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Paper / 2023SMQ / 213328095757476
Sparse Index Tracking: Simultaneous Asset Selection and Capital Allocation via $\ell_0$-Constrained Portfolio
Eisuke Yamagata / Shunsuke Ono
numerical methods / optimizationResource overview

Sparse Index Tracking: Simultaneous Asset Selection and Capital Allocation via $\ell_0$-Constrained Portfolio

Paper2023

by Eisuke Yamagata, Shunsuke Ono

Tags
numerical methodsoptimizationportfolio managementportfolio optimization

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Suggested foundations for portfolio construction and optimisation and numerical methods. Specialist prerequisites vary by paper.

Before you read

  1. Eigenvalues and Covariance Matrices

    Understand the covariance structure of portfolio risk.

  2. Constrained and Convex Optimisation

    Identify the objective, constraints and conditions for an optimum.

  3. Vectors, Matrices and Linear Systems

    Read the linear algebra used to define a numerical problem.

Go further

  1. Mean-Variance Optimisation

    Construct allocations and examine sensitivity to estimated inputs.

  2. Portfolio Constraints

    Turn mathematical weights into feasible portfolio decisions.

  3. Calibration as an Inverse Problem

    Understand identifiability and fitted model parameters.

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