Research Article A Two-Mode Mean-Field Optimal Switching Problem for the Full Balance Sheet

Size: px
Start display at page:

Download "Research Article A Two-Mode Mean-Field Optimal Switching Problem for the Full Balance Sheet"

Transcription

1 Hndaw Publhng Corporaon Inernaonal Journal of Sochac Analy Volume 14 Arcle ID page hp://dx.do.org/1.1155/14/ Reearch Arcle A wo-mode Mean-Feld Opmal Swchng Problem for he Full Balance Shee Boualem Djehche and Al Hamd Deparmen of Mahemac KH-Royal Inue of echnology 1 44 Sockholm Sweden Correpondence hould be addreed o Boualem Djehche; boualem@mah.kh.e Receved February 14; Acceped 4 May 14; Publhed 5 May 14 Academc Edor: Qng Zhang Copyrgh 14 B. Djehche and A. Hamd. h an open acce arcle drbued under he Creave Common Arbuon Lcene whch perm unrerced ue drbuon and reproducon n any medum provded he orgnal work properly ced. We conder he problem of wchng a large number of producon lne beween wo mode hgh producon and low producon. he wchng baed on he opmal expeced prof and co yeld of he repecve producon lne and conder boh de of he balance hee. Furhermore he producon lne are all aumed o be nerconneced hrough a couplng erm whch he average of all opmal expeced yeld. Inuvely h mean ha each ndvdual producon lne compared o he average of all peer whch ac a a benchmark. Due o he complexy of he problem we conder he aggregaed opmal expeced yeld where he couplng erm approxmaed wh he mean of he opmal expeced yeld. h urn he problem no a womode opmal wchng problem of mean-feld ype whch can be decrbed by a yem of Snell envelope where he obacle are nerconneced and nonlnear. he man reul of he paper a proof of a connuou mnmal oluon o he yem of Snell envelope a well a he full characerzaon of he opmal wchng raegy. 1. Inroducon Conder a company wh N dfferen producon lne whch all have wo mode of producon hgh mode and low mode where each mode of producon ha own balance hee of expeced prof and co. For each producon lne j n mode ley +j denoe he opmal expeced prof yeld a me and le he correpondng opmal expeced co yeld be denoed by Y j. Aume ha we wan o wch beween he wo mode of producon eher f he curren mode unprofable or f we can expec beer prof n he oher mode. Aume furher ha he wchng baed on boh de of he balance hee o ha we for example wch f we can expec lower co n he oher mode. hen h problem can be modeled a a wo-mode opmal wchng problem for each producon lne j whchcanbedecrbedbyhe followng yem of Snell envelope: Y +j = e up E [ ψ +j () d + S +j 1 {<} +ξ + 1 {=} F ] Y j = e nf E [ ψ j () d + S j 1 {<} +ξ 1 {=} F ] for each producon lne j = 1...Nwhereψ ±j () are he prof and co rae per un me (he generaor) and where S +1j S +j S 1j S j =(Y +j =(Y +1j =(Y j =(Y 1j l 1 ()) (Y 1j l ()) (Y j +l 1 ()) (Y +1j +l ()) (Y +j a 1 ()) a ()) +b 1 ()) +b ()) are he obacle of he wchng problem. Here ξ ± are he fnal prof and co of each mode a ome fxed me and he funcon l a andb repreen wchng co. (1) ()

2 Inernaonal Journal of Sochac Analy Now aume ha he producon lne all have he ame generaor bu hey are nerconneced hrough a couplng erm.ifhecouplngermheaverageofheprofandco yeld of all he projec N Y ±j j=1 1 (3) N hen h nuvely mean ha each producon lne compared o a benchmark conued of he average of peer. In h cae he correpondng generaor become ψ +j () =ψ + ( Y +j ψ j () =ψ ( Y j N Y +k k=1 1 ) N N Y k k=1 1 ). N Wh h aumpon olvng he yem (1) becomea hghly complex ak for large N ncehesnellenvelope are all nerconneced hrough he couplng erm (3). Bu nead of olvng (1) we can conder he expeced prof andcoyeldonanaggregaedlevelwhereweuehe mean-feld approxmaon EY ± for he couplng erm (3). he correpondng yem of Snell envelope become Y + Y = e up = e nf for =1where E [ E [ ψ + ( Y + EY + )d +S + 1 {<} +ξ + 1 {=} F ] ψ + ( Y EY )d +S 1 {<} +ξ 1 {=} F ] S +1 =(Y + l 1 ()) (Y 1 a 1 ()) S + =(Y +1 l ()) (Y a ()) S 1 =(Y +l 1 ()) (Y +1 +b 1 ()) S =(Y 1 +l ()) (Y + +b ()). In h paper we wll how he exence of a connuou mnmal oluon of h yem. In a forhcomng paper we wll how convergence of he yem (1) o our yem of Snell envelop of mean-feld ype. he e of counerexample derved n [1] can be ued o argue ha unquene may no hold n general. (4) (5) (6) In erm of BSDE he yem equvalen o he followng yem of mean-feld refleced BSDE (MF-RBSDE): =ξ + Y + ψ + ( Y + Z + db =ξ Y ψ ( Y Z db Y + (Y + (S EY + )d+(k + EY )d (K S + Y S S + )dk + = Y )dk =. K+ ) K ) For deal ee for example []. In h paper we conder he followng lghly more general yem of MF-RBSDE: =ξ + Y + ψ + ( Y + Z + db =ξ Y ψ ( Y Z db Y + (Y + (S EY + EY Z + Z S + Y S S + )dk + = Y )dk =. )d+(k + )d (K K+ ) K ) We follow a procedure mlar o he one ued n [1]; ha we ue an ncreang equence of approxmang meanfeld refleced ochac dfferenal equaon (MF-RBSDE) o how he exence of a connuou mnmal oluon of he yem. However due o he added generaly n he problem we have o prove a comparon reul and an upper bound for h ype of MF-RBSDE gven he n-daa. Mean-feld relaed problem have been uded no only n he eng of backward ochac dfferenal equaon bu n many oher feld a well. Example of area where mean-feldapproxmaonhavebeenuccefulncludeacal mechanc quanum mechanc quanum chemry economc fnance and game heory. Recen work nclude for example [3] where he auhor conder he problem (7) (8)

3 Inernaonal Journal of Sochac Analy 3 of ecor-we allocaon n a porfolo conng of a very large number of ock. Anoher paper on mean-feld approxmaon he emnal work by Lary and Lon [4] whch concern applcaon of mean-feld approxmaon o problem n economc and fnance. For an accoun on recen work relaed o our paper we refer o[5] and he reference heren. Backward ochac dfferenal equaon of he meanfeld ype have been uded by everal auhor ncludng [5 8]. o he be of our knowledge he work of Buckdahn e al. [6] he fr paper o ackle h cla of problem. hey udy an equaon of he form Y =ξ+ E f(ω ωy (ω )Z (ω )Y (ω) Z (ω))d Z dw where he mean-feld neracon lnear n he generaor obaned a a mean-feld lm of BSDE equaon drven by SDE of mean-feld ype. h ype of mean-feld backward ochac dfferenal equaon (MF-BSDE) furher uded n [6] where he auhor oban exence and unquene for a general drver under Lpchz condon. Exenon of h work o refleced BSDE nclude [7 8]. he equaon hey udy are of he form Y =ξ+ E f(ω ωy (ω ) +K K Z dw Y S Z (ω )Y (ω) Z (ω))d (Y S )dk =. (9) (1) he auhor prove exence and unquene of he MF- BSDEawellaacomparonheoremunderomeaddonal condon for he generaor. hee reul ealy exend o our cae where he mean-feld neracon of he MF- RBSDE nonlnear n he generaor. For compleene we dplay n he Appendce an adapaon of he proof of [7 8] o our eng. he oulne of h paper a follow. Secon ae he neceary noaon and prelmnare. In Secon 3 we ae andprovehemanreulofhpaper.. Noaon and Prelmnare For he re of he paper we fx a probably pace denoed by (Ω F P) on whch defned a a andard d-dmenonal Brownan moon B = (B ) whoe naural flraon (F := σ{b }).LeF = (F ) be he flraon (F ) compleed wh he P-null e of F. h mple ha F afe he uual condon; ha rgh connuou and complee. For fuure reference we nroduce he followng pace: () P he σ-algebra on [ ] Ω of F-progrevely meaurable procee () M d he e of P-meaurable and R d -valued procee w=(w ) uch ha w M d 1/ := E[ w d] < (11) () S (rep. S c )heeofp-meaurable and càdlàg (rep. connuou) R-valued procee w=(w ) uch ha w S 1/ := E[ up w ] < (1) (v) K (rep. K c ) a ube of S (rep. S c ) on nondecreang càdlàg (rep. connuou) procee (K ) uch ha K =. Le ξ be an F -meaurable L -random varable le f be an R-valued funcon and le S be an F-adaped proce. o reamlne he preenaon of he reul we nroduce he followng noaon. () If here ex a par of procee (Y Z) uch ha Y S (rep. S c ) Z Md Y =ξ+ f(ωy EY Z )d Z db hen we ay ha (13) (Y Z) =F(ξ f) (rep. (Y Z) =F c (ξ f)). (14) () If here ex a rple of procee (YZK)uch ha Y S (rep. S c ) Z Md K K (rep. K c ) Y =ξ+ f(ωy EY Z )d+k K Z db Y S (Y S )dk = hen we ay ha (rep. (Y S )dk =) (15) (Y Z K) =F + (ξ f S) (rep. (Y Z K) =F c + (ξ f S)). (16)

