Assessing financial risk with extreme value theory: US financial indemnity loss data analysis

In this paper, we presented a financial analysis of the values of financial losses for real data in light of a set of indicators for measuring financial risks. The value-at-risk (VAR), tail mean–variance (TMV), tail-VAR (TVAR), tail variance (TV), Peaks Over a Random Threshold Value-at-Risk (PORT-VA...

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Veröffentlicht in:Alexandria engineering journal 2024-10, Vol.105, p.496-507
1. Verfasser: Aljadani, Abdussalam
Format: Artikel
Sprache:eng
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Zusammenfassung:In this paper, we presented a financial analysis of the values of financial losses for real data in light of a set of indicators for measuring financial risks. The value-at-risk (VAR), tail mean–variance (TMV), tail-VAR (TVAR), tail variance (TV), Peaks Over a Random Threshold Value-at-Risk (PORT-VAR) and the mean of order P (MOOP) indicators are used in identifying and describing important events or outliers within US financial indemnity loss data. Some extreme financial value theory (EFVT) models are compared in view of financial indemnity loss data and according to some confidence levels. The paper provided a clear financial framework for financial institutions to help them avoid large, sudden losses. Therefore, financial data with a long tail to the right were chosen, and several financial risk measures were used that study and analyze the behavior of the long tail.
ISSN:1110-0168
DOI:10.1016/j.aej.2024.08.006