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AndrewRWA/Nasdaq

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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