First Version of an (not yet) iterative Elliott Wave scanner in financial data.

use Python 3.9 environment and install all packages via pip install -r requirements.txt

Start with example_monowave.py to see how the basic concept (finding monowaves) works and play with the parameter skip_n.

Then have a look into example_12345_impulsive_wave.py to see how the algorithm works for finding 12345 impulsive movements.

Use get_data.py script to download data directly from yahoo finance.

The basic idea of the algorithm is to try a lot of combinations of possible wave patterns for a given OHLC chart and validate each one against a given set of rules (e.g. against an 12345 impulsive movement).

The smallest element in a chart (or a trend) is called a MonoWave: The impulsive movement from a given low (or high) to the next high (or down to the low), where each candle (exactly: high / low) forms a new high (or new low respectively).

The MonoWave ends, once a candle breaks this "micro trend".

There is MonoWaveUp and the MonoWaveDown, denoting the direction of the wave.

WaveOptions are a set of integers denoting how many of the (local) highs or lows should be skipped to form a MonoWave.

The essential idea is, that with the parameter skip=, smaller corrections can be skipped. In case of an upwards trend, e.g. skip=2 will skip the next 2 maxima.

A WavePattern is the chaining of e.g. in case for an Impulse 5 MonoWaves (alternating between up and down direction). It is initialized with a list of MonoWave.

WavePattern can be validated against a set of rules. E. g. form a valid 12345 impulsive waves, certain rules have to apply for the monowaves, e.g. wave 3 must not be the shortest wave, top of wave 3 must be over the top of wave 1 etc.

Own rules can be created via inheritance from the base class. There are rules implemented for 12345 Impulse. Leading Triangle and for ABC Corrections.

To create an own rule, the .set_conditions() method has to be implemented for every inherited rule. The method has a dict, having arbitrarily named keys, having {'waves': list 'function': ..., 'message': ...} as value.

For waves you pass a list of waves which are used to validate a specific rule, e.g. [wave1, wave2].

For function you use a lambda function to check, e.g. lambda wave1, wave2: wave2.low > wave1.low

For message you enter a message to display (in case WavePattern(..., verbose=True) is set).

Note that only if all rules in the conditions are True the whole WaveRule is valid.

Once you have a WavePattern (chaining of 5 MonoWave for an impulse or 3 MonoWave for a correction) You can check against a WaveRule via the .check_rule(waverule: WaveRule) method.

A WaveCycle is the combination of an impulsive (12345) and a corrective (ABC) movement. Not working atm.

Is used to find impulsive and corrective movements. Not working atm.

There are three WaveOptionsGenerators available at the moment to fit the needs for creating tuples of 2, 3 and 5 integers (for a 12 TDWave, an ABC Correction and a 12345 Impulse).

The generators already remove invalid combinations, e.g. [1,2,0,4,5], as after selecting the next minimum (3rd index is 0), for the 4th and 5th wave skipping is not allowed.

As unordered sets are used, the generators have the .options_sorted property to go from low numbers to high ones. This means that first, the shortest (time wise) movements will be found.

Contains some plotting functions to plot a MonoWave (a single movement), a WavePattern (e.g. 12345 or ABC) and a WaveCycle (12345-ABC).

For different models there are plotting functions. E.g. use plot_monowave to plot a MonoWave instance or plot_pattern for a WavePattern.