In the rapidly evolving world of finance, algorithmic trading strategies powered by generative AI (GenAI) are transforming how traders approach the markets. This hands-on course is designed to equip traders, financial analysts, and developers with the skills to leverage GenAI for enhanced trading performance. Participants will delve into setting up a GenAI trading environment, creating custom AI-driven strategies, and automating trading processes. Through real-world examples and practical exercises, learners will gain the expertise to build, test, and deploy GenAI-enhanced trading systems, making this course an essential toolkit for modern algorithmic trading.
GenAI for Algorithmic Trading
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Beginner level
Recommended experience
3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
Implement generative AI techniques to analyze historical market data and generate insights that support both trading and research decisions.
Create and backtest trading strategies enhanced by GenAI, incorporating real-time data and predictive analytics to optimize decision-making.
Develop portfolio management strategies using GenAI to automate rebalancing, optimize allocations, and manage risk exposure effectively.
Employ GenAI to streamline and improve investment research processes, including sentiment analysis, trend analysis, and data-driven reporting.
Details to know
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Recently updated!
February 2025
Assessments
1 assignment
Taught in English
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There is 1 module in this course
In this course, you’ll learn how to leverage generative AI to enhance trading performance. You’ll explore setting up a GenAI trading environment, creating custom AI-driven strategies, and automating trading processes. Through real-world examples and practical exercises, you’ll gain the skills to build, test, and deploy GenAI-enhanced trading systems, equipping you with essential tools for modern algorithmic trading.
What's included
13 videos4 readings1 assignment3 peer reviews2 discussion prompts
Instructor
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Frequently asked questions
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