Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
The Role of AI in Trading and Asset Management
- Emerging trends in algorithmic and AI-driven trading.
- An overview of quantitative finance workflows.
- Essential tools, platforms, and data sources.
Managing Financial Data with Python
- Processing time series data using Pandas.
- Data cleaning, transformation, and feature engineering.
- Constructing financial indicators and trading signals.
Supervised Learning for Trading Signals
- Applying regression and classification models for market prediction.
- Assessing predictive models using metrics such as accuracy, precision, and Sharpe ratio.
- Case study: Developing an ML-based signal generator.
Unsupervised Learning and Market Regimes
- Utilizing clustering to identify volatility regimes.
- Applying dimensionality reduction for pattern discovery.
- Use cases in basket trading and risk grouping.
AI-Driven Portfolio Optimization
- Examining the Markowitz framework and its constraints.
- Exploring risk parity, Black-Litterman, and ML-based optimization methods.
- Implementing dynamic rebalancing with predictive inputs.
Backtesting and Strategy Evaluation
- Leveraging Backtrader or custom frameworks for testing.
- Analyzing risk-adjusted performance metrics.
- Mitigating overfitting and look-ahead bias.
Live Deployment of AI Models
- Integrating models with trading APIs and execution platforms.
- Managing model monitoring and re-training cycles.
- Addressing ethical, regulatory, and operational considerations.
Course Summary and Future Steps
Requirements
- Foundational knowledge of basic statistics and financial markets.
- Practical experience in Python programming.
- Familiarity with time series data analysis.
Target Audience
- Quantitative analysts.
- Trading professionals.
- Portfolio managers.
21 Hours
Testimonials (1)
i already have some reports that i know, i will use some of the prompts that looked at today
