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Dynamic Portfolio Optimization for Power Generation Assets

In: Operations Research Proceedings 2012

Author

Listed:
  • B. Glensk

    (School of Business and Economics / E.ON Energy Research Center, RWTH Aachen University)

  • R. Madlener

    (School of Business and Economics / E.ON Energy Research Center, RWTH Aachen University)

Abstract

Markowitz’s classical mean-variance approach for portfolio selection considers only single-period investments. It has, therefore, received very little attention in the context of long-term investment planning. Nevertheless, considering dynamic aspects, already Markowitz [12] mentioned the attractiveness of multi-period portfolio selection problems for portfolio readjustments during the planning horizon. The direct application of the mean-variance model to multi-stage portfolio problems, however, causes many difficulties. A number of studies have tackled such difficulties, providing suggestions on how the dynamic aspects of portfolio optimization should be considered. One of these suggestions is a reallocation methodology that is based on scenario analysis and a tree approach [14]. In this paper, we apply this methodology to power generation assets, in order to capture the continuously changing values of the economic as well as technical parameters considered when evaluating investments in power plants.

Suggested Citation

  • B. Glensk & R. Madlener, 2014. "Dynamic Portfolio Optimization for Power Generation Assets," Operations Research Proceedings, in: Stefan Helber & Michael Breitner & Daniel Rösch & Cornelia Schön & Johann-Matthias Graf von der Schu (ed.), Operations Research Proceedings 2012, edition 127, pages 177-182, Springer.
    • Handle: RePEc:spr:oprchp:978-3-319-00795-3_26
    DOI: 10.1007/978-3-319-00795-3_26
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