ssmehta / technical

contains different indicators developed or collected for the freqtrade trading bot

technical

Welcome to Technical, where things are, well technical. This is a simple collection of indicators and utils to make the day to day operation of working with the freqtrade trading bot easier and more powerful!

What does it do for you

We basically provide you with easy to use indicators, collected from all over github and custom methods. Over time we plan to provide a simple API wrapper around TA-Lib, PyTi and others, as we find them. So you have one place, to find 100s of indicators.

Custom indicators

We will happily add your custom indicators to this repo!

1. Consensus - an indicator which is based on a consensus model, across several indicators you can easily customize these. It is based on the tradinvg view buy/sell graph. 1.1 MovingAverage Consensus 1.2 Oscillator Consensus 1.3 SUmmary Consensus
2. vfi
3. mmar
4. madrid_sqz
5. stc
6. ichimoku cloud
7. volume weighted moving average
8. laguerre
9. vpci
10. trendlines, 2 different algorithms to calculate trendlines
11. fibonacci retracements

Utilities

1. resample - easily resample your dataframe to a larger interval
2. merge - merge your resampled dataframe into your original dataframe, so you can build triggers on more than 1 interval!

Wrapped Indicators

This following indicators are available and have been 'wrapped' to just utilize a dataframe with the standard open/close/high/low/volume columns

1. cmf - chaikow money flow, requires dataframe and period
2. accumulation_distribtuion - requires a dataframe
3. osc - requires a dataframe and the periods
4. aroon - dataframe, period, field
5. atr - dataframe, period, field
6. atr_percent - dataframe, period, field
7. bollinger_bands - dataframe, period, stdv, field, prefix
8. cmo - dataframe, period, field
9. cci - dataframe, period
10. williams percent
11. momentum oscilator
12. hull moving average
13. ultimate oscillator
14. sma
15. ema
16. tema

We will try to add more and more wrappers as we get to it, but please be patient or help out with PR's! It's super easy, but also super boring work.

Usage

to use the library, please install it with pip

pip install git+https://github.com/berlinguyinca/technical

and than import the required packages

from technical.indicators import accumulation_distribution, ...
from technical.util import resample_to_interval, resampled_merge

have fun!