Vorlesen

Research Seminar Series in Statistics and Mathematics

Wirtschaftsuniversität Wien, Departments 4 D4.4.00809:00 - 10:15

Art Vortrag/Diskussion
SpracheEnglish
Vortragende/rWalter Farkas (Department of Banking and Finance, University of Zurich)
Veranstalter Institut für Statistik und Mathematik
Kontakt katrin.artner@wu.ac.at

Walter Farkas (Depart­ment of Banking and Finance, Univer­sity of Zurich) about "Intrinsic Risk Measures"

The Insti­tute for Statis­tics and Mathe­ma­tics (Depart­ment of Finance, Accoun­ting and Statis­tics) cordi­ally invites ever­yone inte­rested to attend the talks in our Rese­arch Seminar Series, where inter­na­tio­nally renowned scho­lars from leading univer­si­ties present and discuss their (working) papers.

The list of talks for the winter term 2018/19 is avail­able via the follo­wing link:
https://www.wu.ac.at/en/stat­math/resse­minar

Abstract:
Mone­tary risk measures clas­sify a finan­cial posi­tion by the minimal amount of external capital that must be added to the posi­tion to make it accep­table. We propose a new concept: intrinsic risk measures. The defi­ni­tion via external capital is avoided and only internal resources appear. An intrinsic risk measure is defined by the smal­lest percen­tage of the currently held finan­cial posi­tion which has to be sold and reinvested in an eligible asset such that the resul­ting posi­tion becomes accep­table. We show that this approach requires less nominal invest­ment in the eligible asset to reach accep­ta­bi­lity. It provides a more direct path from unac­cep­table posi­tions towards the accep­tance set and imple­ments desired proper­ties such as mono­to­ni­city and quasi-­con­ve­xity solely through the struc­ture of the accep­tance set. We derive a repre­sen­ta­tion on cones and a dual repre­sen­ta­tion on convex accep­tance sets and we detail the connec­tions of intrinsic risk measures to their mone­tary coun­ter­parts.

Kindly note that on October 12 two talks are sche­duled at our insti­tute:
9:00  Walter Farkas
10:30  Torsten Hothorn



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