This chapter made use of some of the trading signals we've seen in the previous chapters to build realistic and robust trend-following and mean reversion trading strategies. In addition, we went another step further and made those basic strategies more sophisticated by adding a volatility measure trading signal to make it more dynamic and adaptive to different market conditions. We also looked at a completely new form of trading strategy in the form of trading strategies dealing with economic releases and how to carry out the analysis for that flavor of trading strategies for our sample Non Farm Payroll data. Finally, we looked at our most sophisticated and complex trading strategy so far, which was the statistical arbitrage strategy, and applied it to CAD/USD with the major currency pairs as leading trading signals. We investigated in great detail how to quantify...
Learn Algorithmic Trading
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Learn Algorithmic Trading
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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 (16 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Free Chapter
Algorithmic Trading Fundamentals
Deciphering the Markets with Technical Analysis
Predicting the Markets with Basic Machine Learning
Classical Trading Strategies Driven by Human Intuition
Sophisticated Algorithmic Strategies
Managing the Risk of Algorithmic Strategies
Building a Trading System in Python
Connecting to Trading Exchanges
Creating a Backtester in Python
Adapting to Market Participants and Conditions
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