Introduction to Algorithmic Trading

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 Basic Info : Introductory course on Algorithmic Trading
Level : Basic
Commitment  : 8 hours of study, 4 sessions of 2 hours each
Technical Requirement : Laptop with a minimum of 2 GB RAM and OS Windows XP or above
Scheduled Date : 25th August 2024


In this 8-hour course, participants delve into the essential principles of trading in financial markets through algorithmic strategies. Understanding that trading without a proven, profitable algorithmic strategy may lead to inconsistent results, students explore key concepts including Algorithmic Trading Foundations, Building Algorithmic Trading Strategies, Implementing Quantitative Analysis Techniques, Understanding Market Data Sources, Backtesting Strategies, and more. Additionally, learners will grasp the fundamentals of market dynamics and price action, enabling them to interpret and analyze chart data with confidence and proficiency.

What Will I Learn

At the end of this course, you will understand:

You will be able to:

  • analyze diverse topics including financial markets and technical indicators
  • exhibit a comprehensive grasp of algorithmic trading strategies
  • recognize avenues for networking with professionals in the algorithmic trading industry
  • construct case studies illustrating the utilization of algorithms in analyzing stock charts


  • Introduction to Algorithms
  • Who uses and provides algorithms?
  • Quantitative Trading
  • Advantages and Disadvantages

  • Simple Moving Average
  • Momentum Based
  • MACD
  • Bollinger Bands
  • RSI (Relative Strength Index)

  • Build trading model
  • Quoting or Hitting strategy
  • Back Testing and Optimizing

  • Back testing
  • Programming Languages
  • Data
  • Web based platform

How It works

   Live Online Sessions
Each session is interactive and informative, featuring case studies, quizzes and projects

   Interact, Learn and Grow enables you to master the concepts, interact with expert faculty and other learners and be a part of the community whilst growing.

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