This project was designed as a proof of concept and training ground within technologies to analyze, and forecast its future using different machine learning models.

• Linear Regression
• Random Forrest
• Arima (not started)

I set out to answer a few questions:

• Are there certain industries, and stocks that have high correlation that is significant to the index?
• For this, I used QQQ as the Nasdaq-100 index
• Which individual ticker maintains a high correlation to the Nasdaq-100 index?
• Can I predict 2024 using different training sets?
• Who has better price control indicating stability?
• Can i obtain 70% forecast / prediction accuracy?

Tasks:

• Extract data from yFinance library
• Load data into local SQL Server for perm storage (offline use)
• Load data into Linear Regression Model
• Version 1.1.1 = 2010 - 2023 to predict 2024
• Version 1.1.2 = 2023 to predict 2024
• Report findings of market and models using:
• Tableau
• PowerBI

Assumed extent of available data:

• Date
• Open
• Close
• High
• Low
• Volume