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Value at Risk (VaR). Empirical parametric models and evaluation

Αξία σε κίνδυνο (VaR). Εμπειρικά παραμετρικά υποδείγματα και αποτίμησή τους

Value at Risk (VaR). Empirical parametric models and evaluation

Abstract

We compare the performance of two parametric methods with one non parametric for day-to-day Value-at-Risk models for 63 stocks traded in NYSE or NASDAQ for three different sample sizes and two significance levels. We find that Historical Simulation is more accurate, but also more dependent on its past VaR violations than GARCH and Variance Covariance model.

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Greece
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Keywords

GARCH, 330, 332.6, Variance-covariance, Kupiec’s unconditional coverage test, Historical simulation, Έλεγχος ανεξαρτησίας του Christoffersen, Μήτρα διακύμανσης-συνδιακύμανσης, Christoffersen’s independence test, Μεικτός έλεγχος του Christoffersen, Christoffersen’s joint test, Έλεγχος του Kupiec, Έλεγχος ανεξαρτησίας του Haas, Μεικτός έλεγχος του Kupiec, Mixed Kupiec test, Independence test by Haas, Ιστορική προσομοίωση

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green