This project analyzes monthly excess returns from the SCS characteristic-managed portfolios dataset, sourced from Serhiy Kozak's data repository. The goal is to recommend an investment strategy based on portfolio selection and performance metrics.
- Dropped data from 1963–1999 to focus on more recent, relevant trends.
- Cleaned missing data using forward fill (limited cases).
- Final dataset includes 55 portfolios over 252 months.
- Visualizations and summary statistics support a data-driven portfolio recommendation.
Project.ipynb: Jupyter notebook with full analysis and visualization code.Presentation.pdf(if applicable): Summary slide deck prepared for investors.README.md: Project overview and documentation.
Develop an investment strategy for a hypothetical fund by:
- Evaluating performance across various characteristic-managed portfolios.
- Selecting portfolios with strong historical returns and stability.
- Presenting the strategy to potential investors via a 10-slide deck.
- Python (Pandas, NumPy, Matplotlib, Seaborn)
- Jupyter Notebook
Kozak, Serhiy, et al. (2020). Shrinking the Cross Section. Journal of Financial Economics.