4 4 Inernaonal Journal of Sochac Analy () If here ex a rple of procee (Y Z K) uch ha Y S (rep. S c ) Z Md K K (rep. K c ) Y =ξ+ f(ωy EY Z )d (K K ) Z db Y S (S Y )dk = hen we ay ha (rep. (Y S )dk =) (17) (Y Z K) =F (ξ f S) (rep. (Y Z K) =F c (ξ f S)). (18) hee mean-feld backward ochac dfferenal equaon (MF-BSDE) and mean-feld refleced backward ochac dfferenal equaon (MF-RBSDE) are ad o be andard f he followng condon hold. (H1) he generaor f Lpchz wh repec o (y 1 y z) unformly n ( ω). (H) he proce (f( ω )) F-progrevely meaurable and d dp-quare negrable. (H3) he random varable ξ n L (Ω F P). (H4) he barrer S càdlàg F-adaped and afe and S ξ P-a.. E [ up S+ ]< (19) MoreonMF-BSDEcanbefoundn[5 6]. For furher reference on MF-RBSDE ee [7 8]. Fnally a key ool ued n h paper he noon of he Snell envelope. Le θ denoe he cla of F-oppng me uch ha θfor ome F-oppng me θ. Propoon 1. Le U=(U ) be an F-adaped R-valued càdlàg proce uch ha he e of random varable {U } unformly negrable. hen here ex an F-adaped R- valued càdlàg proce Z:=(Z ) uch ha Z he malle upermarngale whch domnae U.he proce Z called he Snell envelope of U and ha he followng propere. () For any F-oppng me θ hold ha Z θ = e up E [U F θ ] (and hence Z =U ). θ () () he Doob-Meyer decompoon of Z mple he exence of a connuou marngale (M ) and wo nondecreang predcable procee (A ) and (B ) whch are repecvely connuou and purely dconnuou uch ha for all one ha Z =M A B (wh A =B =). (1) () For any {ΔB > } {ΔU <} {Z =U }. () Hence f U only ha pove jump hen Z a connuou proce. (v) If θ an F-oppng me hen θ := nf { θ : Z =U } (3) opmal afer θ;ha Z θ = e up θ E [U F θ ] = E [U θ F θ]=e [Z θ F θ]. (4) For furher reference on he Snell envelope we refer o [9 1]or[11]. We fnally collec reul regardng exence unquene boundandcomparonformf-rbsde.heeareadapaon of reul n [7 8] o our cae. Proof are deferred o he Appendce. Propoon. Le (ξ f S) be ome n-daa whch afe (H1) (H4). hen here ex a unque rple (YZK)whch olve (Y Z K) =F + (ξ f S). (5) Amlarreulholdfor(Y Z K) = F (ξ f S). Proof. See Appendx A. Propoon 3. Le (ξ f S) be a e of daa afyng aumpon (H1) (H4) andle(y Z K) = F ± (ξ f S). hen here ex a conan C uch ha E [ up Y Z d + K ] (6) CE [ξ f ( ) d + up (S + )]. Proof. See Appendx B. Nex we dplay a comparon reul for oluon of (Y Z K) = F + (ξ f S). Amlarreulholdfor(Y Z K) = F (ξ f S). Propoon 4. Le (ξ f S) and (ξ f S ) be wo e of daa each one afyng aumpon (H1) (H4)and le (Y Z K) =F + (ξ f S) (Y Z K )=F + (ξ f S ). If he followng condon hold: (7) () ξ ξ a.. () f( y 1 y z) f ( y 1 y z) dp d-a.e. and (y 1 y z) R R R d

5 Inernaonal Journal of Sochac Analy 5 () S S a.. (v) S and S are connuou (v) aleaoneofhewogeneraorf and f nondecreang n y hen P-a.. Proof. See Appendx C. Y Y (8) Propoon 5. Propoon 4 hold rue even when S=S a.. and S only afe (H4); ha need no be connuou. Proof. See Appendx D. 3. he Syem of MF-RBSDE Conder he followng yem of equaon: for =1where (Y + Z + K + )=F + (ξ + ψ+ S+ ) (Y Z K )=F (ξ ψ S ) S +1 =(Y + l 1 ()) (Y 1 a 1 ()) S + =(Y +1 l ()) (Y a ()) S 1 =(Y +l 1 ()) (Y +1 +b 1 ()) (9) (3) S =(Y 1 +l ()) (Y + +b ()). Furher aume he followng. (A1) ψ ± are Lpchz n (y 1 y z)unformly n ( ω);ha here ex a C > uch ha for any ( ω) [ ] Ω ψ± ( ω y 1 y z) ψ ± (ωy 1 y z) C( y y + z z ). (31) In addon he procee ψ ± () := ψ ± (ω) are F-progrevely meaurable and d dp-quare negrable. (A) he procee (a ( ω)) (b ( ω)) and (l ( ω)) belong o S c. In addon l () > P- a.. (A3) he random varable ξ ± are F -meaurable and quare negrable. Furhermore P-a.. hold ha ξ + 1 (ξ+ l 1 ()) (ξ 1 a 1 ()) ξ + (ξ+ 1 l ()) (ξ a ()) ξ 1 (ξ +l 1 ()) (ξ + 1 +b 1 ()) ξ (ξ 1 +l ()) (ξ + +b ()). (3) (A4) heprocee(b ()) and (l ()) are of Iôype; ha b () =b () l () =l () U () d V () db U d V db (33) where (U U) and (V V) are ome F-progrevely meaurable procee whch are d P-quare negrable. I worh nong a few hng here. Fr he obacle procee a need no be of Iô-ype. Second he e of oluon o he yem (3) nonempy. An example of oluon o e ξ + =ξ =1andle l () =e 4 a () =b () = (34) for =1.LalywhleY + a upermarngale Y a ubmarngale. he aumpon (A4) needed o prove he connuy of he ncreang proce K. h n urn ued o prove connuy of Y whch fnally ued o derve connuy of Y +. heorem 6. Le he generaor n he yem (9) be nondecreangnhehrdargumen;ha y ψ ± ( y 1 y z) = 1 (35) are nondecreang funcon. hen under he aumpon (A1) (A4) he yem (9) adm a mnmal oluon uch ha Y ± = 1 connuou. he oluon mnmal n he ene ha f ( Y ± Z ± K ± ) =1 anoher oluon hen Y ± Y ± a..heoluonoheyem(3) no unque n general. Proof. he heorem proved ung an approxmang cheme. Le and denoe hen (Y + Z + )=F(ξ + ψ+ ) (36) L L =ξ+ ψ + ( Y + EY + := Y+ +b (). (37) Z + )d +b () U () d V () db =L ψ ( L EL Z )d Z db Z + db (38)

