NETFLIX-Stock_Correlation

Stock Correlation

In this Notebook, I analyze the following five semiconductor stocks: HD, INTC, AMD, MU, NVDA, and TSM. Then, I choose the stock with the least correlation to JNJ in order to diversify a portfolio. The data was generated using the GOOGLEFINANCE historical market data script.

To learn more about diversification and how correlation in a portfolio helps to minimize risk, review this article on diversification.

Steps

1. I Imported the Pandas and Plotly Express libraries.

2. Read the CSV file into a DataFrame and set the date column as the index.

3. Used the pct_change function to calculate the daily returns.

4. Dropped any rows with missing data.

5. Created a correlation matrix.

6. Created a heatmap using the correlation matrix.

7. Used the unstack function to find the best stock pair for diversification.

8. Last, I explain which semiconductor stock would be the best candidate to add to the existing portfolio and why.