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    Exchangeability, extreme returns and Value-at-Risk forecasts

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    Authors
    Huang, Chun-Kai
    North, D.
    Zewotir, T.
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    Huang, C. and North, D. and Zewotir, T. 2017. Exchangeability, extreme returns and Value-at-Risk forecasts. Physica A: Statistical Mechanics and Its Applications. 477: pp. 204-216.
    Source Title
    Physica A: Statistical Mechanics and Its Applications
    DOI
    10.1016/j.physa.2017.02.080
    ISSN
    0378-4371
    URI
    http://hdl.handle.net/20.500.11937/67319
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, we propose a new approach to extreme value modelling for the forecasting of Value-at-Risk (VaR). In particular, the block maxima and the peaks-over-threshold methods are generalised to exchangeable random sequences. This caters for the dependencies, such as serial autocorrelation, of financial returns observed empirically. In addition, this approach allows for parameter variations within each VaR estimation window. Empirical prior distributions of the extreme value parameters are attained by using resampling procedures. We compare the results of our VaR forecasts to that of the unconditional extreme value theory (EVT) approach and the conditional GARCH-EVT model for robust conclusions.

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