6 6 Inernaonal Journal of Sochac Analy where Z := Z+ +V () ψ ( L EL Z ) where := ψ + ( L b () EL Eb () Z V ()) U (). (39) Now le ( Y Z) be he unque oluon o he BSDE Y = Y α(ωy 1 y z) α( Y EY Z )d := (ψ 1 ψ ψ 1 ψ )(ωy 1y z) Z db S (4) Y := (ξ + 1 +b 1 ()) (ξ + +b ()) ξ 1 ξ. By Propoon 4 hold ha Hence (41) Y L =Y+ +b (). (4) Y (Y + +b ()) ( Y +l ()) (43) nce l () > a.. Conder now he procee where (Y 1 Z 1 K 1 )=F ( Y ψ S 1 ) (Y +1 Z +1 K +1 )=F + (ξ + ψ+ S+1 ) S 1 and for n 1 where =(Y + +b ()) ( Y +l ()) S +11 =(Y + l 1 ()) (Y 11 a 1 ()) S +1 =(Y +1 l ()) (Y 1 a ()) (Y n+1 Z n+1 K n+1 )=F (ξ ψ S n+1 ) (Y +n+1 Z +n+1 K +n+1 )=F + (ξ + ψ+ S+n+1 ) S 1n+1 =(Y n +l 1 ()) (Y +1n +b 1 ()) (44) (45) (46) Snce (Y + Z + ) he oluon of a andard MF-BSDE he exence and unquene have been eablhed n [6] and he exence and unquene of he procee (Y 1 Z 1 K 1 ) were eablhed n Propoon. Wh h n mnd ealy hown by he ue of nducon ha for any n 1he rple (Y +n Z +n K +n ) ex are unque and belong o he approprae pace. follow ha Y + Y +1.MoreoverbyPropoon 4 agan follow ha Y Y 1.Hence From Propoon 4 and he fac ha K +1 ( Y +l 1 ()) (Y +1 +b 1 ()) K +1 (Y 1 +l 1 ()) (Y +11 +b 1 ()) ( Y +l ()) (Y + +b ()) Propoon 4 hen yeld Y 1 Now aume ha hen S +1n+1 S +n+1 =(Y +n (Y +n+1 =(Y +1n (Y +1n+1 (Y 11 +l ()) (Y +1 +b ()). Y +n Y n+1 Y. Y +n+1 Y n+. l 1 ()) (Y 1n+1 l 1 ()) (Y 1n+ l ()) (Y n+1 l ()) (Y n+ a 1 ()) (48) (49) a 1 ()) =S +1n+ a ()) a ()) =S +n+ (5) from whch follow by Propoon 4 agan ha Y +n+1.hencealoholdha Y +n+ S 1n+ S n+ =(Y n+1 (Y n+ =(Y 1n+1 (Y 1n+ +l 1 ()) (Y +1n+1 +l 1 ()) (Y +1n+ +l ()) (Y +n+1 +l ()) (Y +n+ Y n+3.bynduc- hu Propoon 4 yeld ha Y n+ on +b 1 ()) +b 1 ()) =S 1n+3 +b ()) +b ()) =S n+3. (51) S n+1 S +1n+1 =(Y 1n =(Y +n +l ()) (Y +n l 1 ()) (Y 1n+1 +b ()) a 1 ()) (47) Y +n Y n+1 Y +n+1 Y n+ (5) S +n+1 =(Y +1n l ()) (Y n+1 a ()). for n 1.

7 Inernaonal Journal of Sochac Analy 7 By Propoon 3 hee equence are bounded and nce hey are alo ncreang he lm ex. Denoe hee lm by Y + Y := lm n Y+n := lm n Y n. (53) In wha follow we wll prove ha hee lm are n fac connuouandolveheyem(9). o do h we wll ue he followng clam: here ex a pove conan C uch ha for all n 1 E [ ( dk n ) d] C. (54) d he fr ep oward provng h clam o prove he abolue connuy of dk 1 wh repec o d.nongha S 1 =L ( Y +l ()) =L (L Y l ()) + (55) hen n vew of (A4) and he Iô-anaka formula we ge S 1 =S 1 f () d g () db 1 L (56) where L he local me a zero of he connuou emmarngale L Y l and where f () := ψ ( L EL Z )+1 {L > Y +l ()} (ψ ( L EL Z ) α( Y EY Z )+U ()) g () := Z 1 {L > Y +l ()} (Z Z V ()). I follow ha (57) where Λ he local me a for S 1 Y 1.Snce(S 1 Y 1 ) + S 1 he dfferenal mu concde whch yeld ha 1 dλ = 1 {Y 1 Hence dk 1 = 1 {Y 1 Y 1 =S 1 =S 1 } ((f () +ψ ( Y 1 1 dl dk 1 ) } ((f () +ψ ( Y 1 1 dl ) dk (dλ + 1 {Y 1 =S 1 } dl ) = 1 {Y 1 =S 1 from whch follow ha dk 1 } (f () +ψ ( Y 1 1 {Y 1 =S 1 } (f () +ψ ( Y 1 ( f () + ψ ( Y 1 EY 1 EY 1 Z 1 EY 1 EY 1 EY 1 Z 1 ) )d. Z 1 )) d Z 1 )) d Z 1 )) d (6) )) d (61) (6) Now n vew of (A1) (A4) andpropoon 3 here ex a conan C uch ha E [ ( f () + ψ ( Y 1 EY 1 + g () )d] C Z 1 ) (63) d(s 1 Y 1 ) =(f () +ψ ( Y 1 EY 1 Z 1 )) d +(g () Z 1 )db 1 dl dk 1. From Iô-anaka agan we ge ha d(s 1 Y 1 ) + (58) whch ogeher wh (6)prove(54)forn=1. For he nducon ep we only conder he cae =1 nce he oher cae follow n a mlar fahon. Aume ha dk n S 1n+1 /d afe (54) andconder heobacle proce =(Y n =Y +1n +l 1 ()) (Y +1n +b 1 () (Y +1n +b 1 ()) +b 1 () Y n l 1 ()) +. (64) = 1 {S {S 1 1 {S 1 >Y 1 } (f () +ψ ( Y 1 EY 1 >Y 1 } (g () Z 1 )db Z 1 )) d >Y 1 } (dk dl )+1 dλ (59) By (A4) and he Iô-anaka formula we ge S 1n+1 =S 1n+1 1 L1n f n+1 () d g n+1 () db 1 {Y +1n +b 1 () Y n +l 1 ()} dk+1n (65)

8 8 Inernaonal Journal of Sochac Analy where L 1n he local me a for he connuou emmarngale Y +1n +b 1 () Y n l 1 () and where f n+1 () := ψ {Y +1n ( Y+1n EY +1n +b 1 ()>Y n +l 1 ()} Z +1n )+U 1 () akng he weak lm n each de of h equaon along he ubequence menoned earler yeld Y =Y φ d k d Z db P-a.. (71) ( ψ + 1 +ψ ( Y+1n ( Y n EY +1n EY n U 1 () dk n ) d f n+1 () := Z +1n +V 1 () Z +1n Z n ) )+U 1 () (66) he procee on each de of he equaly beng oponal we can ue he oponal econ heorem (ee e.g. [1heorem 86 page 138]) o conclude ha Y =Y φ d k d Z db P-a.. (7) 1 {Y +1n (Z +1n +b 1 ()>Y n +l 1 ()} +V 1 () Z n V 1 ()). In vew of (A1) (A4) andpropoon 3 ogeher wh he nducon aumpon here ex a conan C > ndependen of nuchha E [ ( f n+1 () + ψ 1 ( Y 1n+1 + g n+1 () d)] C. EY 1n+1 Z 1n+1 ) (67) Followng he ame ep a we dd earler for dk 1 can be hown ha dk 1n+1 ( f n+1 () + ψ 1 ( Y 1n+1 EY 1n+1 Z 1n+1 ) )d (68) whch yeld ha here ex a conan C>ndependen of n uch ha E [ ( dk 1n+1 ) d] C. (69) d Hence clam (54)rueforalln 1. Propoon 3 and emae (54) ell u ha here a ubequence along whch he equence of procee /d) (ψ ( Y n EY n Z n )) and (Z n ) convergeweaklynherrepecvepacem 1 M 1 andm d o he procee (k ) (φ )and (Z ). Now for any n and any F-oppng me wehave (dk n Y n =Y n +K n ψ ( Y n Z n db. EY n Z n )d (7) herefore he proce Y connuou. Relyng on boh Dn heorem and Lebegue domnaed convergence heorem we fnd ha lm E [ up n Y n Y ]=. (73) In wha follow we wll characerze he lm procee Y + of he equence {Y +n } n a Snell envelope of he procee n he ene ha P-a.. and for each Y + = e up E [ ψ + 1 ( Y+ EY + Z + )d +ξ + 1 {=} +S + 1 {<} F ] (74) andhenwedervehermeconnuy. In vew of Propoon 3 and applyng Peng monoone lm heorem (ee [13]) o he equence (Y +n Z +n K +n ) we oban ha Y + càdlàg. Moreover here ex a càdlàg nondecreang proce K + K and a proce Z + M d uch ha Y + Y + =ξ ψ + ( Y + S +. Z + db EY + Z + )d+k + K+ (75) Hence n vew of Propoon 1 we arrve a (74)oncewehow ha (Y + S+ )dk+ =. (76)

