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...
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 (17 chapters)
Preface
Free Chapter
Section 1: Introduction and Environment Setup
Algorithmic Trading Fundamentals
Section 2: Trading Signal Generation and Strategies
Deciphering the Markets with Technical Analysis
Predicting the Markets with Basic Machine Learning
Section 3: Algorithmic Trading Strategies
Classical Trading Strategies Driven by Human Intuition
Sophisticated Algorithmic Strategies
Managing the Risk of Algorithmic Strategies
Section 4: Building a Trading System
Building a Trading System in Python
Connecting to Trading Exchanges
Creating a Backtester in Python
Section 5: Challenges in Algorithmic Trading
Adapting to Market Participants and Conditions
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