Genetic Mimicking Portfolios for ETF Arbitrage

Financial markets are full of securities whose price depends on other securities that are often difficult to trade. We develop a method to identify a liquid mimicking portfolio that tracks a de facto non-tradable asset. Our method combines a genetic algorithm with non-negative least squares. We apply it to the corporate ETF market. An arbitrage portfolio that takes a short position in the ETF with the highest price relative to its net asset value and a long position in the mimicking portfolio generates a Sharpe ratio of 3. The return on the mimicking portfolio correlates negatively with the return on the short position, is responsible for about one-third of the Sharpe ratio, and reduces expected tail loss by two-thirds.

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Publication Details

Journal
The Journal of Fixed Income
Published
2026-02-14
DOI
https://doi.org/10.3905/jfi.2026.1.225
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
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article

Genetic Mimicking Portfolios for ETF Arbitrage

Niek Stevens, Åvald Åslaugson Sommervoll, Dag Einar Sommervoll, Julio A. Crego et al.
The Journal of Fixed Income
Stock Market Forecasting Methods
article

Genetic Mimicking Portfolios for ETF Arbitrage

Niek Stevens, Åvald Åslaugson Sommervoll, Dag Einar Sommervoll, Julio A. Crego, Jens Soerlie Kvaerner
article en

Abstract

Financial markets are full of securities whose price depends on other securities that are often difficult to trade. We develop a method to identify a liquid mimicking portfolio that tracks a de facto non-tradable asset. Our method combines a genetic algorithm with non-negative least squares. We apply it to the corporate ETF market. An arbitrage portfolio that takes a short position in the ETF with the highest price relative to its net asset value and a long position in the mimicking portfolio generates a Sharpe ratio of 3. The return on the mimicking portfolio correlates negatively with the return on the short position, is responsible for about one-third of the Sharpe ratio, and reduces expected tail loss by two-thirds.

The Journal of Fixed Income
BI Norwegian Business School (NO), OsloMet – Oslo Metropolitan University (NO), Norwegian University of Science and Technology (NO), Business Roundtable (US), Norwegian University of Life Sciences (NO), Universidade Nova de Lisboa (PT)
Openalex Percentile: Top 60%
Stock Market Forecasting Methods
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