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Multi-Agent Stochastic Simulation for the Electricity Spot Market Price

In: Emergent Results of Artificial Economics

Author

Listed:
  • Matylda Jabłońska

    (Lappeenranta University of Technology)

  • Tuomo Kauranne

    (Lappeenranta University of Technology)

Abstract

The Great Recession of 2008-2009 has dented public confidence in econometrics quite significantly, as few econometric models were able to predict it. Since then, many economists have turned to looking at the psychology of markets in more detail. While some see these events as a sign that economics is an art, rather than a science, multi-agent modelling represents a compromise between these two worlds. In this article, we try to reintroduce stochastic processes to the heart of econometrics, but now equipped with the capability of simulating human emotions. This is done by representing several of Keynes’ Animal Spirits with terms in ensemble methods for stochastic differerential equations. These terms are derived from similarities between fluid dynamics and collective market behavior. As our test market, we use the price series of the Nordic electricity spot market Nordpool.

Suggested Citation

  • Matylda Jabłońska & Tuomo Kauranne, 2011. "Multi-Agent Stochastic Simulation for the Electricity Spot Market Price," Lecture Notes in Economics and Mathematical Systems, in: Sjoukje Osinga & Gert Jan Hofstede & Tim Verwaart (ed.), Emergent Results of Artificial Economics, pages 3-14, Springer.
    • Handle: RePEc:spr:lnechp:978-3-642-21108-9_1
    DOI: 10.1007/978-3-642-21108-9_1
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    Citations

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    Cited by:

    1. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    2. Kolb, Sebastian & Dillig, Marius & Plankenbühler, Thomas & Karl, Jürgen, 2020. "The impact of renewables on electricity prices in Germany - An update for the years 2014–2018," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    3. Jabłońska-Sabuka, Matylda & Sitarz, Robert & Kraslawski, Andrzej, 2014. "Forecasting research trends using population dynamics model with Burgers’ type interaction," Journal of Informetrics, Elsevier, vol. 8(1), pages 111-122.

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