The con­fer­ence is go­ing to take place at Eötvös Loránd Uni­ver­sity, Bu­dapest, Hun­gary Pázmány Péter Sétány 1/​A, Har­mony Hall.

Keynote speaker:

Clau­dia Klüp­pel­berg (TU Mu­nich)

In­vited speak­ers:

  • Chen Zhou (De Ned­er­land­sche Bank and Eras­mus Uni­ver­sity of Rot­ter­dam)
  • Carlo Acerbi (Banque Pictet & Cie)

Clau­dia Klüp­pel­berg (TU Mu­nich)

Mod­el­ling risk in an agent-ob­ject mar­ket by a ran­dom bi­par­tite graph struc­ture

We in­tro­duce a ran­dom net­work model for busi­ness re­la­tion­ships as for in­stance an in­sur­ance mar­ket, over­lap­ping port­fo­lios, or Op­er­a­tional Risk. Us­ing Pareto-tailed losses (as are ob­served for large risks) with a de­pen­dence struc­ture in­tro­duced by the graph we study sys­temic risk mea­sures, which are based on the Value-at-Risk and the Ex­pected Short­fall. We show that the de­pen­dence on the net­work struc­ture plays a fun­da­men­tal role for the in­di­vid­ual agen­t’s risk as well as for the mar­ket risk. The fo­cus of our analy­sis lies in the study of the in­flu­ence of the ran­dom graph on risk mea­sures, where we con­sider the Bernoulli graph and a Rasch-type graph as ex­am­ples. In par­tic­u­lar, we ex­plain the in­flu­ence of the net­work struc­ture on di­ver­si­fi­ca­tion in such mod­els. This is joint work with Oliver Kley and Ge­sine Rein­ert.

Chen Zhou (De Ned­er­land­sche Bank and Eras­mus Uni­ver­sity of Rot­ter­dam)

Why risk is so hard to mea­sure?

This pa­per an­a­lyzes the re­li­a­bil­ity of stan­dard ap­proaches for fi­nan­cial risk analy­sis. We fo­cus on the dif­fer­ence be­tween Value-at-Risk and ex­pected short­fall, their small sam­ple prop­er­ties, the scope for un­der­re­port­ing risk and how es­ti­ma­tion can be im­proved. Over­all, we find that risk fore­casts are ex­tremely un­cer­tain at low sam­ple sizes, with Value-at-Risk more ac­cu­rate than ex­pected short­fall. Value-at-Risk is eas­ily de­lib­er­ately un­der­re­ported with­out vi­o­lat­ing reg­u­la­tions and con­trol mech­a­nisms. Fi­nally, we dis­cuss the im­pli­ca­tions for aca­d­e­mic re­search, prac­ti­tion­ers and reg­u­la­tors, along with best prac­tice sug­ges­tions.

Carlo Acerbi (Banque Pictet & Cie)

A new game the­o­ret­i­cal per­spec­tive on Risk At­tri­bu­tion and Per­for­mance At­tri­bu­tion

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Pro­gram com­mit­tee:

  • L. Márkus (chair),
  • N.M. Arató,
  • J. Gáll,
  • Gy. Michalet­zky,
  • G. Mol­nár-Sáska,
  • V. Prokaj,
  • M. Rá­sonyi

Lo­cal or­gan­is­ers:

  • A. Zem­pléni (chair),
  • Á. Back­hausz,
  • V. Csiszár


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