Large data sets in finance with millions of observations have becomewidely available. Such data sets enable the construction of reliablesemi-parametric estimates of the risk associated with extreme pricemovements. Our approach is based on semi-parametric statisticalextreme value analysis, and...

Large data sets in finance with millions of observations have becomewidely available. Such data sets enable the construction of reliablesemi-parametric estimates of the risk associated with extreme pricemovements. Our approach is based on semi-parametric statisticalextreme value analysis, and...

Large data sets in finance with millions of observations have becomewidely available. Such data sets enable the construction of reliablesemi-parametric estimates of the risk associated with extreme pricemovements. Our approach is based on semi-parametric statisticalextreme value analysis, and...

Die risikoneutrale Verteilung von Renditen, wie sie von S&P 500 Optionen impliziert wird, ist ein seit Jahren beliebtes Forschungsthema in den Finanzwissenschaften. Durch ihre vorausschauende Eigenschaft liefert diese Verteilung und im Speziellen ihre Momente, wertvolle Einsichten in die...

Economic problems such as large claims analysis in insurance and value-at-risk in finance, requireassessment of the probability P of extreme realizations Q. This paper provided a semi-parametricmethod for estimation of extreme (P, Q) combinations for data with heavy tails. We solve the...

Economic problems such as large claims analysis in insurance and value-at-risk in finance, requireassessment of the probability P of extreme realizations Q. This paper provided a semi-parametricmethod for estimation of extreme (P, Q) combinations for data with heavy tails. We solve the...

Economic problems such as large claims analysis in insurance and value-at-risk in finance, require assessment of the probability P of extreme realizations Q. This paper provided a semi-parametric method for estimation of extreme (P, Q) combinations for data with heavy tails. We solve the long...

Economic problems such as large claims analysis in insurance and value-at-risk in finance, requireassessment of the probability P of extreme realizations Q. This paper provided a semi-parametricmethod for estimation of extreme (P, Q) combinations for data with heavy tails. We solve the...

In this study, we propose the use of Heterogeneous Autoregressive (HAR) type realized volatility models in combination with the Extreme Value Theory (EVT) method for Value-at-Risk (VaR) forecasting. The proposed model accounts for the long memory property of the realized volatility and the fat...