Here, we will discuss how trading ideas are born and how they are turned into algorithmic trading strategies. Fundamentally, all trading ideas are driven by human intuition to a large extent. If markets have been moving up/down all the time, you might intuitively think that it will continue to move in the same direction, which is the fundamental idea behind trend-following strategies. Conversely, you might argue that if prices have moved up/down a lot, it is mispriced and likely to move in the opposite direction, which is the fundamental idea behind mean reversion strategies. Intuitively, you may also reason that instruments that are very similar to one another, or loosely dependent on one another, will move together, which is the idea behind correlation-based trading or pairs trading. Since every market participant has their own view of the...

Learn Algorithmic Trading
By :

Learn Algorithmic Trading
By:
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
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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