https://github.com/gusgitmath/toptech_sp500_forecasting

Forecasting the stock market is difficult. I sought to observe the relationship between Apple's stock price and others in the S&P500. In doing this, I was able to conclude that stocks in the tech industry can help predict a trend in Apple's Percent change.
https://github.com/gusgitmath/toptech_sp500_forecasting

arima-forecasting linear-regression python3 vector-autoregression

Last synced: about 2 months ago
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Forecasting the stock market is difficult. I sought to observe the relationship between Apple's stock price and others in the S&P500. In doing this, I was able to conclude that stocks in the tech industry can help predict a trend in Apple's Percent change.

• Host: GitHub
• URL: https://github.com/gusgitmath/toptech_sp500_forecasting
• Owner: GusGitMath
• Created: 2024-08-29T15:24:10.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-08-29T15:27:14.000Z (4 months ago)
• Last Synced: 2024-08-30T16:51:34.719Z (4 months ago)
• Topics: arima-forecasting, linear-regression, python3, vector-autoregression
• Language: Jupyter Notebook
• Homepage:
• Size: 13 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Top Tech S&P 500 Forecasting

**Date:** November 2022

## Overview

Forecasting the stock market is inherently challenging. This project explores the relationship between Apple's stock price and other stocks in the S&P 500, particularly those in the technology sector. Through this analysis, I discovered that tech industry stocks can help predict trends in Apple's percentage price changes.

To model this relationship, I implemented a Vector Autoregression (VAR) model to forecast Apple's stock price for the next quarter. I then compared the performance of the VAR model against an ARIMA model to assess whether incorporating related stocks significantly improves forecasting accuracy.

## Data

Please note that the dataset provided here is a cleaned version, containing only the top ten tech stocks in the S&P 500 based on average trading volume. The original dataset, which includes a broader range of stocks, can be accessed through the following link:

[Original S&P 500 Stocks Dataset](https://www.kaggle.com/datasets/andrewmvd/sp-500-stocks?select=sp500_stocks.csv)

## Further Reading

A comprehensive analysis of the data and modeling process was documented in a twenty-five-page paper. If you are interested in reading the full analysis, please feel free to contact me.

**Math & Physics Fun with Gus!**