9 Inernaonal Journal of Sochac Analy 9 Conder he malle ψ + -upermarngale Y + lower obacle S + whcholve Y + =ξ + + K + ( Y + ψ + ( Y + K + Y + EY + Z + Z + db S + S+ + )d K =. )d wh (77) By defnon we have ha Y + Y +.UngPropoon 5 we ee ha Y + Y +n n 1.Pangohelmwegeha Y + = Y + =1.Hence(76) afed. I reman o how ha Y + are connuou. Nong ha > and ha Y + afe (74) we fnd ha Y + Y + or equvalenly ha ΔY +.huuffcenoproveha he e {ΔY + <} empy. By he Doob-Meyer decompoon of he Snell envelope (ee Propoon 1) here ex for each a connuou marngale (M ) a connuou nondecreang proce (C ) and a purely dconnuou proce (D ) wh C =D =uchha Y + ψ + ( Y + EY + Z + )d=m C D (78) whch mean ha ΔY + = ΔD. Now n vew of Propoon 1 we have he followng propere of he jump of D.Ifhereajumpame n D 1 henhmeanha he proce (Y + l ) (Y 1 a 1 ) alo jump. Snce l 1 and Y 1 a 1 are connuou h can only mean ha here a jump n Y +. h n urn mean ha here a jump n D. Andconverelybyheameypeofreaonngwecandeduce ha f here a jump n D herealoajumpnd 1.Hence D 1 and D alwayjumpaheameme. Wh h n mnd denoe X:=(Y + l 1 ) and F:=Y 1 a 1.Wehave {Δ (X F) <} ={X F <X F } = {{X F <X F } {X <F <X }} {{X F <X F } {X <X <F }} {{X F <X F } {F <X <X }} = {{F <X } {X <F <X }} {{F <F } {X <X <F }} {{X <X } {F <X <X }} = {{F <X } {X <F } {F <X }} {{X <X } {F <X } {X <X }} = {{F <X } {X <F }} {{X <X } {F <X }} = {{F <X } {X <F } {X <X }} {{X <X } {F <X } {F <X }} = {{X <X } {F <X }} {{X <F } {F <X }} ={X <X } {F <X } ={ΔX <} {F <X } ={ΔY + <(Y 1 a 1 ()) <(Y + l 1 ())}. (79) WhahelluhafS +1 jump a me henweknow wo hng. One ha Y + alo ha a jump a me and he oher ha herefore nce ΔY + oban ha {ΔD 1 >} {ΔD >} {Y+1 ={ΔD >} {Y+1 ={ΔD >} {Y+1 Smlarly we have {ΔD >} {ΔD 1 >} {Y+ ={ΔD 1 >} {Y+ ={ΔD 1 >} {Y+ Y 1 a 1 () <Y + l 1 (). (8) = ΔD nvewofpropoon 1 we =S+1 } =(Y+ l 1 ()) (Y 1 a 1 ())} =Y+ =S+ } l 1 ()}. (81) =(Y+1 l ()) (Y a ())} =Y+1 l ()}. (8) Fnally nce we know ha D 1 and D alway jump a he ame me hold ha {ΔD 1 >} {ΔD1 >} ={ΔD 1 >} {ΔD >} ={Y +1 {Y + =Y+ l 1 ()} =Y+1 l ()} = (83)

10 1 Inernaonal Journal of Sochac Analy nce for any l 1 () + l () >. I follow ha he procee D 1 and D are conan and dencally equal o nce D 1 =D =.HenceheproceeY+1 and Y + are connuou. h n urn gven (75) yeld he connuy of he ncreang procee K +. herefore (Y + Z + K + ) a oluon o he fr par of he yem (9). By Dn heorem and Lebegue domnaed convergence heorem agan we alo conclude ha he convergence of (Y +1n ) n 1 o Y +1 hold n S c ;ha lm E [ up n Y+n Y + ]=. (84) Furhermore nce Y connuou we can rely on andard argumen n parcular by applyng Iô formula o (Y +n Y +m ) (m n )oclamha(z +n ) a Cauchy equence and herefore converge o Z + n M d ;ha lm E [ n Z+n Z + d] =. (85) Combnng h wh (84) and he defnon of he procee Y +n and Y + yeld ha lm E [ up n K+n In oal we have hown ha lm E [ up n Y+n Z+n Y + Z + d + up K + ]=. (86) K+n K + ]=. (87) Ung (84)andapplyngIô formula o (Y n Y m ) (m n )followha(z n ) n 1 a Cauchy equence and herefore converge o Z n M d ;ha lm E [ n Z n Z d] =. (88) Ung h and akng no accoun he decompoon obaned n (7) we arrve a Y =ξ ψ ( Y EY Z )d k d Z db Y 1 (Y +l 1 ()) (Y +1 +b 1 ()) Y (Y 1 +l ()) (Y + +b ()). Ahownabovealoholdha lm E [ up n Y n + up K n Y Z n k d ]=. Z d (89) (9) Moreover due o he weak convergence of (dk n /d n 1)o he proce k and he rong convergence of (Y +n ) and (Y n ) n S followha = (S n Y n ) dk n (S a n whch mple ha f we defne K Y ) k d (91) := k d (9) hen (Y Z K ) a oluon o he econd par of (9). Iremanohowhaheobanedoluonmnmal. o do h we compare Y + wh he malle ψ + - upermarngale wh lower obacle S + denoed by Y + and we compare Y + wh he malle ψ -upermarngale wh upper obacle S denoed by Y ; ha le (Y ± Z ± K ± ) be he malle oluon o he yem (Y + Z + K + )=F + (ξ + ψ+ S+ ) = 1 (Y Z K )=F (ξ ψ S ) = 1. (93) Ung Propoon 4 and he mnmaly of he oluon we can conclude ha Y ± Y ±. On he oher hand Propoon 4 aloelluhaforalln we have Y ±n Y ±.NownceY ±n are ncreang n n we can ake he lm n and oban ha Y ± Y ±.huy ± =Y ±. Fnally o eablh ha he oluon no unque n general he counerexample found n [1] vald here a well. Appendce A. Proof of Propoon he proof ue echnque found n [ 7 8]. Le S be he pace of progrevely meaurable {(Y Z ) : } akng value n R R d uch ha Z M d and Y S for. ake any (U V) S and defne f() := f( U EU V ). hen by Propoon 5.1 n [] here a unque rple (Y Z K) uch ha Y S Z M d K K K L (Ω F P) Y =ξ+ f () d + K K Z db K = Y S (Y S )dk =. (A.1) We defne a mappng Φ from S ono elf by ayng ha (Y Z) = Φ(U V) he unque elemen of S uch ha f we defne K =Y Y f () d Z db (A.)

11 Inernaonal Journal of Sochac Analy 11 hen (YZK) he unque rple whch olve he yem above. Now le (U V ) be anoher elemen of S and le (Y Z )= Φ(U V ). In addon le U=U U V=V V Y=Y Y Z=Z Z f= f f where f () := f( U EU V ). For any β> applyng Iô formula o e β Y akng expecaon we fnd ha E [e β Y βe β Y d e β Z d] Moreover nce =E [ e β Y f () d e β Y dk ]. E [ e β Y dk ] hold ha =E [ e β (Y Y )d(k K )] (A.3) and hen =E [ e β [(Y S ) (Y S )] (dk dk )] = E [ e β (Y S )dk ] E [ e β (Y S )dk ] E [ βe β Y d e β Z d] E [ e β Y f () d]. (A.4) (A.5) (A.6) Ung he Lpchz propery of f and hen Young nequaly yeld ha E [ βe β Y d e β Z d] E [ e β Y f () d] =E [ e β Y (f ( U EU V ) f ( U EU V )) d] KE [ e β Y ( U U + EU EU + V V )d] KE [ e β Y ( U U + E U U 1K E [ e β Y d] + V V )d] E [ e β ( U U + E U U 1K E [ e β Y d] E [ = 1K E [ e β Y d] + V V ) d] e β ( U U + E U U + V V )d] e β (EU + E V )d 1K E [ e β Y d] + 1 E [ e β (U + V )d]. Seng β = 1K +1we fnd (A.7) E [ e β (Y + Z )d] (A.8) 1 E [ e β (U + V )d]. hu he mappng Φ a rc conracon on S wh he norm 1/ (Y Z) β =(E e β (Y + Z )d). (A.9) he Banach fxed pon heorem hen yeld ha Φ ha a unque fxed pon whch he ough oluon.

12 1 Inernaonal Journal of Sochac Analy B. Proof of Propoon 3 Applyng Iô formula o Y yeld ha Y Z d =ξ + Y f(y EY Z )d + Y dk Y Z db =ξ + Y f(y EY Z )d + S dk Y Z db and o by akng expecaon we ge E [Y Z d] (B.1) = E [ξ + S dk ]+E[ Y f(y EY Z )d]. (B.) Ung he Lpchz propery of f yeld ha E [ Y f(y EY Z )d] Hence E [ Y f ( ) +K Y +K Y E [ Y ]+K Y Z d] E [ Y ]+E[ f ( ) ]+KE[ Y ] +KE[ Y ] +K E [ Y ]+ 1 E [ Z ]d (1 + 4K + K ) E [ Y ]+E[ f( ) ]d + 1 E [ Z ]d. E [ Y ]+ 1 E [ Z d] E [ξ + S dk f ( ) d] +(1+4K+K ) E [ Y ]d. (B.3) (B.4) herefore E [ Y ] E[ξ + S dk f ( ) d] +(1+4K+K ) E [ Y ]d (B.5) 1 E [ Z d] E [ξ + S dk f ( ) d] +(1+4K+K ) E [ Y ]d (B.6) E [ξ + S + dk f ( ) d] +(1+4K+K ) E [ Y ]d. Ung Gronwall nequaly on (B.5) we oban ha E [ Y ] CE[ξ + S dk f ( ) d] CE [ξ + S + dk f ( ) d]. (B.7) Inerng no (B.6) yeld ha 1 E [ Z d] E [ξ + S + dk f ( ) d] +(1+4K+K ) CE [ξ + S + u dk u f (u ) du] d E [ξ + S + dk f ( ) d] +(1+4K+K ) CE [ (ξ + S + dk f ( ) d)]. (B.8) Hence E [ Z d] C E [ξ + S + dk f ( ) d]. (B.9)

13 Inernaonal Journal of Sochac Analy 13 Conder now he equaly =4K E [ f ( ) d] K =Y ξ f(y EY Z )d+ Z db. (B.1) +8K E [ Y d] + 4K E [ Z d] (B.1) We have E [K ]=E[(Y ξ f(y EY Z )d Z db ) ] 4E [Y +ξ +( f(y EY Z )d) +( Z db ) ] ={Iô ruleonhequaredochacnegral} =4E [Y +ξ +( f(y EY Z )d) Z d] 4E [Y +ξ f( Y EY Z ) d Z d] CE [ξ + S + dk f ( ) d] +4E [ξ f( Y EY Z ) d] (B.11) where he la nequaly follow from ung (B.7) and(b.9). Now from he Lpchz propery of f we ge E [ f( Y EY Z ) d] K E [( f ( ) + Y + EY + Z ) ]d 4K E [ f ( ) + Y + EY + Z ]d 4K E [ f ( ) + Y + E [ Y ]+ Z ]d whch by nerng no he above and hen ung (B.7) and (B.9) agan yeld ha E [K ] CE [ξ + S + dk f ( ) d] +4E [ξ ]+8K E [ f ( ) d] CE [ξ + S + dk f ( ) d] +8(1+K ) E [ξ f ( ) d + S + dk ] =CE [ξ f ( ) d + S + dk ] CE [ξ f ( ) d] + E [C ( up S + )K ] CE [ξ f ( ) d] +C E [ up (S + ) ]+ 1 E [K ]. (B.13) hu E [K ] C[ξ f ( ) d + up (S + ) ]. (B.14) Ung he Burkholder-Dav-Gundy nequaly we fnd ha E [ up Y ] CE[ Z d]. (B.15) Hence agan n vew of (B.9) we ge E [ up Y Z d + K ] E [(1+C) Z d + K ] CE [ξ f ( ) d + up (S + ) ]. (B.16)

14 14 Inernaonal Journal of Sochac Analy C. Proof of Propoon 4 Iô formula appled o (Y Y )+ yeld ha (Y Y )+ = (Y Y )+ (f ( Y EY Z ) f ( Y EY Z )) d + (Y Y )+ (dk dk ) (Y Y )+ (Z Z )db (Y Y )+ dl 1 {Y >Y } Z Z d (Y Y )+ (f ( Y EY Z ) f ( Y EY Z )) d + (Y Y )+ (dk dk ) (Y Y )+ (Z Z )db 1 {Y >Y } Z Z d. akng expecaon we fnd ha E (Y Y )+ + E 1 {Y >Y } Z Z d E (Y Y )+ (f ( Y EY Z ) f ( Y EY Z )) d +E (Y Y )+ (dk dk ). (C.1) (C.) Hence E (Y Y )+ + E 1 {Y >Y } Z Z d E (Y Y )+ (f(y EY Z ) f ( Y EY Z )) d =E (Y Y )+ E (Y Y )+ (f(y EY Z ) f(y EY Z ) +f(y EY Z ) f ( Y EY Z )) d (f(y EY Z ) f(y EY Z )) d (C.4) by aumpon. Whou lo of generaly we may aume ha f he generaor whch nondecreang n he hrd argumen o ha by he Lpchz propery of f we ge E (Y Y )+ + E 1 {Y >Y } Z Z d KE (Y Y )+ ( Y Y +(EY EY )+ + Z Z )d KE (Y Y )+ ( Y Y + Z Z )d +KE (Y Y )+ E [(Y Y )+ ]d (C.5) where he la nequaly follow from Jenen nequaly. For he fr negral we have Bu on {Y >Y } hold ha Y >Y S S fromwhch follow ha (Y Y )+ (dk dk )= (Y Y )+ dk. (C.3) KE (Y Y )+ ( Y Y + Z Z )d =KE (Y Y )+ d + E K(Y Y )+ 1 {Y >Y } Z Z d

15 Inernaonal Journal of Sochac Analy 15 KE (Y Y )+ d +K E (Y Y )+ d + 1 E 1 {Y >Y } Z Z d = (K + K ) E (Y Y )+ d + 1 E 1 {Y >Y } Z Z d. (C.6) Inerng no he above and cancelng ou erm yeld ha E (Y Y )+ D. Proof of Propoon 5 Conder he penalzed equaon of he MF-RBSDE for n 1: Leng Y n Y n =ξ+ f(y n EYn Zn )d +n (Y n S ) d Z n db =ξ f ( Y n +n (Y n EY n Z n )d S ) d Z n db. f n ( y 1 y z):=f(y 1 y z)+n(y z) f n ( y 1 y z):=f ( y 1 y z)+n(y z) (D.1) (D.) + 1 E 1 {Y >Y } Z Z d (K + K ) E (Y Y )+ d +KE (Y Y )+ E [(Y Y )+ ]d = (K + K ) E (Y Y )+ d (C.7) we have wo equence of unrefleced connuou MF-BSDE wh generaor f n and f n where f n ( y 1 y z) f n ( y 1 y z). (D.3) Followng he ep n he proof of Propoon 4 we ee ha a.. akng he lm n weoban he reul. Y n Y n Conflc of Inere he auhor declare ha here no conflc of nere regardng he publcaon of h paper. +K E[(Y Y )+ ] d (K + K ) E (Y Y )+ d +K E [ (Y Y )+ ]d = (4K + K ) E (Y Y )+ d. Hence hold ha E (Y Y )+ (4K+K ) E (Y Y )+ d. (C.8) Ung Gronwall nequaly yeld ha and hence Y Y P-a.. E (Y Y )+ = (C.9) Acknowledgmen he fnancal uppor from he Swedh Expor Cred Corporaon (SEK) graefully acknowledged. Reference [1] B. Djehche and A. A. Hamd Full balance hee wo-mode opmal wchng problem Preprn 11. [] N. El Karou C. Kapoudjan E. Pardoux S. Peng and M. C. Quenez Refleced oluon of backward SDE and relaed obacle problem for PDE he Annal of Probablyvol.5 no. pp [3] V. S. Borkar and K. S. Kumar McKean-Vlaov lm n porfolo opmzaon Sochac Analy and Applcaon vol.8no. 5pp [4] J.M.LaryandP.L.Lon Meanfeldgame Japanee Journal of Mahemacvol.no.1pp [5] R. Buckdahn B. Djehche J. L and S. Peng Mean-feld backward ochac dfferenal equaon: a lm approach he Annal of Probablyvol.37no.4pp [6] R.BuckdahnJ.LandS.Peng Mean-feldbackwardochac dfferenal equaon and relaed paral dfferenal equaon Sochac Procee and her Applcaon vol.119no. 1 pp

16 16 Inernaonal Journal of Sochac Analy [7] J. L Refleced mean-feld backward ochac dfferenal equaon. Approxmaon and aocaed nonlnear PDE Journal of Mahemacal Analy and Applcaonvol.413no. 1pp [8] Z. L and J. Luo Mean-feld refleced backward ochac dfferenal equaon Sac & Probably Leer vol.8 no.11pp [9] J. Cvanć and I. Karaza Backward ochac dfferenal equaon wh reflecon and Dynkn game he Annal of Probablyvol.4no.4pp [1] S. Hamadène Refleced BSDE wh dconnuou barrer and applcaon Sochac and Sochac Reporvol.74no.3-4 pp [11] I. Karaza and S. E. Shreve Mehod of Mahemacal Fnance vol. 39 Sprnger New York NY USA [1] C. Dellachere and P. Meyer Probable and Poenal chaper 1 4 Hermann Par France [13] S. Peng Monoonc lm heorem of BSDE and nonlnear decompoon heorem of Doob-Meyer ype Probably heory and Relaed Feldvol.113no.4pp

17 Advance n Operaon Reearch Hndaw Publhng Corporaon hp:// Volume 14 Advance n Decon Scence Hndaw Publhng Corporaon hp:// Volume 14 Journal of Appled Mahemac Algebra Hndaw Publhng Corporaon hp:// Hndaw Publhng Corporaon hp:// Volume 14 Journal of Probably and Sac Volume 14 he Scenfc World Journal Hndaw Publhng Corporaon hp:// Hndaw Publhng Corporaon hp:// Volume 14 Inernaonal Journal of Dfferenal Equaon Hndaw Publhng Corporaon hp:// Volume 14 Volume 14 Subm your manucrp a hp:// Inernaonal Journal of Advance n Combnaorc Hndaw Publhng Corporaon hp:// Mahemacal Phyc Hndaw Publhng Corporaon hp:// Volume 14 Journal of Complex Analy Hndaw Publhng Corporaon hp:// Volume 14 Inernaonal Journal of Mahemac and Mahemacal Scence Mahemacal Problem n Engneerng Journal of Mahemac Hndaw Publhng Corporaon hp:// Volume 14 Hndaw Publhng Corporaon hp:// Volume 14 Volume 14 Hndaw Publhng Corporaon hp:// Volume 14 Dcree Mahemac Journal of Volume 14 Hndaw Publhng Corporaon hp:// Dcree Dynamc n Naure and Socey Journal of Funcon Space Hndaw Publhng Corporaon hp:// Abrac and Appled Analy Volume 14 Hndaw Publhng Corporaon hp:// Volume 14 Hndaw Publhng Corporaon hp:// Volume 14 Inernaonal Journal of Journal of Sochac Analy Opmzaon Hndaw Publhng Corporaon hp:// Hndaw Publhng Corporaon hp:// Volume 14 Volume 14

Optimal Switching of One-Dimensional Reflected BSDEs, and Associated Multi-Dimensional BSDEs with Oblique Reflection

Optimal Switching of One-Dimensional Reflected BSDEs, and Associated Multi-Dimensional BSDEs with Oblique Reflection arxv:81.3176v1 [mah.pr] 17 Oc 28 Opmal Swchng of One-Dmenonal Refleced BSDE, and Aocaed Mul-Dmenonal BSDE wh Oblque Reflecon Shanjan Tang We Zhong Ocober 17, 28 Abrac In h paper, he opmal wchng problem

More information

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function MACROECONOMIC THEORY T J KEHOE ECON 87 SPRING 5 PROBLEM SET # Conder an overlappng generaon economy le ha n queon 5 on problem e n whch conumer lve for perod The uly funcon of he conumer born n perod,

More information

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation Global Journal of Pure and Appled Mahemacs. ISSN 973-768 Volume 4, Number 6 (8), pp. 89-87 Research Inda Publcaons hp://www.rpublcaon.com Exsence and Unqueness Resuls for Random Impulsve Inegro-Dfferenal

More information

Matrix reconstruction with the local max norm

Matrix reconstruction with the local max norm Marx reconrucon wh he local max norm Rna oygel Deparmen of Sac Sanford Unvery rnafb@anfordedu Nahan Srebro Toyoa Technologcal Inue a Chcago na@cedu Rulan Salakhudnov Dep of Sac and Dep of Compuer Scence

More information

( ) () we define the interaction representation by the unitary transformation () = ()

( ) () we define the interaction representation by the unitary transformation () = () Hgher Order Perurbaon Theory Mchael Fowler 3/7/6 The neracon Represenaon Recall ha n he frs par of hs course sequence, we dscussed he chrödnger and Hesenberg represenaons of quanum mechancs here n he chrödnger

More information

H = d d q 1 d d q N d d p 1 d d p N exp

H = d d q 1 d d q N d d p 1 d d p N exp 8333: Sacal Mechanc I roblem Se # 7 Soluon Fall 3 Canoncal Enemble Non-harmonc Ga: The Hamlonan for a ga of N non neracng parcle n a d dmenonal box ha he form H A p a The paron funcon gven by ZN T d d

More information

Epistemic Game Theory: Online Appendix

Epistemic Game Theory: Online Appendix Epsemc Game Theory: Onlne Appendx Edde Dekel Lucano Pomao Marcano Snscalch July 18, 2014 Prelmnares Fx a fne ype srucure T I, S, T, β I and a probably µ S T. Le T µ I, S, T µ, βµ I be a ype srucure ha

More information

Part II CONTINUOUS TIME STOCHASTIC PROCESSES

Part II CONTINUOUS TIME STOCHASTIC PROCESSES Par II CONTINUOUS TIME STOCHASTIC PROCESSES 4 Chaper 4 For an advanced analyss of he properes of he Wener process, see: Revus D and Yor M: Connuous marngales and Brownan Moon Karazas I and Shreve S E:

More information

A. Inventory model. Why are we interested in it? What do we really study in such cases.

A. Inventory model. Why are we interested in it? What do we really study in such cases. Some general yem model.. Inenory model. Why are we nereed n? Wha do we really udy n uch cae. General raegy of machng wo dmlar procee, ay, machng a fa proce wh a low one. We need an nenory or a buffer or

More information

Downloaded 10/13/16 to Redistribution subject to SIAM license or copyright; see

Downloaded 10/13/16 to Redistribution subject to SIAM license or copyright; see SIAM J. CONTROL OPTIM. Vol. 52, No. 5, pp. 335 375 c 204 Socey for Indural and Appled Mahemac Downloaded 0/3/6 o 36.42.24.99. Redrbuon ubec o SIAM lcene or copyrgh; ee hp://www.am.org/ournal/oa.php ON

More information

A Demand System for Input Factors when there are Technological Changes in Production

A Demand System for Input Factors when there are Technological Changes in Production A Demand Syem for Inpu Facor when here are Technologcal Change n Producon Movaon Due o (e.g.) echnologcal change here mgh no be a aonary relaonhp for he co hare of each npu facor. When emang demand yem

More information

Control Systems. Mathematical Modeling of Control Systems.

Control Systems. Mathematical Modeling of Control Systems. Conrol Syem Mahemacal Modelng of Conrol Syem chbum@eoulech.ac.kr Oulne Mahemacal model and model ype. Tranfer funcon model Syem pole and zero Chbum Lee -Seoulech Conrol Syem Mahemacal Model Model are key

More information

Online Appendix for. Strategic safety stocks in supply chains with evolving forecasts

Online Appendix for. Strategic safety stocks in supply chains with evolving forecasts Onlne Appendx for Sraegc safey socs n supply chans wh evolvng forecass Tor Schoenmeyr Sephen C. Graves Opsolar, Inc. 332 Hunwood Avenue Hayward, CA 94544 A. P. Sloan School of Managemen Massachuses Insue

More information

L N O Q. l q l q. I. A General Case. l q RANDOM LAGRANGE MULTIPLIERS AND TRANSVERSALITY. Econ. 511b Spring 1998 C. Sims

L N O Q. l q l q. I. A General Case. l q RANDOM LAGRANGE MULTIPLIERS AND TRANSVERSALITY. Econ. 511b Spring 1998 C. Sims Econ. 511b Sprng 1998 C. Sm RAD AGRAGE UPERS AD RASVERSAY agrange mulpler mehod are andard fare n elemenary calculu coure, and hey play a cenral role n economc applcaon of calculu becaue hey ofen urn ou

More information

NONLOCAL BOUNDARY VALUE PROBLEM FOR SECOND ORDER ANTI-PERIODIC NONLINEAR IMPULSIVE q k INTEGRODIFFERENCE EQUATION

NONLOCAL BOUNDARY VALUE PROBLEM FOR SECOND ORDER ANTI-PERIODIC NONLINEAR IMPULSIVE q k INTEGRODIFFERENCE EQUATION Euroean Journal of ahemac an Comuer Scence Vol No 7 ISSN 59-995 NONLOCAL BOUNDARY VALUE PROBLE FOR SECOND ORDER ANTI-PERIODIC NONLINEAR IPULSIVE - INTEGRODIFFERENCE EQUATION Hao Wang Yuhang Zhang ngyang

More information

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS R&RATA # Vol.) 8, March FURTHER AALYSIS OF COFIDECE ITERVALS FOR LARGE CLIET/SERVER COMPUTER ETWORKS Vyacheslav Abramov School of Mahemacal Scences, Monash Unversy, Buldng 8, Level 4, Clayon Campus, Wellngon

More information

A Weak Dynamic Programming Principle for Zero-Sum Stochastic Differential Games with Unbounded Controls

A Weak Dynamic Programming Principle for Zero-Sum Stochastic Differential Games with Unbounded Controls A Weak Dynac Prograng Prncple for Zero-Su Sochac Dfferenal Gae wh Unbounded Conrol rhan Bayrakar, Song Yao Abrac We analyze a zero-u ochac dfferenal gae beween wo copeng player who can chooe unbounded

More information

Survival Analysis and Reliability. A Note on the Mean Residual Life Function of a Parallel System

Survival Analysis and Reliability. A Note on the Mean Residual Life Function of a Parallel System Communcaons n Sascs Theory and Mehods, 34: 475 484, 2005 Copyrgh Taylor & Francs, Inc. ISSN: 0361-0926 prn/1532-415x onlne DOI: 10.1081/STA-200047430 Survval Analyss and Relably A Noe on he Mean Resdual

More information

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng

More information

A Nonlinear ILC Schemes for Nonlinear Dynamic Systems To Improve Convergence Speed

A Nonlinear ILC Schemes for Nonlinear Dynamic Systems To Improve Convergence Speed IJCSI Inernaonal Journal of Compuer Scence Iue, Vol. 9, Iue 3, No, ay ISSN (Onlne): 694-84 www.ijcsi.org 8 A Nonlnear ILC Scheme for Nonlnear Dynamc Syem o Improve Convergence Speed Hoen Babaee, Alreza

More information

ELIMINATION OF DOMINATED STRATEGIES AND INESSENTIAL PLAYERS

ELIMINATION OF DOMINATED STRATEGIES AND INESSENTIAL PLAYERS OPERATIONS RESEARCH AND DECISIONS No. 1 215 DOI: 1.5277/ord1513 Mamoru KANEKO 1 Shuge LIU 1 ELIMINATION OF DOMINATED STRATEGIES AND INESSENTIAL PLAYERS We udy he proce, called he IEDI proce, of eraed elmnaon

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Lnear Response Theory: The connecon beween QFT and expermens 3.1. Basc conceps and deas Q: ow do we measure he conducvy of a meal? A: we frs nroduce a weak elecrc feld E, and hen measure

More information

Available online at J. Nonlinear Sci. Appl. 9 (2016), Research Article

Available online at  J. Nonlinear Sci. Appl. 9 (2016), Research Article Avalable onlne a www.jna.com J. Nonlnear Sc. Appl. 9 06, 76 756 Reearch Arcle Aympoc behavor and a poeror error emae n Sobolev pace for he generalzed overlappng doman decompoon mehod for evoluonary HJB

More information

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005 Dynamc Team Decson Theory EECS 558 Proec Shruvandana Sharma and Davd Shuman December 0, 005 Oulne Inroducon o Team Decson Theory Decomposon of he Dynamc Team Decson Problem Equvalence of Sac and Dynamc

More information

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim Korean J. Mah. 19 (2011), No. 3, pp. 263 272 GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS Youngwoo Ahn and Kae Km Absrac. In he paper [1], an explc correspondence beween ceran

More information

Let s treat the problem of the response of a system to an applied external force. Again,

Let s treat the problem of the response of a system to an applied external force. Again, Page 33 QUANTUM LNEAR RESPONSE FUNCTON Le s rea he problem of he response of a sysem o an appled exernal force. Agan, H() H f () A H + V () Exernal agen acng on nernal varable Hamlonan for equlbrum sysem

More information

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5 TPG460 Reservor Smulaon 08 page of 5 DISCRETIZATIO OF THE FOW EQUATIOS As we already have seen, fne dfference appromaons of he paral dervaves appearng n he flow equaons may be obaned from Taylor seres

More information

On One Analytic Method of. Constructing Program Controls

On One Analytic Method of. Constructing Program Controls Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna

More information

Graduate Macroeconomics 2 Problem set 5. - Solutions

Graduate Macroeconomics 2 Problem set 5. - Solutions Graduae Macroeconomcs 2 Problem se. - Soluons Queson 1 To answer hs queson we need he frms frs order condons and he equaon ha deermnes he number of frms n equlbrum. The frms frs order condons are: F K

More information

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and hs arcle appeared n a journal publshed by Elsever. he aached copy s furnshed o he auhor for nernal non-commercal research and educaon use, ncludng for nsrucon a he auhors nsuon and sharng wh colleagues.

More information

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC CH.3. COMPATIBILITY EQUATIONS Connuum Mechancs Course (MMC) - ETSECCPB - UPC Overvew Compably Condons Compably Equaons of a Poenal Vecor Feld Compably Condons for Infnesmal Srans Inegraon of he Infnesmal

More information

Chapter Lagrangian Interpolation

Chapter Lagrangian Interpolation Chaper 5.4 agrangan Inerpolaon Afer readng hs chaper you should be able o:. dere agrangan mehod of nerpolaon. sole problems usng agrangan mehod of nerpolaon and. use agrangan nerpolans o fnd deraes and

More information

Cooling of a hot metal forging. , dt dt

Cooling of a hot metal forging. , dt dt Tranen Conducon Uneady Analy - Lumped Thermal Capacy Model Performed when; Hea ranfer whn a yem produced a unform emperaure drbuon n he yem (mall emperaure graden). The emperaure change whn he yem condered

More information

Wissal SABBAGH. Some Contributions on Probabilistic Interpretation For Nonlinear Stochastic PDEs JURY

Wissal SABBAGH. Some Contributions on Probabilistic Interpretation For Nonlinear Stochastic PDEs JURY Wal SABBAGH Mémore préené en vue de l obenon du grade de Doceur de l Unveré du Mane ou le label de L Unveré Nane Anger Le Man e de l'ecole Naonale d'ingéneur de Tun ou le label de L Unveré de Tun EL Manar

More information

( t) Outline of program: BGC1: Survival and event history analysis Oslo, March-May Recapitulation. The additive regression model

( t) Outline of program: BGC1: Survival and event history analysis Oslo, March-May Recapitulation. The additive regression model BGC1: Survval and even hsory analyss Oslo, March-May 212 Monday May 7h and Tuesday May 8h The addve regresson model Ørnulf Borgan Deparmen of Mahemacs Unversy of Oslo Oulne of program: Recapulaon Counng

More information

ON THE WEAK LIMITS OF SMOOTH MAPS FOR THE DIRICHLET ENERGY BETWEEN MANIFOLDS

ON THE WEAK LIMITS OF SMOOTH MAPS FOR THE DIRICHLET ENERGY BETWEEN MANIFOLDS ON THE WEA LIMITS OF SMOOTH MAPS FOR THE DIRICHLET ENERGY BETWEEN MANIFOLDS FENGBO HANG Absrac. We denfy all he weak sequenal lms of smooh maps n W (M N). In parcular, hs mples a necessary su cen opologcal

More information

Lecture 18: The Laplace Transform (See Sections and 14.7 in Boas)

Lecture 18: The Laplace Transform (See Sections and 14.7 in Boas) Lecure 8: The Lalace Transform (See Secons 88- and 47 n Boas) Recall ha our bg-cure goal s he analyss of he dfferenal equaon, ax bx cx F, where we emloy varous exansons for he drvng funcon F deendng on

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm H ( q, p, ) = q p L( q, q, ) H p = q H q = p H = L Equvalen o Lagrangan formalsm Smpler, bu

More information

CS286.2 Lecture 14: Quantum de Finetti Theorems II

CS286.2 Lecture 14: Quantum de Finetti Theorems II CS286.2 Lecure 14: Quanum de Fne Theorems II Scrbe: Mara Okounkova 1 Saemen of he heorem Recall he las saemen of he quanum de Fne heorem from he prevous lecure. Theorem 1 Quanum de Fne). Le ρ Dens C 2

More information

Comparison of Differences between Power Means 1

Comparison of Differences between Power Means 1 In. Journal of Mah. Analyss, Vol. 7, 203, no., 5-55 Comparson of Dfferences beween Power Means Chang-An Tan, Guanghua Sh and Fe Zuo College of Mahemacs and Informaon Scence Henan Normal Unversy, 453007,

More information

A NUMERICAL SCHEME FOR BSDES. BY JIANFENG ZHANG University of Southern California, Los Angeles

A NUMERICAL SCHEME FOR BSDES. BY JIANFENG ZHANG University of Southern California, Los Angeles The Annals of Appled Probably 24, Vol. 14, No. 1, 459 488 Insue of Mahemacal Sascs, 24 A NUMERICAL SCHEME FOR BSDES BY JIANFENG ZHANG Unversy of Souhern Calforna, Los Angeles In hs paper we propose a numercal

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm Hqp (,,) = qp Lqq (,,) H p = q H q = p H L = Equvalen o Lagrangan formalsm Smpler, bu wce as

More information

Chapter 6: AC Circuits

Chapter 6: AC Circuits Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.

