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<p>The purpose of this thesis is to test the risk-measure Value-at-Riskand techniques for calculating it on data from the Financial Crisis of2007–2010. Different “pre-Financial Crisis” approaches to calculatingValue-at-Risk are considered, and tested on data from the period ofthe Financial Crisis. Also combinations of different approaches aretested.</p><p>Estimation of Value-at-Risk is done using the two different frame-works: Historical simulation (regular and the Hybrid approach) andparametric (conditional heteroscedastic) models.</p><p>The conditional heteroscedastic models considered are the EGARCHand the APARCH, calibrated using QMLE-methods. They are applied to the normal and Student’s t-distributions, Generalized ErrorDistribution and a non-parametric distribution. Consequently, a semi-parametric approach consisting of a non-parametric distribution alongwith an ARCH model is considered.</p><p>Quantile regression as by Koenker (1978) is used for the parameterestimation of the Historical simulation models used.</p><p>The Value-at Risk models are validated using Christoffersen’s con-ditional coverage test.Four stock indices (NIKKEI 225, NASDAQ 100, FTSE 100 andISEQ-overall) are evaluated, selected based on location and the re-gional effect of the Financial Crisis. Models are calibrated based ondata from before the Financial Crisis of 2007–2010, as the crisis isknown at present (April 2010).</p><p>It is found that the present approach to Value-at-Risk estimationcan not be considered redundant due to the extreme events of theFinancial Crisis.</p>