EconStor
metadata only
Structural Complexity of One-Factor Sparse Portfolio Selection: Exact Algorithms, Parameterized Hardness, and Restricted Circuit Lower Bounds
We study exact-cardinality, equally weighted minimum-variance portfolio selection under a one-factor covariance model supplied in factor form. In the nonnegative homoskedastic regime, selecting the K smallest loadings is optimal. Allowing strictly positive asset-specific idiosyncratic variances make
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Governed Human-AI Prioritization Under Uncertainty: Adaptive Estimation and Dependency-Constrained Portfolio Selection#673592
- Efficient Portfolio Selection of Some Assets in the Nigeria Market#406940
- Decision-Focused Fine-Tuning for Illiquid Asset Portfolio Optimization#684068
- Convex Optimization Is Free When Accuracy Is Expensive#1130006
- Some Further Asset Pricing Tests Using Information Variables: Portfolios vs Individual Stocks#942692
Record · ID 922121
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive