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Math. Fi­nan­ce Se­mi­nar (Som­mer­se­mes­ter 2018)

Das In­sti­tut für Ma­the­ma­ti­sche Wirt­schafts­for­schung ver­an­stal­tet im Rah­men des Bie­le­feld Sto­chastic Af­ter­noon re­gel­mä­ßig Se­mi­na­re zum Thema Fi­nanz­ma­the­ma­tik. Das Pro­gramm des ak­tu­el­len Se­mes­ters fin­den Sie hier.

18. April 2018 (Zeit: 15-16 und 16-17, Ort: V3-​201 und V2-​213):

Max Nen­del (Bie­le­feld Uni­ver­si­ty)

Titel: A se­mi­group ap­proach to non­line­ar Lévy pro­ces­ses

Abs­tract: Non­line­ar ex­pec­ta­ti­ons, as in­tro­du­ced by S. Peng, are clo­se­ly re­la­ted to mo­ne­ta­ry risk me­a­su­res. Non­line­ar ex­pec­ta­ti­ons na­tu­ral­ly ap­pe­ar in the con­text of pri­cing under model un­cer­tain­ty, e.g. drift un­cer­tain­ty (g-​expectation) or vo­la­ti­li­ty un­cer­tain­ty (G-​expectation). In this talk, we de­mons­tra­te how Lévy pro­ces­ses under non­line­ar ex­pec­ta­ti­ons arise from so­lu­ti­ons to cer­tain fully non­line­ar PDEs, where the Knig­thi­an un­cer­tain­ty is in the Lévy triplet. This is done using non­line­ar se­mi­groups and a non­line­ar ver­si­on of Kol­mo­go­rov?s ex­ten­si­on theo­rem. We pro­vi­de a suf­fi­ci­ent con­di­ti­on for fa­mi­lies of Lévy ti­plets that gua­ran­te­es the sol­va­bi­li­ty of the re­la­ted fully non­line­ar par­ti­al integro-​differential equa­ti­on, and show that the so­lu­ti­on ad­mits a re­p­re­sen­ta­ti­on by means of a non­line­ar Lévy pro­cess.


Marco Frit­tel­li (Uni­ver­si­ty of Milan)

Titel: On Fair­ness of Sys­temic Risk Me­a­su­res

Abs­tract:In a pre­vious paper, we­have in­tro­du­ced a ge­ne­ral class of sys­temic risk me­a­su­res that allow ran­dom al­lo­ca­ti­ons to in­di­vi­du­al banks be­fo­re ag­gre­ga­ti­on of their risks. In the pre­sent paper, we ad­dress the ques­ti­on of fair­ness of these al­lo­ca­ti­ons and we pro­po­se a fair al­lo­ca­ti­on of the total risk to in­di­vi­du­al banks. We show that the dual pro­blem of the mi­ni­miza­ti­on pro­blem which iden­ti­fy the sys­temic risk me­a­su­re, pro­vi­des a va­lua­ti­on of the ran­dom al­lo­ca­ti­ons which is fair both from the point of view of the so­cie­ty/re­gu­la­tor and from the in­di­vi­du­al fi­nan­cial in­sti­tu­ti­ons. The case with ex­po­nen­ti­al uti­li­ties which al­lows for ex­pli­cit com­pu­ta­ti­on is trea­ted in de­tails.

25. April 2018 (Zeit: 15-16 und 16-17, Ort: V3-​201):

Hans­pe­ter Schmid­li (Uni­ver­si­ty of Co­lo­gne)

Titel: Op­ti­mal Di­vi­dend and Ca­pi­tal In­jec­tion Pro­blems in Non-​Life In­su­ran­ce

