This is based on the Fractal indicator. For this purpose I calculated the Fractals manually in python. The optimize number for fractals on a Daily (Globex) Chart is 4. I then ran a DBSCAN (Machine Learning cluster algo) to determine the relationship of Support and Resistance over the last two years data. I then plotted those scans.
UpFractals:

Count: There are 49 non-NaN UpFractal data points.
Mean: The average value of UpFractals is approximately 4443.53.
Standard Deviation: The spread of UpFractals around the mean is approximately 268.19.
Minimum: The smallest UpFractal value is 3980.25.
25th Percentile: 25% of the data points have an UpFractal value less than 4266.75.
Median (50th Percentile): The median value is 4382.25.
75th Percentile: 75% of the data points have an UpFractal value less than 4636.75.
Maximum: The highest UpFractal value is 4979.75.

DownFractals:

Count: There are 51 non-NaN DownFractal data points.
Mean: The average value of DownFractals is approximately 4201.51.
Standard Deviation: The spread of DownFractals around the mean is approximately 267.79.
Minimum: The smallest DownFractal value is 3662.25.
25th Percentile: 25% of the data points have a DownFractal value less than 4009.63.
Median (50th Percentile): The median value is 4205.25.
75th Percentile: 75% of the data points have a DownFractal value less than 4407.13.
Maximum: The highest DownFractal value is 4790.00.
Beyond Technical Analysis
neuralenergies

Exención de responsabilidad