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Markov Switching Predictors Under Asymmetric Loss Functions

In: Mathematical and Statistical Methods for Actuarial Sciences and Finance

Author

Listed:
  • Francesco Giordano

    (University of Salerno)

  • Marcella Niglio

    (University of Salerno)

Abstract

There is empirical evidence that in economic and financial domains the forecast generation is often based on asymmetric losses that allow to differently treat positive and negative forecasts errors. It has led to the introduction of predictors that differently consider the cost related to the over and underprediction. It this context we focus the attention on the generation of forecasts from nonlinear Markov Switching models using the asymmetric LinEx loss function. After the presentation of the model, we introduce an asymmetric LinEx predictor for a well defined variant of Markov Switching structure, generalizing some results given in the literature and focusing the attention on the theoretical formulation of the predictor and on the properties mainly related to its bias. These results are illustrated in an example that gives evidence of some features of the new predictor.

Suggested Citation

  • Francesco Giordano & Marcella Niglio, 2021. "Markov Switching Predictors Under Asymmetric Loss Functions," Springer Books, in: Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 251-256, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-78965-7_37
    DOI: 10.1007/978-3-030-78965-7_37
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