Sparse Portfolio Selection via Topological Data Analysis based Clustering
By Anubha Goel, Damir Filipović, Puneet Pasricha
Rating
1442
Battle Count: 37
Relevance
9/10
Highly relevant for developing efficient sparse portfolio strategies and improving index tracking performance
Implementation Complexity
7/10
Requires understanding of topological data analysis and clustering techniques, as well as portfolio optimization methods
Reproducibility
4/5
The paper provides detailed methodology and uses publicly available data, enhancing reproducibility
About this paper
Methodology: Topological Data Analysis based Clustering. Problem types: Portfolio Optimization, Index Tracking, Dimensionality Reduction.
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