Python Algorithmic Trading Part 2: Real-Time Algorithmic Trading with the Interactive Brokers API

Notes before taking the course 📢

IMPORTANT NOTICE :

This course is designed to educate algorithmic trading and coding automation from a developer's perspective . The course content focuses on developing investment strategies and simulating them , and does not cover account opening, legal procedures, tax-related matters related to actual investments, etc. In addition, it does not serve as investment advice or financial counseling , and matters related to actual financial transactions should be carried out at one's own risk.

All trading strategies covered in the course are based on simulations and are for educational purposes only. If students have questions related to investing or trading, please understand that we cannot answer questions that are outside the scope of the course.

[Python Algorithm Trading Lecture] is a three-part series , and this lecture is 'Part 2'.

Part 2 is required to take Part 3 , and Part 1 is recommended.

• Part 1 - 'Python Data Analysis for Algorithmic Trading'

  
  

• Part 2 - 'Real-time algorithmic trading using Interactive Brokers API' (main lecture)

  
  

• Part 3 - 'Cloud Transaction Automation'

  • Learn how to automatically launch virtual machines to match your stock trading schedule with cloud automation.

    
    

Course Review Event

• There is a course review event. Please leave a course review for Part 1 and contact us by email (daniel@datatrain.education ) and we will issue a voucher for an additional 20% discount from the current price .

• Please refer to the last public lecture of Part 1 lecture.

Utilizing the world's No. 1 investment service API
Building a real-time investment pipeline

This course was created after much thought on whether it would be possible to include a universally applicable 'method' in the course so that any investment strategy can be put into practice immediately. The use of the API of Interactive Brokers (IBKR), the world's No. 1 market share, will enhance your investment execution ability.

Despite the above advantages, the reality is that there are few lectures that apply the IBKR API, which has the world's No. 1 market share in Korea. This lecture connects the IBKR API to Python to create a pipeline that can trade in real time.

Based on the latest investment portfolio
Easy, fast and safe automated trading execution

Learning through Quant Investment Project
Object Oriented Programming

'Inheritance', one of the core principles of object-oriented programming, allows you to create a completely new class by extending or modifying the functionality of an existing class. In this process, the inherited class can shorten development time and maintain code consistency by reusing the properties and methods of the base class.

The importance of code blocking and management

Blocking and organizing your code is an often overlooked part of programming. When it comes to efficiently integrating external code and building on it to add new features, well-structured code offers the following benefits:

• Performance Improvement : By reusing existing components, you can improve the performance of your overall system.

• Ease of debugging : When the structure of your code is clear, it becomes easier to find and fix errors.

• Extensibility : Code with a well-defined structure makes it easy to add new features or modify existing ones.

Hands-on example: PairsTradingUpdatePosition class

In our lectures Let's take the 'PairsTradingUpdatePosition' class as an example and see how this class can be extended by inheriting from other trading strategy classes through real code. Through this process, you will learn specifically how inheritance is applied to real code and how it affects code maintenance and optimization.

Things to note before taking the class

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