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Portfolio Optimization with Irreversible Long-Term Investments in Renewable Energy under Policy Risk: A Mixed-Integer Multistage Stochastic Model and a Moving-Horizon Approach

  • Portfolio optimization is an ongoing hot topic of mathematical optimization and management science. Due to the current financial market environment with low interest rates and volatile stock markets, it is getting more and more important to extend portfolio optimization models by other types of investments than classical assets. In this paper, we present a mixed-integer multistage stochastic model that includes investment opportunities in irreversible and long-term infrastructure projects in the context of renewable energies, which are also subject to policy risk. On realistic time scales for investment problems of this type, the resulting instances are by far too large to be solved with today's most evolved optimization software. Thus, we present a tailored moving-horizon approach together with suitable approximations and simplifications of the model. We evaluate these approximations and simplifications in a computational sensitivity analysis and derive a final model that can be tackled on a realistic instance by our moving-horizon approach.

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Metadaten
Verfasserangaben:Nadine Gatzert, Alexander Martin, Martin Schmidt, Benjamin Seith, Nikolai Vogl
Titel des übergeordneten Werkes (Deutsch):European Journal of Operational Research
Dokumentart:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Veröffentlichung (online):03.07.2019
Datum der Erstveröffentlichung:03.07.2019
Datum der Freischaltung:03.07.2019
Freies Schlagwort / Tag:Illiquid investments; Mixed-integer optimization; Multistage stochastic optimization; Policy risk; Portfolio optimization
Seitenzahl:29
Institute:Friedrich-Alexander-Universität Erlangen-Nürnberg
Universität Trier
Teilprojekte:A05
B07
B08
Lizenz (Deutsch):License LogoCreative Commons - CC BY - Namensnennung 4.0 International