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Stock Market Analysis using PCA: A Case Study with 10 Stocks

This case study explores stock market analysis using Principal Component Analysis (PCA) with 10 stocks including Boeing, NASDAQ, Dell, GE, GM, IBM, McDonald's, Microsoft, Coca Cola, and Pepsi. Analysis involves original data, log-transformed data, scree plots, loadings, detrended time series, normality tests, and relationships between principal components and data points.

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Stock Market Analysis using PCA: A Case Study with 10 Stocks

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  1. Principal Component Analysis A case study for 10 stock markets

  2. Variables analyzed (Yahoo finance) • Boeing (BA) • NASDAQ • Dell • General Electric (GE) • General Motors (GM) • IBM • McDonalds (MD) • Microsoft (MSFT) • Coca Cola • Pepsi Cola

  3. Original data (Yahoo finance)

  4. Logarithm base 10 of data

  5. Scree plot (values of PC’s variances)

  6. First two principal components

  7. Loadings

  8. First two principal components less the means, sign corrected

  9. Detrended time series (STL)

  10. Normal Probability Plots for Detrended Data BA NASDAQ MSFT PEPSI

  11. Scree plot (values of PC’s variances)

  12. Loadings

  13. Chi-square Normality test using original data (p=10)

  14. Chi-square Normality test (BA+NASDAQ)

  15. Normality test (BA+NASDAQ) NASDAQ Boeing

  16. Chi-square Normality test (NASDAQ+DELL)

  17. Normality test (NASDAQ+DELL) DELL NASDAQ

  18. Chi-square Normality test using PCs (p=10)

  19. Chi-square Normality test using PC1+PC2

  20. Normality test using PC1+PC2 PC1 PC2

  21. Normality test, using PC1 + PC2 Principal component 2 Principal component 1

  22. Chi-square Normality test using PC3 + …+ PC10

  23. Relationship between PC1 and data BOEING Principal component 1

  24. Relationship between PC1 and data NASDAQ Principal component 1

  25. Relationship between PC3 and data COCA Principal component 3

  26. Time series of statistical distance for PC1 and PC2 Time series of statistical distance for PC3, …, PC10

  27. First two PCs for 3000 initial data points PC2 PC1

  28. First two PCs for 3000 initial data points PC2 PC1

  29. First two PCs for data points 4990-5000 PC2 PC1

  30. First two PCs for data points 4000-4100 PC2 PC1

  31. First two PCs for data points 3300-3500 PC2 PC1

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