lCARE - localizing Conditional AutoRegressive Expectiles

  • We account for time-varying parameters in the conditional expectile based value at risk (EVaR) model. EVaR appears more sensitive to the magnitude of portfolio losses compared to the quantile-based Value at Risk (QVaR), nevertheless, by fitting the models over relatively long ad-hoc fixed time intervals, research ignores the potential time-varying parameter properties. Our work focuses on this issue by exploiting the local parametric approach in quantifying tail risk dynamics. By achieving a balance between parameter variability and modelling bias, one can safely fit a parametric expectile model over a stable interval of homogeneity. Empirical evidence at three stock markets from 2005- 2014 shows that the parameter homogeneity interval lengths account for approximately 1-6 months of daily observations. Our method outperforms models with one-year fixed intervals, as well as quantile based candidates while employing a time invariant portfolio protection (TIPP) strategy for the DAX portfolio. The tail risk measure implied byWe account for time-varying parameters in the conditional expectile based value at risk (EVaR) model. EVaR appears more sensitive to the magnitude of portfolio losses compared to the quantile-based Value at Risk (QVaR), nevertheless, by fitting the models over relatively long ad-hoc fixed time intervals, research ignores the potential time-varying parameter properties. Our work focuses on this issue by exploiting the local parametric approach in quantifying tail risk dynamics. By achieving a balance between parameter variability and modelling bias, one can safely fit a parametric expectile model over a stable interval of homogeneity. Empirical evidence at three stock markets from 2005- 2014 shows that the parameter homogeneity interval lengths account for approximately 1-6 months of daily observations. Our method outperforms models with one-year fixed intervals, as well as quantile based candidates while employing a time invariant portfolio protection (TIPP) strategy for the DAX portfolio. The tail risk measure implied by our model finally provides valuable insights for asset allocation and portfolio insurance.show moreshow less

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Metadaten
Author: Xiu Xu, Andrija Mihoci, Wolfgang Karl Härdle
URL:https://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2015-052.pdf
Publisher:SFB 649
Place of publication:Berlin
Document Type:Report
Language:English
Year of publication:2015
Tag:Expectiles; Local Parametric Approach; Risk Management; Tail Risk
Number of pages:32
Series ; volume number:SFB 649 Discussion Paper ; 2015,052
Faculty/Chair:Fakultät 5 Wirtschaft, Recht und Gesellschaft / FG Wirtschaftsstatistik und Ökonometrie
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