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Learn Algorithmic Trading

You're reading from  Learn Algorithmic Trading

Product type Book
Published in Nov 2019
Publisher Packt
ISBN-13 9781789348347
Pages 394 pages
Edition 1st Edition
Languages
Authors (2):
Sebastien Donadio Sebastien Donadio
Profile icon Sebastien Donadio
Sourav Ghosh Sourav Ghosh
Profile icon Sourav Ghosh
View More author details

Table of Contents (16) Chapters

Title Page
Copyright and Credits About Packt Contributors Preface 1. Algorithmic Trading Fundamentals 2. Deciphering the Markets with Technical Analysis 3. Predicting the Markets with Basic Machine Learning 4. Classical Trading Strategies Driven by Human Intuition 5. Sophisticated Algorithmic Strategies 6. Managing the Risk of Algorithmic Strategies 7. Building a Trading System in Python 8. Connecting to Trading Exchanges 9. Creating a Backtester in Python 10. Adapting to Market Participants and Conditions 1. Other Books You May Enjoy

Learning how to choose the correct assumptions

Backtesting is a required step for deploying trading strategies. We use the historical data stored in databases to reproduce the behavior of the trading strategy. The fundamental assumption is that any methodology that functioned in the past is probably going to function in the future. Any strategies that performed ineffectively in the past are probably going to perform inadequately in the future. This section investigates what applications are utilized in backtesting, what sort of information is obtained, and how to utilize them.

A backtester can be a for-loop or event-driven backtester system. It is always important to consider how much time you will spend in order to achieve higher accuracy. It is impossible to obtain a model corresponding to reality; a backtester will just be a model of reality. However, there are rules...

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