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Duration 14 hours
Course Outline
Introduction to LLMs in Finance
- The impact of AI and LLMs on financial analysis
- An overview of LLM capabilities and their role in text analysis
- Case studies examining LLMs in financial forecasting and risk assessment
Processing Financial Data with LLMs
- Extracting financial indicators from unstructured data using LLMs
- Training LLMs on financial texts to perform sentiment analysis
- Connecting news sentiment to market movements
Constructing Predictive Models with LLMs
- Designing LLM-based models for stock price prediction
- Forecasting economic trends by leveraging LLM-generated insights
- Backtesting models against historical financial data
Integrating LLMs into Investment Strategies
- Incorporating LLM analytics into quantitative trading
- Applying LLMs for portfolio optimization and risk management
- Effectively communicating AI-driven insights to stakeholders
Hands-on Lab: Financial Market Prediction Project
- Setting up a financial data analysis environment utilizing LLMs
- Building a market prediction model with LLMs
- Assessing model performance and implementing improvements
Requirements
- A foundational understanding of financial markets and instruments
- Proficiency in Python programming and data analysis
- Working knowledge of machine learning concepts and statistical models
Target Audience
- Financial analysts
- Data scientists
- Investment professionals
