In this chapter, we explored concepts of generating trading signals, such as support and resistance, based on the intuitive ideas of supply and demand that are fundamental forces that drive market prices. We also briefly explored how you might use support and resistance to implement a simple trading strategy. Then, we looked into a variety of technical analysis indicators, explained the intuition behind them, and implemented and visualized their behavior during different price movements. We also introduced and implemented the ideas behind advanced mathematical approaches, such as Autoregressive (AR), Moving Average (MA), Differentiation (D), AutoCorrelation Function (ACF), and Partial Autocorrelation Function (PACF) for dealing with non-stationary time series datasets. Finally, we briefly introduced an advanced concept such as seasonality, which explains how...
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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