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1. What is Data Driven Investing?
1.1. Statistical Techniques
1.2. Computational tools
2. Getting Started
2.3. Cloud Setup
2.4. Local installation
3. Python Essentials
3.1. Basics
3.2. Collections
3.3. Numpy
3.4. Pandas
3.4.3. Indexing
3.4.4. Time-Series
3.4.5. Reshape
3.4.6. Merge
3.4.7. Group-by
3.4.8. Plotting
3.4.9. Cleaning data
3.4.10. Data Storage
3.5. Flow control
3.6. Functions
3.7. Plotting
4. Introduction to Asset Returns
4.11. The Choice of Frequency and Annualization of Returns
4.12. Data APIs
5. Timing Strategies
5.6. Expected Returns Timing
5.7. Volatility Timing
6. Factor Models
7. Portfolios
7.13. Linear Algebra Review
8. Capital Allocation
9. Cross-Sectional Equity Strategies
9.18. Momentum factor
9.19. An overview of factors
10. Capital Allocation II
11. Performance Evaluation
12. Machine Learning in Finance
13. Multi Factor Models
13.7. 📊 Interpreting Factor Models
14. Risk Management
15. Liquidity and Trading Cost Management
16. Leverage, Shorting, and Limits to Arbitrage
17. Gen AI and LLMs in Finance
18. Additional Statistics Material
19. Assignments
19.1. Assignment 1
19.2. Assignment 2
19.3. Assignment 3
19.6. Assignment 4
19.8. Assignment 5
Repository
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Assignments
19.
Assignments
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Please see below the class Assignments