Abs­tract: The tra­di­tio­nal risk me­a­su­re in ac­tua­ri­al ma­the­ma­tics is the ruin pro­ba­bi­li­ty. This con­cept has been cri­ti­cis­ed be­cau­se it does not take into ac­count the time to ruin and the de­fi­cit at ruin. An al­ter­na­ti­ve me­a­su­re has been sug­gested by de Fi­net­ti (1957). He pro­po­sed to con­sider the dis­coun­ted value of di­vi­dends paid from the port­fo­lio. How­e­ver, under the op­ti­mal di­vi­dend stra­te­gy ruin be­co­mes cer­tain. Mo­reo­ver, the de­fi­cit at ruin is not taken into ac­count, eit­her. As an al­ter­na­ti­ve, we allow ca­pi­tal in­jec­tions that have to keep the sur­plus po­si­ti­ve. Ruin is not al­lo­wed in our model. In one model, we me­a­su­re the risk as the value of the (dis­coun­ted) ca­pi­tal in­jec­tions. We look for the rein­su­ran­ce stra­te­gy that mi­ni­mi­ses the value. A se­cond model al­lows also di­vi­dend pay­ments. Here, the value is the dis­coun­ted di­vi­dends minus pe­na­li­sed ca­pi­tal in­jec­tions. We show that the op­ti­mal di­vi­dend stra­te­gy is a bar­ri­er stra­te­gy. Dis­coun­ting in these mo­dels has to be seen as a pre­fe­rence me­a­su­re: di­vi­dends today are pre­fer­red to di­vi­dends to­mor­row and in­jec­tions to­mor­row are pre­fer­red to in­jec­tions today. Since the pa­ra­me­ters of the sur­plus pro­cess are kept con­stant, the new me­a­su­res are also to be con­side­red as tech­ni­cal me­a­su­res used for risk ma­nage­ment. This talk is based on joint work with Julia Ei­sen­berg and Na­ta­lie Scheer.


Peter Gran­dits (TU Wien)

Titel: Some ap­p­li­ca­ti­ons of sto­chastic con­trol for ruin pro­blems in in­su­ran­ce ma­the­ma­tics

Abs­tract: The cal­cu­la­ti­on and esti­ma­ti­on of ruin pro­ba­bi­li­ties is a clas­si­cal theme in in­su­ran­ce ma­the­ma­tics, star­ting pro­ba­b­ly with the ce­le­bra­ted Lund­berg ine­qua­li­ty. We will ge­ne­ra­li­ze the clas­si­cal model in two di­rec­tions. On the one hand, we shall con­sider com­pa­nies, which in­vest in the stock mar­ket, on the other hand two com­pa­nies are con­side­red, which are al­lo­wed­to col­la­bo­ra­te. We want to find esti­ma­tes for the ruin pro­ba­bi­li­ties, re­spec­tive­ly some in­for­ma­ti­on about the op­ti­mal stra­te­gies.

13. Juni 2018 (Zeit: 15-16, Ort: V3-​201):

Marie-​Claire Que­n­ez (Uni­ver­si­ty Paris Di­de­rot)

Titel: Non­line­ar pri­cing of Eu­ropean and Ame­ri­can op­ti­ons in an im­per­fect mar­ket with de­fault

Abs­tract: We study pri­cing and hedging for con­tin­gent claims in an im­per­fect mar­ket model with de­fault, where the im­per­fec­tions are taken into ac­count via the non­linea­ri­ty of the wealth dy­na­mics, ex­pres­sed in terms of a non­line­ar dri­ver g(y; z; k). In this frame­work, the sel­ler?s (resp. buyer?s) pri­cing rule for Eu­ropean op­ti­ons cor­re­sponds to the non­line­ar g-​expectation Eg (resp. ~g-​expectation E~g) 1, in­du­ced by a BSDE with dri­ver g (resp ~g). We also ad­dress the case of op­ti­ons which ge­ne­ra­te in­ter­me­di­a­te cash­flows mo­de­led via an op­tio­nal fi­ni­te va­ria­tio­nal pro­cess. We then study the pri­cing of Ame­ri­can op­ti­ons in this frame­work. The payoff is given by an op­tio­nal ir­re­gu­lar pro­cess (t). We de­fi­ne the sel­ler?s price of the Ame­ri­can op­ti­on as the mi­ni­mum of the in­iti­al ca­pi­tals which allow her/him to build up a su­per­hedging port­fo­lio stra­te­gy '. We also con­sider the buyer?s price, de­fi­ned as the su­pre­mum of the in­iti­al pri­ces which allow the buyer to select an ex­er­ci­se time  and a port­fo­lio stra­te­gy ' so that she/he is su­per­hedged. We prove that the sel­ler?s (resp. buyer?s) price co­in­ci­des with the value func­tion of an Eg-(resp. E~g-) op­ti­mal stop­ping pro­blem, which cor­re­sponds to the so­lu­ti­on of a re­flec­ted BSDE with ob­sta­cle (t) and dri­ver g (resp. ~g). At last, we study the pri­cing of a game op­ti­on with ir­re­gu­lar payoffs. In this case, the sel­ler?s (resp. buyer?s) price is shown to be equal to the value func­tion of an Eg-(resp. E~g-) Dyn­kin game, which co­in­ci­des with the so­lu­ti­on of a non­line­ar dou­bly re­flec­ted BSDEs with dri­ver g (resp. ~g). We also con­sider the case of am­bi­gui­ty on the model.

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