An open-source implementation of the critical-line algorithm for portfolio optimization
type: Item
instance of: scholarly article
title: An open-source implementation of the critical-line algorithm for portfolio optimization
zbMATH Open document ID: 1461.91266
author: D. H. Bailey
author: Marcos López de Prado
published in: Algorithms
publication date: 2019-03-26T00:00:00Z
review text: Summary: Portfolio optimization is one of the problems most frequently encountered by financial practitioners. The main goal of this paper is to fill a gap in the literature by providing a well-documented, step-by-step open-source implementation of \textit{Critical Line Algorithm} (CLA) in scientific language. The code is implemented as a Python class object, which allows it to be imported like any other Python module, and integrated seamlessly with pre-existing code. We discuss the logic behind CLA following the algorithm's decision flow. In addition, we developed several utilities that support finding answers to recurrent practical problems. We believe this publication will offer a better alternative to financial practitioners, many of whom are currently relying on generic-purpose optimizers which often deliver suboptimal solutions. The source code discussed in this paper can be downloaded at the authors' websites (see Appendix).
Mathematics Subject Classification ID: 91G10
Mathematics Subject Classification ID: 91G60
Mathematics Subject Classification ID: 90C20
zbMATH DE Number: 7042157
zbMATH Keywords: portfolio selection
zbMATH Keywords: quadratic programming
zbMATH Keywords: portfolio optimization
zbMATH Keywords: constrained efficient frontier
zbMATH Keywords: turning point
zbMATH Keywords: Kuhn-Tucker conditions
zbMATH Keywords: risk aversion
Wikidata QID: Q114938032
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/a6010169
OpenAlex ID: W3124796278
cites work: The Simplex Method for Quadratic Programming
cites work: Risk and asset allocation.
cites work: Q5521146
cites work: Sequential Minimax Search for a Maximum
DOI: 10.3390/A6010169
describes a project that uses: Python
description: scientific article; zbMATH DE number 7042157