What question did this study set out to answer?

The research aims to explore how genetic algorithms can create mimicking portfolios for ETF arbitrage.

April 10, 2026

Snapshots of Genetic Mimicking Portfolios for ETF Arbitrage

Key Points

The research aims to explore how genetic algorithms can create mimicking portfolios for ETF arbitrage.
Utilized genetic algorithms to develop liquid ETF mimicking portfolios.
Applied nonnegative least squares for portfolio construction.
Focused on tracking NAVs of illiquid corporate bond ETFs.
The approach supports successful ETF arbitrage strategies.
Tail risk is reduced through effective portfolio construction.
Risk-adjusted returns are improved compared to direct trading of underlying bonds.

Abstract

Quickly apply original, key PMR-published papers with Snapshots—a short article companion that distills PMR research into compressed, digestible takeaways, so you can put the paper’s core ideas to work in your investment process—fast. This Snapshot is based on an article about using genetic algorithms and nonnegative least squares to build liquid ETF mimicking portfolios that track illiquid corporate bond ETFs’ NAVs. It shows how this approach can support ETF arbitrage, reduce tail risk, and improve risk-adjusted returns without trading underlying bonds directly.

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Derived from original PMR research written by Julio A. Crego, Jens Soerlie Kvaerner, Åvald Åslaugson Sommervoll, Dag Einar Sommervoll, and Niek Stevens using AI and an editor

Snapshots of Genetic Mimicking Portfolios for ETF Arbitrage

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