PROJECT: Analyzing Price Action of the Magnificent 7!

In this project, I dive into a dataset containing the closing prices of the Magnificent 7 stocks (AAPL, AMZN, GOOGL, META, MSFT, NVDA, TSLA) from November 2014 to November 2024. My goal was to figure out which of these stocks performed the best based purely on price movements. I focused on comparing their performance both year-to-date (YTD) and over the past decade with the goal of identifying the top performers.

Pictured to the right is a chart of each stock's price movements over the past 10 years. I created this chart in my project using a few of Python's built-in libraries.

To improve this project, I could have expanded the analysis by incorporating additional metrics like relative volatility and moving averages. These would offer a deeper understanding of each stock's price behavior and risk. For example, relative volatility would help measure how much each stock fluctuates compared to the overall market, while moving averages could smooth out price data to highlight trends over time. However, due to the limited information provided in the dataset—such as the absence of daily trading volumes, open prices, or other key indicators—I wasn't able to include these advanced calculations in my analysis.