RSI-divergence-detector VS pandas-ta

Compare RSI-divergence-detector vs pandas-ta and see what are their differences.

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RSI-divergence-detector pandas-ta
1 17
71 4,756
- -
0.0 0.0
11 months ago 10 days ago
Python Python
MIT License MIT License
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RSI-divergence-detector

Posts with mentions or reviews of RSI-divergence-detector. We have used some of these posts to build our list of alternatives and similar projects.

pandas-ta

Posts with mentions or reviews of pandas-ta. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-23.

What are some alternatives?

When comparing RSI-divergence-detector and pandas-ta you can also consider the following projects:

Twitter_Activated_Crypto_Trading_Bot - Buys crypto through keyword detection in new tweets. Executes buy in 1 second and holds for a given time (e.g. Elon tweets 'doge', buys Dogecoin and sells after 5 minutes). Tested on Kraken and Binance exchanges

ta - Technical Analysis Library using Pandas and Numpy

shrimpy-python - Shrimpy’s Developer Trading API is a unified way to integrating trading functionality across every major exchange. Collect historical market data, access real-time websockets, execute advanced trading strategies, and manage an unlimited number of users.

ta-lib-python - Python wrapper for TA-Lib (http://ta-lib.org/).

finta - Common financial technical indicators implemented in Pandas.

Crypto-Signal - Github.com/CryptoSignal - Trading & Technical Analysis Bot - 4,100+ stars, 1,100+ forks

node-talib - A technical analysis library for node.js

intelligent-trading-bot - Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

py-market-profile - A library to calculate Market Profile (aka Volume Profile) for financial data from a Pandas DataFrame.

fundamental-analysis - Screen stocks on fundamentals and estimate their intrinsic value

tuneta - Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models