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Course Outline
Artificial Intelligence in the Trading and Asset Management Landscape for Government
- Current trends in algorithmic and AI-based trading strategies
- Overview of quantitative finance workflows and methodologies
- Key tools, platforms, and data sources utilized in the industry
Working with Financial Data in Python for Government
- Techniques for handling time series data using Pandas
- Methods for data cleaning, transformation, and feature engineering
- Construction of financial indicators and signals
Supervised Learning for Trading Signals for Government
- Application of regression and classification models for market prediction
- Evaluation of predictive models using metrics such as accuracy, precision, and Sharpe ratio
- Case study: development of an ML-based signal generator
Unsupervised Learning and Market Regimes for Government
- Use of clustering techniques to identify volatility regimes
- Dimensionality reduction methods for pattern discovery in financial data
- Applications of unsupervised learning in basket trading and risk grouping
Portfolio Optimization with AI Techniques for Government
- Review of the Markowitz framework and its limitations
- Advanced optimization techniques such as risk parity, Black-Litterman, and machine learning-based approaches
- Implementation of dynamic rebalancing using predictive inputs
Backtesting and Strategy Evaluation for Government
- Utilization of backtesting frameworks such as Backtrader or custom solutions
- Assessment of risk-adjusted performance metrics
- Strategies to avoid overfitting and look-ahead bias in model evaluation
Deploying AI Models in Live Trading for Government
- Integration with trading APIs and execution platforms for real-time operations
- Ongoing monitoring and re-training of models to maintain accuracy
- Ethical, regulatory, and operational considerations in deploying AI models
Summary and Next Steps for Government
Requirements
- A foundational knowledge of statistics and financial markets for government applications
- Experience with Python programming for data analysis tasks
- Familiarity with handling time series data for government
Audience
- Quantitative analysts in the public sector
- Trading professionals working in governmental financial roles
- Portfolio managers within government agencies
21 Hours
Testimonials (2)
it went through language right up to automation and made me aware of what capabilities I have.
Declan Glennon - Teleflex Medical Europe Ltd
Course - Copilot for Finance and Accounting Professionals
The background / theory of LLMs, the exercise