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Learn Algorithmic Trading
Learn Algorithmic Trading

Learn Algorithmic Trading: Build and deploy algorithmic trading systems and strategies using Python and advanced data analysis

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Profile Icon Sebastien Donadio Profile Icon Sourav Ghosh
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$9.99 $35.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8 (10 Ratings)
eBook Nov 2019 394 pages 1st Edition
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$9.99 $35.99
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Arrow left icon
Profile Icon Sebastien Donadio Profile Icon Sourav Ghosh
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$9.99 $35.99
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8 (10 Ratings)
eBook Nov 2019 394 pages 1st Edition
eBook
$9.99 $35.99
Paperback
$48.99
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Free Trial
Renews at $19.99p/m
eBook
$9.99 $35.99
Paperback
$48.99
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Renews at $19.99p/m

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Learn Algorithmic Trading

Algorithmic Trading Fundamentals

Algorithmic trading, or automated trading, works with a program that contains a set of instructions for trading purposes. Compared to a human trader, this trade can generate profits and losses at a higher speed. In this chapter, this will be your first time being exposed to trading automation. We will walk you through the different steps to implement your first trading robot. You will learn the trading world and the technical trading components behind it. We will also go into detail about the tools that you will use and, by the end of this chapter, you will be capable of coding your first native trading strategy in Python. We will cover the following topics in this chapter:

  • Why are we trading?
  • Introducing algorithm trading and automation
  • What the main trading components are
  • Setting up your first programming environment
  • Implementing your...

Why are we trading?

From the Roman era through to the present day, trading is an inherent part of humankind. Buying raw materials when the price is low to resell it when the price is high has been a part of many cultures. In ancient Rome, the rich Romans used the Roman Forum to exchange currencies, bonds, and investments. In the 14th century, traders negotiated government debts in Venice. The earliest form of the stock exchange was created in Antwerp, Belgium, in 1531. Traders used to meet regularly to exchange promissory notes and bonds. The conquests of new worlds entailed a high cost, but also a good return. The Dutch East India Company in 1602 opened their capital for investors to participate in this costly project with a high potential return. During the same time period, a well-known tulip was sold everywhere in the world, creating a profitable market for investors and sellers...

Basic concepts regarding the modern trading setup

This section will cover the basics of trading and what drives market prices, as well as supply and demand.

As we touched upon in the previous section, trading has been around since the beginning of time, when people wanted to exchange goods between one another and make profits while doing so. Modern markets are still driven by basic economic principles of supply and demand. When demand outweighs supply, prices of a commodity or service are likely to rise higher to reflect the relative shortage of the commodity or service in relation to the demand for it. Conversely, if the market is flooded with a lot of sellers for a particular product, prices are likely to drop. Hence, the market is always trying to reflect the equilibrium price between available supply and demand for a particular product. We will see later how this is the fundamental...

Understanding algorithmic trading concepts

We introduced a lot of new concepts in the previous section, such as exchange order books (consisting of different kinds of orders sent by market participants), exchange matching algorithms, exchange market data protocols, and exchange order entry protocols. Let's formally discuss these in greater detail here.

Exchange order book

The exchange order book maintains all incoming buy and sell orders placed by clients. It tracks all attributes for incoming orders—prices, number of contracts/shares, order types, and participant identification. Buy orders (or bids) are sorted from the highest price (best price) to the lowest price (worst price). Bids with higher prices have...

From intuition to algorithmic trading

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...

Components of an algorithmic trading system

In an earlier section, we provided a top-level view of the entire algorithmic trading setup and many of the different components involved. In practice, a complete algorithmic trading setup is divided into two sections, as shown in the following diagram:

  • Core infrastructure deals with exchange-facing market data protocol integration, market data feed handlers, internal market data format normalization, historical data recording, instrument definition recording and dissemination, exchange order entry protocols, exchange order entry gateways, core side risk systems, broker-facing applications, back office reconciliation applications, addressing compliance requirements, and others.
  • Algorithmic trading strategy components deal with using normalized market data, building order books, generating signals from incoming market data and order...

Designing a trading strategy based on trend- and momentum-based indicators

Trading strategies based on trend and momentum are pretty similar. If we can use a metaphor to illustrate the difference, the trend strategy uses speed, whereas the momentum strategy uses acceleration. With the trend strategy, we will study the price historical data. If this price keeps increasing for the last fixed amount of days, we will open a long position by assuming that the price will keep raising. 

The trading strategy based on momentum is a technique where we send orders based on the strength of past behavior. The price momentum is the quantity of motion that a price has. The underlying rule is to bet that an asset price with a strong movement in a given direction will keep going in the same direction in the future. We will review a number of technical indicators expressing momentum...

Creating trading signals based on fundamental technical analysis

This section will show you how to use technical analysis to build trading signals. We will start with one of the most common methods, the simple moving average, and we will discuss more advanced techniques along the way. Here is a list of the signals we will cover:

  • Simple Moving Average (SMA)
  • Exponential Moving Average (EMA)
  • Absolute Price Oscillator (APO)
  • Moving Average Convergence Divergence (MACD)
  • Bollinger Bands (BBANDS)
  • Relative Strength Indicator (RSI)
  • Standard Deviation (STDEV)
  • Momentum (MOM)

Simple moving average

Simple moving average, which we will refer to as SMA, is a basic technical analysis indicator. The simple moving average, as you may have...

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Key benefits

  • Understand the power of algorithmic trading in financial markets with real-world examples
  • Get up and running with the algorithms used to carry out algorithmic trading
  • Learn to build your own algorithmic trading robots which require no human intervention

Description

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.

Who is this book for?

This book is for software engineers, financial traders, data analysts, and entrepreneurs. Anyone who wants to get started with algorithmic trading and understand how it works; and learn the components of a trading system, protocols and algorithms required for black box and gray box trading, and techniques for building a completely automated and profitable trading business will also find this book useful.

What you will learn

  • Understand the components of modern algorithmic trading systems and strategies
  • Apply machine learning in algorithmic trading signals and strategies using Python
  • Build, visualize and analyze trading strategies based on mean reversion, trend, economic releases and more
  • Quantify and build a risk management system for Python trading strategies
  • Build a backtester to run simulated trading strategies for improving the performance of your trading bot
  • Deploy and incorporate trading strategies in the live market to maintain and improve profitability

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Publication date : Nov 07, 2019
Length: 394 pages
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Language : English
ISBN-13 : 9781789342147
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Product Details

Publication date : Nov 07, 2019
Length: 394 pages
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Language : English
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Table of Contents

16 Chapters
Section 1: Introduction and Environment Setup Chevron down icon Chevron up icon
Algorithmic Trading Fundamentals Chevron down icon Chevron up icon
Section 2: Trading Signal Generation and Strategies Chevron down icon Chevron up icon
Deciphering the Markets with Technical Analysis Chevron down icon Chevron up icon
Predicting the Markets with Basic Machine Learning Chevron down icon Chevron up icon
Section 3: Algorithmic Trading Strategies Chevron down icon Chevron up icon
Classical Trading Strategies Driven by Human Intuition Chevron down icon Chevron up icon
Sophisticated Algorithmic Strategies Chevron down icon Chevron up icon
Managing the Risk of Algorithmic Strategies Chevron down icon Chevron up icon
Section 4: Building a Trading System Chevron down icon Chevron up icon
Building a Trading System in Python Chevron down icon Chevron up icon
Connecting to Trading Exchanges Chevron down icon Chevron up icon
Creating a Backtester in Python Chevron down icon Chevron up icon
Section 5: Challenges in Algorithmic Trading Chevron down icon Chevron up icon
Adapting to Market Participants and Conditions Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8
(10 Ratings)
5 star 40%
4 star 30%
3 star 10%
2 star 10%
1 star 10%
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Jamie Oct 08, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Covers order book backtesting.
Amazon Verified review Amazon
Robin T. Wernick Dec 01, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Analyzing and using Trading Indicators deserves a careful introduction to avoid confusion and the common misunderstandings that redound throughout the marketplace. This book avoids the common misunderstandings about a diverse series of indicators and gives many detailed examples of their proper use. It also provides reasonably detailed code examples to let the reader know how to implement them for general use.The reader is still going to need the examples from other sources to acquire the gigabytes of stock data from the internet needed to make this information useful. But, one book cannot do it all. This volume is an excellent place to start and holds a premier position on my bookshelf.
Amazon Verified review Amazon
Fable Dec 31, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book literally gives you the keys to the kingdom. If you have the patience and time for this book.. you will go from aspiring trader to a full on engineer of your own trading system. Each chapter explains a topic, then codes it. Really great work on this book
Amazon Verified review Amazon
JB Jun 02, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I'm only getting started in this topic, but so far the book is great. It covers a broad amount of information needed to get started with algorithmic trading. All without focusing on topics that are too basic. Some algo trading books spend too much time on basic programming, this one focuses more on trading methods and technologies. Just what I was looking for.Also, please be aware that that color images are available free from the publisher. I viewed an electronic version of the book and the link is in the preface. Not sure if the link is in the paper version, but the images are still freely available.
Amazon Verified review Amazon
Rodrigo Jul 17, 2021
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I’ve been studying AT for couple of months, I’ve taken some courses at Udemy, and have bought previous basic books of AT.This book I would not recommend it for a completely beginner at this field. You should already know some basic concepts in AT and How to perform a very basic strategy, how to perform a simple back tester, event driven, how to simulate buys and sells, know what is an API, optimization, know the language of AT the vocabulary, etc. And definitely previous knowledge programming in Python.This book explains all the basics of an AT system and how it works but in a very solid and formal way. The codes works well, graphs works well everything is good. Explanations of codes maybe are a little bit poor but not terrific. Even though I had Studied some books before I would consider this book a beginner-intermediate book, IT IS NOT A TRIVIAL BOOK, it is not easy and less if you are a total beginner. In general I really like this book because it is a very solid book for understanding all the pillars of creating a trading system. Very recommended
Amazon Verified review Amazon
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