The PCF-based methodology I use for divergences incorporates several neat ways of evaluating the "strength" of the divergence, once the formulae attached at the end of this writeup have been used to identify the slope direction.

This method has several strengths, in particular:

** Its basis is the simplest core form of the LinReg math (+/- slope-direction), keeping the PCF's relatively short and efficient

** It is relatively easy to adjust for different time windows and trading styles

** It can be adapted to Custom Indicator form and be visually backtested as such

** It is independent of the actual values or scaling of the indicator and of the symbol's price

** Its ranking approach is simple to understanding and work with

Here is the approach, in a nutshell:

1) Write a T/F PCF that identifies price-vs-indicator divergences using the info attached to the end of this document - this requires two formulae with appropriate glue-logic

2) Copy and modify the #1 PCF to model the same two LinReg lines, but change the "anchor" point from today to N days ago (typically N might be half of the LinReg window)

3) Copy and modify the #1 PCF to model the same two LinReg lines, but lengthen the "window width" to M days, anchored to today (typically M might be 2x the width of the #1 formulae)

4) Combine these formulae with boolean-algebra logic that:
a. identifies the divergence based on #1, giving it a "score" of +100 for bullish, -10 for bearish, or 0 otherwise
b. adds +10/0/-10 to the score based on a similar divergence eval from the #2 N-days-ago formulae
c. adds +1/0/-1 to the score based on a similar divergence eval from the #3 M-days-wide formulae

Plot the result as a Custom Indicator (for visual backtesting), or assign it to a WL tab column for daily use. The 100/10/1 weighted "score" components can be interchanged if you wish.

Answers can be +111, +110, +109, +101, +100, +99, +90, +10, +9, +1, 0 or their negative equivalents. By assigning this in a "decimal tiered" fashion, you not only get a nicely sortable result, but also can quickly see which of the criteria had "hits".

You could also create a fourth component, which would combine #2 and #3 to create a M-days wide, N-days ago check. I have found this to add little benefit, however - it has a lot of lag in it. If so, I suggest you give it a score-adder of +0.1/0/-0.1

OK ... for those of you who are pretty good at PCF's, this gives you the "heart" of the methodology. You should be able to take it from here. I'll be happy to help out if there are any questions.

Jim Dean