https://github.com/davidalexandermoe/portfolio-analysis-with-ffc-model
Analysis using R and Python of a set of ten portfolios composed by unknown UK stocks applying the Fama&French&Carhart 4 factor model.
https://github.com/davidalexandermoe/portfolio-analysis-with-ffc-model
cross-section finance portfolio-analysis regression stocks
Last synced: 7 months ago
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Analysis using R and Python of a set of ten portfolios composed by unknown UK stocks applying the Fama&French&Carhart 4 factor model.
- Host: GitHub
- URL: https://github.com/davidalexandermoe/portfolio-analysis-with-ffc-model
- Owner: DavidAlexanderMoe
- Created: 2023-09-18T11:10:29.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-09-18T12:08:46.000Z (about 2 years ago)
- Last Synced: 2025-01-19T22:24:59.048Z (9 months ago)
- Topics: cross-section, finance, portfolio-analysis, regression, stocks
- Language: TeX
- Homepage:
- Size: 701 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Portfolio Analysis with Fama & French & Carhart model
This a University group project made for the Finance Course. R was used for the statistical analysis and Python for the Data Visualization.
This report aims to analyze a set of ten portfolios composed of unknown UK stocks applying the Fama&French&Carhart 4 factor model to study the analogies and the differences. We have been provided with monthly data from October 1980 to December 2010 containing:
1. The returns of the ten UK portfolios. Stocks have been assigned to portfolios based on their market capitalization, from the smallest to the largest;
2. The four risk factors of the Fama&French&Carhart model (SMB, HML, UMD, and RMRF);
3. The risk-free return.
