Python for Finance and Algorithmic Trading: Machine Learning, Deep Learning, Time Series Analysis, Risk and Portfolio Management, Quantitative Trading for MetaTrader5(TM) Live Trading by Lucas Inglese

Python for Finance and Algorithmic Trading: Machine Learning, Deep Learning, Time Series Analysis, Risk and Portfolio Management, Quantitative Trading for MetaTrader5(TM) Live Trading by Lucas Inglese

Chapter 1: Read me
1.1. Find the code
All the resources in the book are available on the
GitHub repository ( https://github.com/Quantreo/2nd-

edition-BOOK-AMAZON-Python-for-Finance-and-

Algorithmic-Trading ). If there is an issue with this link
or something else related to the code, contact us using
the contact page  www.quantreo.com . 
Before reading this book, you should download Jupyter
Notebook using Anaconda Navigator (
https://www.anaconda.com ). In Chapter 01, you can
find a notebook that installs all the necessary libraries
for the book. All the additional readings can be found
on the README.md file on the repository Github.
1.2. Join our community
Follow us on social media to obtain the latest
algorithmic trading information, tips, and ready-to-use
strategies. Moreover, join the discord forum of the
community to ask any questions about the book to
read it easily!

Chapter 2: Prerequisites
This chapter discusses the necessary prerequisites to
understand this book thoroughly. First, we will discuss
some math, statistics, algebra, and optimization
basics. Then, the leading financial theories and the
Python basics are mandatory to implement our trading
strategies.
2.1. Mathematical prerequisites
This section aims to detail many mathematical terms
and concepts necessary for the book's whole
comprehension. However, it is not complete math for
the finance course. We will cover some introductory
algebra, statistics, and optimization.
2.1.1. Algebra

Python for Finance and Algorithmic Trading: Machine Learning, Deep Learning, Time Series Analysis, Risk and Portfolio Management, Quantitative Trading for MetaTrader5(TM) Live Trading by Lucas Inglese