Standard Deviation – For N=21, 42, …, 231, 252 days, we compute the standard deviation of the adjusted close prices.

Slopes – For N=21, 42, …, 231, 252 days, we compute slopes for data as described below. After the data has been transformed, we compute a linear fit and then the slope, where the x value is the array 1, 2, 3, …, N.

- Raw adjusted close prices
- Zscore of adjusted close prices: (price – mean)/standard deviation
- Maximum Minimum of adjusted close prices: (price – min price)/(max price – min price). We
*multiply the results by 100*to make the data, as presented in a CSV file, easier to read. - Fractional Return of adjusted close prices: We transform the time series of adjusted close prices by computing (price_i – price_i-1)/price_i-1. We
*multiply the results by 100000*to make the data, as presented in a CSV file, easier to read.

Standard deviation and slopes are computed each market day and presented as CSV files that are included in the file named Analysis YYYY-MM-DD.zip. Note that the first instance of this data will be available tonight 2023-07-18.

All quantitative and machine learning analysis files are available for download from our Proton Drive. See Quantitative And Machine Learning Asset Analysis for explanations of algorithms, methods, and results.

All data presented here is available for free with no restrictions. If you find such information useful, we ask that you provide value in return via the Value 4 Value links on the homepage. We would also appreciate you spreading the word about our work.