Priority List

The following is a priority list or a list of objectives listed in order of importance. The list is not a complete list and will be updated as needed.

1. Creation of Zig Zag Logic in R. Sample Zig Zag Code
2. Create charts in R using QuantMod or similar.
3. Draw the programmed Zig Zag logic on the R charts so as to visually confirm correctness of code. The resultant output should look similar to what is found in this post. 

This is where the priority may split or be divided and two paths taken and programmed separately. The following studies are all independent of each other with the exception that they are based on the Zig Zag swing as the basis to find and log the needed data or conditions. When the need comes, these studies may be merged in the future to give better statistics and analytics of the said patterns. 

1. Calculate all of the Zig Zag legs and record their values based on the conditions found in this post.
2. Perform pattern recognition and recording of found patterns at the end of the Zig Zag legs. This link gives a brief description of pattern recognition but does the recognition in an unfiltered manner. The idea of this pattern recognition is to look at the pattern of "XX" candles prior to the ZZ turning point and "YY" candles after the ZZ turning point. These patterns will be logged and pattern recognition run on these resultants. Any type of clustering logic or other pattern identifiers should be run on these just the same as finger print or facial recognition software does. The idea here is to "identify" the pattern and market context so that a trade forecast can be made.

UPDATE: 

3/27/2015

The Zig Zag logic is complete.

The updated priority is as follows.

1. Creation of the Calender Dating algorithm added to the Zig Zag logging.  
2. These functions or algorithms coded within the Zig Zag logic to calculate and log the following
1. ZZ_bars
2. ZZ_change
3. ZZ_percent
4. ZZ_slope
5. ZZ_connecting_angle.left
6. ZZ_connecting_angle.right
3. Any additional algorithms deemed more efficient calculated in original ZigZag logging then being calculated later in R or another process in C++.
4. The ZigZag Mean, Standard Deviation and Median values.