Learn to use 10+ trading strategies including Statistical Arbitrage, Machine Learning, Quantitative techniques and more. This bundle of courses is perfect for traders and quants who want to learn and use Python in trading.
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This course is an introduction to different strategy paradigms, back-testing techniques, available programming languages, regulations & compliance around algo trading. The course is designed for anyone who wants to get started with algorithmic trading.
(Level: Beginners, Duration: 2 hours)
Perfect course for beginners in programming. Learn important concepts from scratch and code using interactive help-based exercises. Develop three trading strategies using technical indicators and popular libraries. Understand the dynamics that affect backtesting results and how to optimize your strategies accordingly.
(Level: Beginners, Duration: 6 hours)
Learn to use mathematics, statistics and econometric models in your trading. This is an application based course created by traders who have been using quantitative trading techniques and find profitable strategies using them. Understand market data and its nuances to be able to apply these techniques.
(Level: Beginners, Duration: 4 hours)
Statistical arbitrage is one of the most popular trading strategies which is often used by algorithmic traders. Learn how to create this strategy in both Excel and Python. Start from finding pairs to generating trading signals in a practical fashion. A special section covers risks involved and methods to minimize losses!
(Level: Intermediate, Duration: 3 hours)
An important technique, not to be missed, by alpha seekers. Start by learning basic concepts in machine learning. Work with markets data and process it for the learning model. Understand important concepts such as variance and bias of the model to be able to optimize it well without overfitting. Learn to predict market direction using an algorithm which you will code!
(Level: Intermediate, Duration: 5 hours)
Generate trading signals which rely on predictions by a machine learning model. Learn all about classification techniques which can help in predicting up/down/neutral market trends. Build supervised classifiers such as logistic regression classifier and support vector classifier in Python and incorporate them in trading strategies. Learn from traders and machine learning experts to get the best of both the worlds.
(Level: Intermediate, Duration: 4 hours)
"Very useful and easy to follow, not only learn to code but also it’s a clear explanation about the maths under the hood for better understanding"
"An excellent introduction of machine learning in trading! If one is new to the field of trading and would like to check how beautifully analytical settings like ML works, please consider spending some time on this lovely interactive course!"
"Excellent course. The material is well structured. Provides a comprehensive overview of using Python for trading, commonly used libraries, interactive coding exercises to further understanding, and coding strategy examples. Highly recommended for anyone looking to build trading strategies in Python."
"Wonderfully explained the delta neutral and gamma scalping strategy. Also, got some idea about trading strategies using technical indicators."
