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Forecasting Asian Credit Default Swap Spreads: A Comparison of Multi-regime Models

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Robustness in Econometrics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 692))

Abstract

This paper aims to explore the best forecasting model for predicting the Credit Default Swap (CDS) index spreads in emerging markets Asia by comparing the forecasting performance between the multi-regime models. We apply threshold, Markov switching, Markov switching GARCH and simple least squares for structural and autoregressive modeling. Both in- and out-of-sample forecasts are conducted to compare the forecasting performance between models. The results suggest that Markov switching GARCH(1,1) structural model presents the best performance in predicting Asian Credit Default Swap (CDS) index spreads. We also check the preciseness of our selected model by employing the robustness test.

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Author information

Authors and Affiliations

  1. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Chatchai Khiewngamdee, Woraphon Yamaka & Songsak Sriboonchitta

Authors
  1. Chatchai Khiewngamdee
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  2. Woraphon Yamaka
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  3. Songsak Sriboonchitta
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Corresponding author

Correspondence to Chatchai Khiewngamdee .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso Department of Computer Science, El Paso, TX, USA

    Vladik Kreinovich

  2. Faculty of Economics, Chiang Mai University Faculty of Economics, Chiang Mai, Thailand

    Songsak Sriboonchitta

  3. Japan Adv. Inst. of Sci. & Tech. (JAIST) , Ishikawa, Japan

    Van-Nam Huynh

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Khiewngamdee, C., Yamaka, W., Sriboonchitta, S. (2017). Forecasting Asian Credit Default Swap Spreads: A Comparison of Multi-regime Models. In: Kreinovich, V., Sriboonchitta, S., Huynh, VN. (eds) Robustness in Econometrics. Studies in Computational Intelligence, vol 692. Springer, Cham. https://doi.org/10.1007/978-3-319-50742-2_28

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  • DOI: https://doi.org/10.1007/978-3-319-50742-2_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50741-5

  • Online ISBN: 978-3-319-50742-2

  • eBook Packages: EngineeringEngineering (R0)

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