Harmonic Patterns

28 thg 10, 2023

Harmonic Patterns

Harmonic Pattern utilizes the recognition of specific structures that possess distinct and consecutive Fibonacci ratio alignments that quantify and validate harmonic patterns. These patterns calculate the Fibonacci aspects of these price structures to identify highly probable reversal points in the financial markets. This methodology assumes that harmonic patterns, like many patterns and cycles in life, continually repeat.

Input Parameters:
Zigzag Setup:
These group of parameters are used to identify the swing points. The script also draws the Zigzag line and swing labels based on these parameters.

Harmonic Pattern Setup:
Ignore XD leg calculations – Optionally one can choose to ignore the XD leg calculation.
Fixed value leg offset % - Fixed value leg parameters are such parameters where single value Fibonacci value is used. This makes pattern identification very rare. To overcome this one can input % value which would be used to derive the range of Fibonacci numbers for pattern identification. E.g. XD leg in Bat pattern has fixed leg of 88.6%, If we input 5% as fixed value leg offset % then instead of fixed value of 88.6%, script calculates range as 88.6% + 5% (Value 1) and 88.6% - 5% (Value 2) and uses the same for pattern identification.
The script plots a diamond shape label on the last candle of the chart. The label has been enabled with a tooltip which shows number of patterns of each type along with the time where latest pattern is located.
This script covers harmonic patterns listed in the table below. Each harmonic pattern has bullish and bearish variants. All these patterns have 4 legs known as XABCD.

The Patterns have been configured as specified in the table below. Refer to Figure 1 and Figure 2 to understand how to read and interpret the table.



Figure 1


Figure 2

3 thg 12, 2023

Phát hành các Ghi chú

Added new input parameter 'Deviation %'
This is how this input parameter is used in the pattern detection:
e.g. BAT pattern have XB leg range as 38.2% to 50% and 'Deviation%' is set to 0.01
then while pattern detection range will be calculated by
50% + 0.01% and
38.2% - 0.01%
This will help in detecting patterns which are little away from defined pattern leg ranges