Sparse index tracking using sequential Monte Carlo

DOI10.1080/14697688.2022.2057353zbMath1498.91498OpenAlexW4229061303MaRDI QIDQ5039622

Rushabh Shah, Tanmay Satpathy

Publication date: 30 September 2022

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697688.2022.2057353

zbMATH Keywords

sequential Monte Carlo techniquesparse index tracking problem

Mathematics Subject Classification ID

Numerical methods (including Monte Carlo methods) (91G60) Monte Carlo methods (65C05) Mixed integer programming (90C11) Nonconvex programming, global optimization (90C26) Quadratic programming (90C20) Portfolio theory (91G10)

Cites Work

• Unnamed Item
• Best subset selection via a modern optimization lens
• A hybrid optimization approach to index tracking
• An evolutionary heuristic for the index tracking problem.
• Least angle regression. (With discussion)
• Rejoinder: ``Best subset, forward stepwise or Lasso? Analysis and recommendations based on extensive comparisons
• Differential evolution and combinatorial search for constrained index-tracking
• Mixed-integer programming approaches for index tracking and enhanced indexation
• Exact and heuristic approaches for the index tracking problem with UCITS constraints
• On the stability of sequential Monte Carlo methods in high dimensions
• Following a Moving Target—Monte Carlo Inference for Dynamic Bayesian Models
• An efficient optimization approach for a cardinality-constrained index tracking problem
• Sequential Monte Carlo Samplers
• Sparse Portfolios for High-Dimensional Financial Index Tracking
• Sparse Approximate Solutions to Linear Systems
• The elements of statistical learning. Data mining, inference, and prediction

This page was built for publication: Sparse index tracking using sequential Monte Carlo