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

Ghosh, Sourav, Donadio, Sebastien



Key Features

  • 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

Book 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.

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

Who this book is 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.



  • 透過實際案例了解在金融市場中的演算法交易的威力

  • 學習使用演算法進行演算法交易的基本操作

  • 學習建立不需要人為干預的演算法交易機器人






  • 瞭解現代演算法交易系統和策略的組件

  • 使用Python在演算法交易信號和策略中應用機器學習

  • 基於均值回歸、趨勢、經濟發布等建立、可視化和分析交易策略

  • 為Python交易策略建立風險管理系統

  • 構建一個回測器,運行模擬交易策略,以提高交易機器人的性能

  • 在實際市場中部署和整合交易策略,以維持和提高盈利能力




Sebastien Donadio is the Chief Technology Officer at Tradair, responsible for leading the technology. He has a wide variety of professional experience, including being head of software engineering at HC Technologies, partner and technical director of a high-frequency FX firm, a quantitative trading strategy software developer at Sun Trading, working as project lead for the Department of Defense. He also has research experience with Bull SAS, and an IT Credit Risk Manager with Société Générale while in France. He has taught various computer science courses for the past ten years in the University of Chicago, NYU and Columbia University. His main passion is technology but he is also a scuba diving instructor and an experienced rock-climber.

Sourav Ghosh has worked in several proprietary high-frequency algorithmic trading firms over the last decade. He has built and deployed extremely low latency, high throughput automated trading systems for trading exchanges around the world, across multiple asset classes. He specializes in statistical arbitrage market-making, and pairs trading strategies for the most liquid global futures contracts. He works as a Senior Quantitative Developer at a trading firm in Chicago. He holds a Masters in Computer Science from the University of Southern California. His areas of interest include Computer Architecture, FinTech, Probability Theory and Stochastic Processes, Statistical Learning and Inference Methods, and Natural Language Processing.


Sebastien Donadio 是 Tradair 的首席技術官,負責領導技術團隊。他擁有豐富的專業經驗,包括擔任 HC Technologies 的軟體工程主管、高頻外匯公司的合夥人和技術總監、Sun Trading 的量化交易策略軟體開發人員,以及國防部的專案主管。他還在法國的 Bull SAS 進行過研究,並在 Société Générale 擔任 IT 信用風險經理。他在芝加哥大學、紐約大學和哥倫比亞大學教授過各種計算機科學課程已有十年之久。他主要熱衷於技術,但也是一位潛水教練和經驗豐富的攀岩者。

Sourav Ghosh 在過去十年中曾在多家專有高頻算法交易公司工作。他建立並部署了極低延遲、高吞吐量的自動交易系統,用於全球各交易所的交易,涵蓋多個資產類別。他專注於統計套利市場做市商和對最流動的全球期貨合約進行配對交易策略。他目前在芝加哥的一家交易公司擔任高級量化開發人員。他擁有南加州大學的計算機科學碩士學位。他的興趣領域包括計算機架構、金融科技、概率論和隨機過程、統計學習和推理方法,以及自然語言處理。


  1. Algorithmic Trading Fundamentals
  2. Deciphering the Markets with Technical Analysis
  3. Predicting the Markets with basic Machine Learning
  4. Classical Trading Strategies
  5. Sophisticated Algorithmic Strategies
  6. Managing Risk of Algorithmic Strategies
  7. Building a Trading System in Python
  8. Connecting to trading exchanges
  9. Creating a Backtester in Python
  10. Adapting to market participants and changing financial markets


- 演算法交易基礎
- 透過技術分析解讀市場
- 利用基本機器學習預測市場
- 經典交易策略
- 複雜的演算法策略
- 管理演算法策略的風險
- 使用Python建立交易系統
- 連接到交易所
- 使用Python建立回測器
- 適應市場參與者和不斷變化的金融市場