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Learn Algorithmic Trading

You're reading from   Learn Algorithmic Trading Build and deploy algorithmic trading systems and strategies using Python and advanced data analysis

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781789348347
Length 394 pages
Edition 1st Edition
Languages
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Authors (2):
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Sebastien Donadio Sebastien Donadio
Author Profile Icon Sebastien Donadio
Sebastien Donadio
Sourav Ghosh Sourav Ghosh
Author Profile Icon Sourav Ghosh
Sourav Ghosh
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Introduction and Environment Setup FREE CHAPTER
2. Algorithmic Trading Fundamentals 3. Section 2: Trading Signal Generation and Strategies
4. Deciphering the Markets with Technical Analysis 5. Predicting the Markets with Basic Machine Learning 6. Section 3: Algorithmic Trading Strategies
7. Classical Trading Strategies Driven by Human Intuition 8. Sophisticated Algorithmic Strategies 9. Managing the Risk of Algorithmic Strategies 10. Section 4: Building a Trading System
11. Building a Trading System in Python 12. Connecting to Trading Exchanges 13. Creating a Backtester in Python 14. Section 5: Challenges in Algorithmic Trading
15. Adapting to Market Participants and Conditions 16. Other Books You May Enjoy

Continued profitability in algorithmic trading

In the first half of this chapter, we looked at what common issues you can expect when deploying algorithmic trading strategies that have been built and calibrated in simulations and appear to be profitable. We discussed the impact and common causes of simulation dislocation, which cause deviation in trading strategy performance when deployed to live trading markets. We then explored possible solutions to dealing with those problems and how to get algorithmic trading strategies off the ground and start scaling up safely to build a profitable algorithmic trading business. Now, let's look at the next steps after getting up and running with the algorithmic trading strategies in live trading markets. As we mentioned before, live trading markets are in a constant state of evolution, as participants enter and exit markets and adapt...

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