Python-Powered Algorithmic Trading: From Theory to Practice

Mohit Khandelwal (~mohitkh7)


2

Votes

Description:

Are you fascinated by the world of stock trading and eager to leverage the power of Python to automate trading strategies? This engaging and hands-on workshop will introduce participants to the exciting realm of algorithmic trading using the versatile Backtrader library.

In this workshop, participants will learn to simulate and backtest various trading strategies, allowing them to assess their effectiveness before deploying them in live markets. Essential aspects of technical analysis will be covered, from reading candlestick charts to understanding popular indicators. With step-by-step guidance, learners will gain practical experience in implementing trading algorithms, analyzing trade performance, and making data-driven decisions.

Interactive kahoot quizzes and Q&A sessions throughout the workshop will ensure participants grasp the concepts and stay engaged. By the end of the session, participants will have a clear understanding of how to build, test, and refine trading algorithms, setting them on the path to becoming proficient algorithmic traders.

Intended Audience:

This workshop is perfect for Python enthusiasts with an interest in financial markets, whether they are beginners looking to get started or experienced programmers seeking to expand their skills into the domain of algorithmic trading. This session promises to transform participants' trading approaches with the power of Python and Backtrader.

Libraries to be used:

  • Backtrader: A feature-rich Python framework for backtesting and trading. Backtrader allows you to focus on writing reusable trading strategies, indicators, and analyzers.
  • TA-Lib: Adds technical analysis capabilities to financial market trading applications, supporting 200+ indicators and candlestick pattern recognition.
  • Yfinance: A threaded and Pythonic way to download market data from Yahoo! Finance.
  • Other Libraries: numpy, pandas, seaborn, matplotlib, plotly.

Workshop Outline:

  • Introduction (20 Mins, Slides)
    • Speaker Introduction
    • Brief overview of stock trading and technical analysis
    • Quick walkthrough of candlestick chart reading and technical indicators
    • Introduction to algorithmic trading
    • How Python can facilitate algorithmic trading
  • Hands-On Begins (30 Mins, Exercises)
    • Overview of libraries to be used throughout the workshop
    • Setup: Initializing Colab notebook and importing libraries
    • Fetching stock price
    • Visualizing stock prices: Line chart, candlestick chart
  • Kahoot Quiz 1 (10 Mins)
  • Q&A / Break (10 Mins)
  • It’s Time for Trading! (1 Hour, Excercises)
    • Implementing a trade strategy (Moving Average)
    • Backtesting your trade strategy
    • Trade Analysis
    • Implementing another trade strategy (Hammer/Hanging Man Candlestick Pattern), backtesting it, and performing trade analysis
    • Comparing the two strategies to determine which one works best
  • Q&A / Break (10 Mins)
  • Kahoot Quiz 2 (10 Mins)
  • Closing Notes (20 Mins, Slides)
    • Take-home assignments
    • Further reading resources
  • Q&A (10 Mins)

Prerequisites:

Participants for this workshop should meet the following prerequisites:

  • They must have a laptop with Jupyter Notebook or access to Google Colab.
  • Basic understanding of Python programming.
  • Familiarity with Python libraries such as NumPy, pandas, and matplotlib.
  • Knowledge of reading candlestick charts and understanding popular technical indicators is beneficial but not necessary.
  • For those new to trading and technical analysis, it is recommended to review the Varsity blogs on Technical Analysis.

Video URL:

https://drive.google.com/file/d/1nFMIJp_6tkpZqFWROgnvR5bYojqb7BJa/view?usp=sharing

Content URLs:

Github Gist containing colab notebook source code: https://gist.github.com/mohitkh7/499ec2f9959d05298925c0f876ae9f37

Speaker Info:

Mohit Khandelwal is a dedicated Pythonist, focused on creating user-friendly software applications. He is a passionate problem solver with expertise in cloud computing, microservices architecture, and large scale backend components. With over 5 years of industry experience in Fintech domain and more than a decade of Python coding, he currently serves as a Senior Software Engineer at Bitgo. His past experience includes positions at Goldman Sachs, Genpact, and Infosys. He is always eager to learn, share and expand knowledge.

Speaker Links:

Mohit has delivered multiple talks and workshops on various platforms:

  • Workshop on "Robotics Programming with rospy" at Scipy India 2019, IIT Bombay [Video Link]
  • Workshop on "Learn Blockchain by Building One with Python" at Scipy India 2021
  • Talk on "The Zen of Python" at Scipy India 2019, IIT Bombay.
  • Masterclass on "Building Dynamic Websites Using AWS Serverless" in collaboration with Pregrad
  • Webinar on "Observer Design Pattern 101" with Pune Developer's Community Video Link
  • Webinar on "Promises in JavaScript" hosted by Indore Software Developer Community
  • Webinar on "Unit Testing in JavaScript" at the Tech Carnival event organized by Pune Developer's Community Video Link

Social Media Accounts:

Section: Other
Type: Workshops
Target Audience: Intermediate
Last Updated: