Are you looking to begin your journey into Technical Indicators but unsure of where to start? Are you interested in implementing them using Python?
Look no further than the sample ebook “TECHNICAL INDICATORS – PYTHON AND TA-Lib” . This resource will guide you through the world of Technical Indicators, providing you with insights on the Ta-Lib library and assisting you in implementing a popular trading strategy using Python.
TA-Lib Library: Installation and usage guide
Comprehensive explanation and detailed formulas for the Stochastic Oscillator and its two variations
Step-by-step Python implementation of both versions from scratch
Implementation of the indicators using TA-Lib
Comparison of the results obtained from the different implementations
Insightful interpretation of the results
You’re keen to begin your learning journey in algorithmic trading
You desire to explore the functionalities of the TA-Lib library
You want to implement real-world examples using Python,
You are eager to gain insights into the contrasting implementations between TA-Lib and hands-on Python
I’m ready!
Hello there! I’m Hanane, a passionate individual with a deep interest in machine learning, AI (ChatGPT), and algorithmic trading. As the creator of this blogging website, I aim to share my knowledge and insights with you.
Currently, I work as an algorithmic trader in a bank. In my pursuit of continuous learning, I explore various fields such as machine learning, algorithmic trading, and most recently, ChatGPT.
In this sample ebook, I will guide you through the step-by-step implementation of a well-known momentum indicator in Python. Furthermore, I will provide a comparison between this implementation and the one found in TA-Lib, an essential library in algorithmic trading.
I hope you find this ebook enjoyable to read, and I welcome any feedback you may have.