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Backtesting Value-at-Risk and expected shortfall: an empirical comparison using non-parametric and parametric models

Author

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  • Mo Zheng
  • Han-Suck Song
  • Fredrik Armerin

Abstract

The Swedish real estate sector index services as a guideline and general indicator of the performance of the real estate industry, events such global financial crisis, the European debt crisis cause unprecedentedly high uncertainty and volatility. There is a need to understand and search for an appropriate method to deal with Value-at-risk and expected shortfall which comprehensively covers unconditional and conditional risk models with various estimation window and significance level. In this paper, we apply nonparametric, parametric and semiparametric methods such as historical simulation and filtered historical simulation; RiskMetrics; GARCH-type models and GARCH together with extreme value theory. The result is still in process, the draft paper will be submitted within the deadline.

Suggested Citation

  • Mo Zheng & Han-Suck Song & Fredrik Armerin, 2019. "Backtesting Value-at-Risk and expected shortfall: an empirical comparison using non-parametric and parametric models," ERES eres2019_366, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2019_366
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    More about this item

    Keywords

    Expected Shortfall; Extreme Value Theory; Risk Management; Swedish Real Estate Sector; Value-at-Risk;
    All these keywords.

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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