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Multivariate constrained robust M‐regression for shaping forward curves in electricity markets

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  • Peter Leoni
  • Pieter Segaert
  • Sven Serneels
  • Tim Verdonck

Abstract

In this paper, a multivariate constrained robust M‐regression method is developed to estimate shaping coefficients for electricity forward prices. An important benefit of the new method is that model arbitrage can be ruled out at an elementary level, as all shaping coefficients are treated simultaneously. Moreover, the new method is robust to outliers, such that the provided results are stable and not sensitive to isolated sparks or dips in the market. An efficient algorithm is presented to estimate all shaping coefficients at a low computational cost. To illustrate its good performance, the method is applied to German electricity prices.

Suggested Citation

  • Peter Leoni & Pieter Segaert & Sven Serneels & Tim Verdonck, 2018. "Multivariate constrained robust M‐regression for shaping forward curves in electricity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1391-1406, November.
    • Handle: RePEc:wly:jfutmk:v:38:y:2018:i:11:p:1391-1406
    DOI: 10.1002/fut.21958
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    References listed on IDEAS

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    5. Willems, Gert & Van Aelst, Stefan, 2005. "Fast and robust bootstrap for LTS," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 703-715, April.
    6. Koller, Manuel & Stahel, Werner A., 2011. "Sharpening Wald-type inference in robust regression for small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2504-2515, August.
    7. Helyette Geman, 2005. "Commodities and Commodity Derivatives. Modeling and Pricing for Agriculturals, Metals and Energy," Post-Print halshs-00144182, HAL.
    8. repec:dau:papers:123456789/607 is not listed on IDEAS
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    Cited by:

    1. Filzmoser, P. & Höppner, S. & Ortner, I. & Serneels, S. & Verdonck, T., 2020. "Cellwise robust M regression," Computational Statistics & Data Analysis, Elsevier, vol. 147(C).

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