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Math. Fi­nan­ce Se­mi­nar (Win­ter­se­mes­ter 2020/2021)

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.

11. No­vem­ber 2020 (Zeit: 17-18 Uhr und 18-19 Uhr, Ort: ON­LINE):

Max Rep­pen (Bos­ton Uni­ver­si­ty)

Titel: Dis­cre­te di­vi­dends in con­ti­nuous time: ran­dom pro­fi­ta­bi­li­ty

Abs­tract: Op­ti­mal di­vi­dend pro­blems are con­cer­ned with op­ti­mi­zing the di­vi­dends of a firm until the time at which its as­sets are ex­hausted (so-​called ruin/bank­rupt­cy). These pro­blems de­ri­ve from ruin theo­ry in ac­tua­ri­al sci­ence, but have gai­ned in­te­rest in cor­po­ra­te fi­nan­ce as a means for un­der­stan­ding ca­pi­tal al­lo­ca­ti­on and firm va­lua­ti­on. We study a di­vi­dend pro­blem in which the pro­fi­ta­bi­li­ty of the firm is dri­ven by a ran­dom pro­cess and the firm has the pos­si­bi­li­ty to issue equi­ty at a fixed or pro­por­tio­nal cost. In the li­te­ra­tu­re, di­vi­dend pro­blems are mo­de­led eit­her in con­ti­nuous time with con­ti­nuous con­trol or in dis­cre­te time. In our case, the di­vi­dend pay­outs are restric­ted to dis­cre­te time, but other con­trol de­cis­i­ons may be cho­sen con­ti­nuous­ly.


Mike Lud­kov­ski (Uni­ver­si­ty of Ca­li­for­nia Santa Bar­ba­ra)

Titel: An Impulse-​-Regime Swit­ching Game Model of Ver­ti­cal Com­pe­ti­ti­on

Abs­tract: I will dis­cuss a new kind of non-​zero-sum sto­chastic dif­fe­ren­ti­al game with mixed im­pul­se/swit­ching con­trols, mo­ti­va­ted by stra­te­gic com­pe­ti­ti­on in com­mo­di­ty mar­kets. A re­p­re­sen­ta­ti­ve upstream firm pro­du­ces a com­mo­di­ty that is used by a re­p­re­sen­ta­ti­ve down­stream firm to pro­du­ce a final con­sump­ti­on good. Both firms can in­flu­ence the price of the com­mo­di­ty. By shut­ting down or in­crea­sing ge­nera­ti­on ca­pa­ci­ties, the upstream firm in­flu­en­ces the price with im­pul­ses. By swit­ching (or not) to a sub­sti­tu­te, the down­stream firm in­flu­en­ces the drift of the com­mo­di­ty price pro­cess. We study the re­sul­ting impulse-​-regime swit­ching game bet­ween the two firms, fo­cu­sing on ex­pli­cit threshold-​type equi­li­bria. Re­mar­kab­ly, this class of games na­tu­ral­ly gives rise to mul­ti­ple Nash equi­li­bria, which we ob­tain via a ve­ri­fi­ca­ti­on based ap­proach. We ex­hi­bit three types of equi­li­bria de­pen­ding on the ul­ti­ma­te  num­ber of swit­ches by the down­stream firm (zero, one or an in­fi­ni­te num­ber of swit­ches). We il­lus­tra­te the di­ver­si­fi­ca­ti­on ef­fect pro­vi­ded by ver­ti­cal in­te­gra­ti­on in the spe­ci­fic case of the crude oil mar­ket. Our ana­ly­sis shows that the di­ver­si­fi­ca­ti­on gains stron­gly de­pend on the pass-​through from the crude price to the ga­so­li­ne price. This is joint work with Rene Aid (Paris Dau­phi­ne), Lu­cia­no Campi (Mila­no) and Li­ang­chen Li (UCSB, JP Mor­gan). 

9. De­zem­ber 2020 (Zeit: 16-17 Uhr und 17-18 Uhr, Ort: ON­LINE):

Giu­lia di Nunno (Uni­ver­si­ty of Oslo)

Title: Sto­chastic con­trol for Vol­ter­ra equa­tions dri­ven by time-​changed noi­ses

Abs­tract: We study a clas­si­cal con­trol pro­blem for non clas­si­cal for­ward dy­na­mics of Vol­ter­ra type dri­ven by time-​changed Levy noi­ses. We con­sider time-​changes that are the abso- lute­ly con­ti­nuous type, thus exi­ting the frame­work of ac­tu­al Levy frame­work. For this we shall con­sider dif­fe­rent in­for­ma­ti­on flows and, when ne­ces­sa­ry, con­sider these flows eit­her as en­lar­ged fil­tra­ti­ons or as par­ti­al in­for­ma­ti­on. Being the sys­tem pos­si­bly non- Mar­ko­vi­an, we prove sto­chastic ma­xi­mum princi­ples of both Pon­trya­gin and Man­gasa­ri­an type. For this we shall study back­ward Vol­ter­ra in­te­gral equa­tions with time-​change. We il­lus­tra­te our re­sults with an ap­p­li­ca­ti­on to mean-​variance port­fo­lio selec­tion.


