MY FINANCE: WEB APPLICATION WITH STOCK PRICE PREDICTION USING REGRESSION LEAST SQUARES ALGORITHM

Abstract

designed for managing personal finances. The application allows users to register and log in using email and password authentication. Once logged in, users have a dashboard displaying essential financial information such as monthly income, spending, balance, and net worth. The application's main feature is the "Pocket" page, where users can create different pockets, including options like Cash, Bank account, and e-wallet. Users can specify the pocket type, name, current balance, and description. Actions such as transferring funds between pockets, editing details, deleting pockets, and reviewing pocket transactions are available. The "Transaction" page enables users to add three types of transactions: income, spending, and transfers. Within the stocks section, a machine learning algorithm is incorporated to predict future stock prices. To predict stock prices, the algorithm collects historical data from the Yahoo Finance API, converts it to a structured panda's data frame-like format, and extracts the necessary features and target variables. By making predictions on new data, the algorithm provides users with insights into potential stock price fluctuations, indicating potential upsides or downsides. Least Squares Regression is a popular algorithm used for predicting numerical values based on input features. It aims to find the best-fitting line that minimizes the sum of the squared differences between the predicted values and the actual values in a given dataset. The web application is developed using the Laravel PHP framework, with a MySQL database and Apache server utilized for storage and hosting purposes. By combining personal finance management features with stock price prediction, the application offers users a powerful tool for making informed financial decisions