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Learn Algorithmic Trading

Learn Algorithmic Trading

By : Sebastien Donadio, Sourav Ghosh
3.8 (10)
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Learn Algorithmic Trading

Learn Algorithmic Trading

3.8 (10)
By: Sebastien Donadio, Sourav Ghosh

Overview of this book

It’s now harder than ever to get a significant edge over competitors in terms of speed and efficiency when it comes to algorithmic trading. Relying on sophisticated trading signals, predictive models and strategies can make all the difference. This book will guide you through these aspects, giving you insights into how modern electronic trading markets and participants operate. You’ll start with an introduction to algorithmic trading, along with setting up the environment required to perform the tasks in the book. You’ll explore the key components of an algorithmic trading business and aspects you’ll need to take into account before starting an automated trading project. Next, you’ll focus on designing, building and operating the components required for developing a practical and profitable algorithmic trading business. Later, you’ll learn how quantitative trading signals and strategies are developed, and also implement and analyze sophisticated trading strategies such as volatility strategies, economic release strategies, and statistical arbitrage. Finally, you’ll create a trading bot from scratch using the algorithms built in the previous sections. By the end of this book, you’ll be well-versed with electronic trading markets and have learned to implement, evaluate and safely operate algorithmic trading strategies in live markets.
Table of Contents (17 chapters)
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1
Section 1: Introduction and Environment Setup
3
Section 2: Trading Signal Generation and Strategies
6
Section 3: Algorithmic Trading Strategies
10
Section 4: Building a Trading System
14
Section 5: Challenges in Algorithmic Trading

Summary

This chapter explored what happens when algorithmic trading system and algorithmic trading strategies are deployed to live markets after months, and often years, of development and research. Many common issues with live trading strategies, such as not behaving or performing according to expectations, were discussed and we provided common causes and possible solutions or approaches to remedy these. This should help to prepare anyone looking to build and deploy algorithmic trading strategies to live markets, and equip them with the knowledge to improve trading strategy components when things don't go as expected.

Once the initial trading strategies are deployed and running in live markets as per expectations, we discussed the evolving nature of the algorithmic trading business and global markets in general. We covered a lot of different factors that cause profitable...

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