Spearman's Rank Correlation:
Spearman's Rank Correlation is a non-parametrical method used for statistical analysis of the correlation.
When using the rank correlation ratio, the tightness of the correlation between the parameters is conventionally evaluated. The ratio values equal to 0.3 or lower are deemed to show weak correlation tightness, the values more than 0.4 but less than 0.7 show moderate
correlation tightness and the values equal to 0.7 or higher indicate high correlation tightness.
The power of the Spearman's Rank Correlation is a bit lower than the power of the correlation parametrical ratio. It is reasonable to use the rank correlation ratio in case there is a small amount of observation results. This method can be used not only for quantitative data but also when registered values are determined by descriptive features of different intensity. The description is taken from here.
This indicator is a type of an oscillator but it is more smooth unlike Stochastic, while not lagging at the reverse points.
The only external parameter affecting the calculation algorithm is rangeN setting the number of bars, for which we are looking for regularity. If rangeN = 14, we use the close prices sequence Close[i], Close[i+1], ... Close[i+rangeN-1] and create a sequence of ranks for
them, i.e. the place each close price is located at, in case this sequence is sorted. In this case we have one real chart compared with a steadily increasing one.
Author: Nikolay Kositsin
Would you mind to explain what is d ?
How to calculate it or rank it ?
default rank is the order;
if (eq) then rank is everage of all rank of eqs;