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Trading Using LLM: Concepts and Strategies

795 Learners
6 Hours
Utilise Large Language Models (LLMs) to build sentiment-driven trading strategies. This course covers LLM basics, prompt engineering for actionable insights, and practical use in trading. Learn to extract sentiment scores from event transcripts like FED meetings or earnings calls, and develop different strategies around it. Analyse your strategy's performance rigorously, leveraging LLM capabilities for informed trading decisions.
Level
Advanced
Authors
Dr. Ernest P. Chan
Dr. Hamlet Medina
Price Lifetime Access Limited Time Offer

₹7000/-₹27999/-

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  • Live Trading
  • Learning Track
  • Prerequisites
  • Syllabus
  • About author
  • Testimonials
  • Faqs

Live Trading

  • Comprehend the foundational aspects of large language models
  • Evaluate the process of training an LLM and prompt engineering
  • Extract sentiment score from transcripts using LLM
  • Develop entry and exit trading signals by using sentiment scores generated using LLM
  • Design and backtest an intraday trading strategy based on sentiment scores generated by LLM. Analyse performance and conduct trade-wise analysis.
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Skills Covered

learning track 5

This course is a part of the Learning Track: Artificial Intelligence in Trading Advanced

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Course Features

  • Community
    Community

    Faculty Support on Community

  • Interactive Coding Exercises
    Interactive Coding Exercises

    Interactive Coding Practice

  • Trade & Learn Together
    Trade & Learn Together

    Trade and Learn Together

  • Get Certified
    Get Certified

    Get Certified

Prerequisites

Fluency with Python, including Python libraries like Pandas, Numpy, and Matplotlib. You can enrol for the ‘Python for Trading: Basic’ course on Quantra to attain a basic level of understanding of Python. You can also check our course on ‘Introduction to Machine Learning for Trading’ if you are not familiar with machine learning concepts.

Syllabus

WEBINAR

Trading Using LLM | Generative AI & Sentiment Analysis for Finance

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about author

Dr. Ernest P. Chan
Dr. Ernest P. Chan
Dr. Ernest Chan is the Managing Member of QTS Capital Management, LLC., a commodity pool operator and trading advisor. QTS manages a hedge fund as well as individual accounts. He has worked in IBM human language technologies group where he developed natural language processing system which was ranked 7th globally in the defense advanced research project competition. He also worked with Morgan Stanley’s Artificial intelligence and data mining group where he developed trading strategies.
Dr. Hamlet Medina
Dr. Hamlet Medina
Dr. Hamlet Medina is the Chief Data Scientist at Criteo, a great mathematician, and has been very successful in applying LLMs on an enterprise scale.
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