregate daily stock closing price. - Exploration and cleaning of companies' stock prices data. - Application of machine learning algorithms in stock price prediction. - Visualization of stock price predictions. ## Code Example ```python def check_null_values(data): """ check if processed data has no null variables :param data: :return: """ return data.isnull().sum().sum() print(check_null_values(data)) ``` ## Prerequisites What things you need to install the software and how to install them * **python 3** Linux: ``` sudo apt-get install python3.6 ``` Windows: Download from python.org Mac OS: ``` brew install python3 ``` * **pip** Linux and Mac OS: ``` pip install …