Jo­han­nes Muhle-​Karbe (Im­pe­ri­al Col­le­ge Lon­don)

Title: Asset Pri­cing with Fric­tions

Abs­tract: We study how equi­li­bri­um asset pri­ces de­pend on “li­qui­di­ty”, that is, the ease with which the as­sets can be tra­ded. This leads to fully-​coupled sys­tems of cou­pled forward-​backward SDEs. This talk out­lines some first well­po­sed­ness re­sults, con­nec­tions to ho­mo­ge­niza­ti­on that lead to the trac­ta­ble ap­pro­xi­ma­ti­ons in the large-​liquidity limit, and a wide range of chal­len­ging open pro­blems in this con­text. 
(Based on joint works (in pro­gress) with Ago­sti­no Cap­po­ni, Lukas Gonon, Mar­tin Her­de­gen, Dylan Pos­sa­mai, Xiao­fei Shi and Chen Yang.)

20.. Ja­nu­ar 2020 (Zeit: 16-17 Uhr und 17-18 Uhr, Ort: ON­LINE):

Mo­gens Stef­fen­sen (Uni­ver­si­ty of Co­pen­ha­gen)

Titel: Epi­pha­nies in Pen­si­on In­vest­ments and Va­lua­ti­on

Abs­tract: We dis­cuss, on a princip­le ra­ther than a tech­ni­cal ground, three in­stances where things are per­haps not the way you thought they were - with po­ten­ti­al im­pact, theo­re­ti­cal­ly or prac­ti­cal­ly. a) In life-​cycle port­fo­lio choice, does one re­al­ly need to take rea­li­zed ca­pi­tal gains into ac­count, or are age-​based in­vest­ment rules doing the job? b) In time-​consistent mean-​variance port­fo­lio op­ti­miza­ti­on, is nor­ma­liza­ti­on of the va­ri­an­ce by cur­rent wealth re­al­ly the 'right' thing to do, or is there a 'bet­ter' nor­ma­liza­ti­on? c) In multi-​state mo­dels fre­quent­ly used in life in­su­ran­ce and credit risk, does there exist such a thing as a set of for­ward tran­si­ti­on rates?


Da­ni­el Bauer (Uni­ver­si­ty of Wisconsin-​Madison)

Titel: Mor­ta­li­ty Risk, In­su­ran­ce, and the Value of Life (with Da­ri­us Lak­da­wal­la and Ju­li­an Reif)

Abs­tract: We de­ve­lop a new frame­work for va­luing health and lon­ge­vi­ty im­pro­vements that de­parts from con­ven­tio­nal but un­rea­listic as­sump­ti­ons of full an­nui­tiza­ti­on and de­ter­mi­nistic health. Our frame­work can value the pre­ven­ti­on of mor­ta­li­ty and of ill­ness, and it can quan­ti­fy the ef­fects of re­ti­re­ment po­li­ci­es on the value of life. We apply the frame­work to life-​cycle data and ge­ne­ra­te new in­sights ab­sent from the con­ven­tio­nal ap­proach. First, tre­at­ment is up to five times more va­lu­a­ble than pre­ven­ti­on, even when both ex­tend life equal­ly. This asym­me­try helps ex­plain low ob­ser­ved in­vest­ment in pre­ven­ti­ve care. Se­cond, se­ve­re ill­ness can si­gni­fi­cant­ly in­crea­se the value of sta­tis­ti­cal life, hel­ping to re­con­ci­le theo­ry with em­pi­ri­cal fin­dings that con­su­mers value life-​extension more in blea­ker health sta­tes. Third, re­ti­re­ment an­nui­ties boost ag­gre­ga­te de­mand for life-​extension. We cal­cu­la­te that So­cial Se­cu­ri­ty adds $10.6 tril­li­on (11 per­cent) to the value of post-​1940 lon­ge­vi­ty gains and would add $127 bil­li­on to the value of a one per­cent de­cli­ne in fu­ture mor­ta­li­ty.

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