atari5o6o / 4cast

A MLP model to predict stock open prices using OHLC time series data

4cast

Overview

This project focuses on predicting stock price movements based on historical OHLC (Open-High-Low-Close) data. It utilizes an MLP (Multi-Layer Perceptron) Classifier and retrieves stock data from the Yahoo Finance API. The aim is to build a model that can forecast stock open price on a given day.

Features

• MLP Classifier: Utilizes an MLP Classifier to analyze historical OHLC data and predict stock price.

• Yahoo Finance API Integration: Gathers historical stock data, including OHLC prices and volume, from Yahoo Finance.

• Data Preprocessing: Cleans and prepares the data for model training, including feature engineering and normalization.

• Model Training: Trains the MLP Classifier on the preprocessed data to learn patterns and trends in stock price movements.

• Price Movement Forecasting: Generates predictions for stock price movements, such as whether the price will increase or decrease, and stock opem price on any given day.

Installation

1. Clone this repository:
   git coone https://github.com/Atari5o6o/4cast.git

2. Install the necessary python packages