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Geometric insights into robust portfolio construction
Lara Dalmeyer / Tim Gebbie
optimization / portfolio optimizationResource overview

Geometric insights into robust portfolio construction

Paper2021

by Lara Dalmeyer, Tim Gebbie

Tags
optimizationportfolio optimization

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Understand this paper

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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Explore Portfolio Theory and Quantitative Investment Explore Linear Algebra, Optimisation and Numerical Methods

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