Computational Economics

, Volume 53, Issue 2, pp 783–816 | Cite as

Tail-Related Risk Measurement and Forecasting in Equity Markets

  • Stelios BekirosEmail author
  • Nikolaos Loukeris
  • Iordanis Eleftheriadis
  • Christos Avdoulas


Parametric, simulation-based and hybrid methods are utilized to estimate various risk measures such as Value-at-Risk (VaR), Conditional VaR and coherent Expected Shortfall. An exhaustive backtesting analysis is performed for London’s FTSE 100 index and a comparative evaluation of the predictability of the investigated models is performed with the use of various statistical tests. We show that optimal tail risk forecasting necessitates that many factors be considered such as asset structure and capitalization and specific market conditions i.e., normal or crisis periods. Specifically, for large capitalization stocks and long investment horizons parametric modeling accounted for relatively better risk estimation in normal quantiles, whilst for short-term trading strategies, the non-parametric methods are more suitable for measuring extreme tail risk of small-cap stocks.


Risk measurement Expected shortfall Forecast evaluation 

JEL Classification

G12 G21 G24 G31 G33 


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of EconomicsEuropean University Institute (EUI)FlorenceItaly
  2. 2.IPAG Business SchoolParisFrance
  3. 3.Department of Business AdministrationUniversity of MacedoniaThessaloníkiGreece
  4. 4.University of Maryland, EuropeAdelphiUSA
  5. 5.Department of Accounting and FinanceAthens University of Economics and BusinessAthensGreece

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