More information

Lecture 11: Stereo and Surface Estimation

Lecture 11: Stereo and Surface Estimation Lecure : Sereo and Surface Emaon When camera poon have been deermned, ung rucure from moon, we would lke o compue a dene urface model of he cene. In h lecure we wll udy he o called Sereo Problem, where

More information

Solution in semi infinite diffusion couples (error function analysis)

Solution in semi infinite diffusion couples (error function analysis) Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of

More information

A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION

A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION S19 A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION by Xaojun YANG a,b, Yugu YANG a*, Carlo CATTANI c, and Mngzheng ZHU b a Sae Key Laboraory for Geomechancs and Deep Underground Engneerng, Chna Unversy

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 0 Canoncal Transformaons (Chaper 9) Wha We Dd Las Tme Hamlon s Prncple n he Hamlonan formalsm Dervaon was smple δi δ Addonal end-pon consrans pq H( q, p, ) d 0 δ q ( ) δq ( ) δ

More information

New Oscillation Results for Forced Second Order Differential Equations with Mixed Nonlinearities

New Oscillation Results for Forced Second Order Differential Equations with Mixed Nonlinearities Appled Maheac,, 3, 47-53 hp://dxdoorg/436/a33 Publhed Onlne February (hp://wwwscrporg/ournal/a) New Ocllaon Reul for Forced Second Order Dfferenal Equaon wh Mxed Nonlneare Ercan Tunç, Adl Kayaz Deparen

More information

Laplace Transformation of Linear Time-Varying Systems

Laplace Transformation of Linear Time-Varying Systems Laplace Tranformaon of Lnear Tme-Varyng Syem Shervn Erfan Reearch Cenre for Inegraed Mcroelecronc Elecrcal and Compuer Engneerng Deparmen Unvery of Wndor Wndor, Onaro N9B 3P4, Canada Aug. 4, 9 Oulne of

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4 CS434a/54a: Paern Recognon Prof. Olga Veksler Lecure 4 Oulne Normal Random Varable Properes Dscrmnan funcons Why Normal Random Varables? Analycally racable Works well when observaon comes form a corruped

More information

Should Exact Index Numbers have Standard Errors? Theory and Application to Asian Growth

Should Exact Index Numbers have Standard Errors? Theory and Application to Asian Growth Should Exac Index umbers have Sandard Errors? Theory and Applcaon o Asan Growh Rober C. Feensra Marshall B. Rensdorf ovember 003 Proof of Proposon APPEDIX () Frs, we wll derve he convenonal Sao-Vara prce

More information

NON-HOMOGENEOUS SEMI-MARKOV REWARD PROCESS FOR THE MANAGEMENT OF HEALTH INSURANCE MODELS.

NON-HOMOGENEOUS SEMI-MARKOV REWARD PROCESS FOR THE MANAGEMENT OF HEALTH INSURANCE MODELS. NON-HOOGENEOU EI-AKO EWA POCE FO THE ANAGEENT OF HEATH INUANCE OE. Jacque Janen CEIAF ld Paul Janon 84 e 9 6 Charlero EGIU Fax: 32735877 E-mal: ceaf@elgacom.ne and amondo anca Unverà a apenza parmeno d

More information

Method of upper lower solutions for nonlinear system of fractional differential equations and applications

Method of upper lower solutions for nonlinear system of fractional differential equations and applications Malaya Journal of Maemak, Vol. 6, No. 3, 467-472, 218 hps://do.org/1.26637/mjm63/1 Mehod of upper lower soluons for nonlnear sysem of fraconal dfferenal equaons and applcaons D.B. Dhagude1 *, N.B. Jadhav2

More information

Notes on the stability of dynamic systems and the use of Eigen Values.

Notes on the stability of dynamic systems and the use of Eigen Values. Noes on he sabl of dnamc ssems and he use of Egen Values. Source: Macro II course noes, Dr. Davd Bessler s Tme Seres course noes, zarads (999) Ineremporal Macroeconomcs chaper 4 & Techncal ppend, and Hamlon

More information

6.8 Laplace Transform: General Formulas

6.8 Laplace Transform: General Formulas 48 HAP. 6 Laplace Tranform 6.8 Laplace Tranform: General Formula Formula Name, ommen Sec. F() l{ f ()} e f () d f () l {F()} Definiion of Tranform Invere Tranform 6. l{af () bg()} al{f ()} bl{g()} Lineariy

More information

Multiple Failures. Diverse Routing for Maximizing Survivability. Maximum Survivability Models. Minimum-Color (SRLG) Diverse Routing

Multiple Failures. Diverse Routing for Maximizing Survivability. Maximum Survivability Models. Minimum-Color (SRLG) Diverse Routing Mulple Falure Dvere Roung for Maxmzng Survvably One-falure aumpon n prevou work Mulple falure Hard o provde 100% proecon Maxmum urvvably Maxmum Survvably Model Mnmum-Color (SRLG) Dvere Roung Each lnk ha

More information

In the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!") i+1,q - [(!

In the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!) i+1,q - [(! ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL The frs hng o es n wo-way ANOVA: Is here neracon? "No neracon" means: The man effecs model would f. Ths n urn means: In he neracon plo (wh A on he horzonal

More information

China s Model of Managing the Financial System

China s Model of Managing the Financial System Chna odel of anagng he Fnancal Syem arku K Brunnermeer chael Sockn We Xong Inerne Appendx Th nerne appendx preen proof of he propoon n he man paper Proof of Propoon A We dere he perfec nformaon equlbrum

More information

Appendix H: Rarefaction and extrapolation of Hill numbers for incidence data

Appendix H: Rarefaction and extrapolation of Hill numbers for incidence data Anne Chao Ncholas J Goell C seh lzabeh L ander K Ma Rober K Colwell and Aaron M llson 03 Rarefacon and erapolaon wh ll numbers: a framewor for samplng and esmaon n speces dversy sudes cology Monographs

More information

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy Arcle Inernaonal Journal of Modern Mahemacal Scences, 4, (): - Inernaonal Journal of Modern Mahemacal Scences Journal homepage: www.modernscenfcpress.com/journals/jmms.aspx ISSN: 66-86X Florda, USA Approxmae

More information

Discrete time approximation of decoupled Forward-Backward SDE with jumps

Discrete time approximation of decoupled Forward-Backward SDE with jumps Dscree me approxmaon of decoupled Forward-Backward SD wh jumps Bruno Bouchard, Romuald le To ce hs verson: Bruno Bouchard, Romuald le Dscree me approxmaon of decoupled Forward-Backward SD wh jumps Sochasc

More information

Track Properities of Normal Chain

Track Properities of Normal Chain In. J. Conemp. Mah. Scences, Vol. 8, 213, no. 4, 163-171 HIKARI Ld, www.m-har.com rac Propes of Normal Chan L Chen School of Mahemacs and Sascs, Zhengzhou Normal Unversy Zhengzhou Cy, Hennan Provnce, 4544,

More information

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he

More information

Scattering at an Interface: Oblique Incidence

Scattering at an Interface: Oblique Incidence Course Insrucor Dr. Raymond C. Rumpf Offce: A 337 Phone: (915) 747 6958 E Mal: rcrumpf@uep.edu EE 4347 Appled Elecromagnecs Topc 3g Scaerng a an Inerface: Oblque Incdence Scaerng These Oblque noes may

More information

How about the more general "linear" scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )?

How about the more general linear scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )? lmcd Lnear ransformaon of a vecor he deas presened here are que general hey go beyond he radonal mar-vecor ype seen n lnear algebra Furhermore, hey do no deal wh bass and are equally vald for any se of

More information

A-posteriori estimates for backward SDEs

A-posteriori estimates for backward SDEs A-poseror esmaes for backward SDEs Chrsan Bender 1, Jessca Sener 1 Aprl 4, 01 Suppose an approxmaon o he soluon of a backward SDE s pre-compued by some numercal algorhm. In hs paper we provde a-poseror

More information

arxiv: v5 [math.pr] 31 Mar 2015

arxiv: v5 [math.pr] 31 Mar 2015 STOCHASTIC CONTROL REPRESENTATIONS FOR PENALIZED BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS GECHUN LIANG arxv:132.48v5 [mah.pr 31 Mar 215 Absrac. Ths paper shows ha penalzed backward sochasc dfferenal

More information

Tight results for Next Fit and Worst Fit with resource augmentation

Tight results for Next Fit and Worst Fit with resource augmentation Tgh resuls for Nex F and Wors F wh resource augmenaon Joan Boyar Leah Epsen Asaf Levn Asrac I s well known ha he wo smple algorhms for he classc n packng prolem, NF and WF oh have an approxmaon rao of

More information

On the numerical treatment ofthenonlinear partial differentialequation of fractional order

On the numerical treatment ofthenonlinear partial differentialequation of fractional order IOSR Journal of Mahemacs (IOSR-JM) e-iss: 2278-5728, p-iss: 239-765X. Volume 2, Issue 6 Ver. I (ov. - Dec.26), PP 28-37 www.osrjournals.org On he numercal reamen ofhenonlnear paral dfferenalequaon of fraconal

More information

2/20/2013. EE 101 Midterm 2 Review

2/20/2013. EE 101 Midterm 2 Review //3 EE Mderm eew //3 Volage-mplfer Model The npu ressance s he equalen ressance see when lookng no he npu ermnals of he amplfer. o s he oupu ressance. I causes he oupu olage o decrease as he load ressance

More information

Discrete Time Approximation and Monte-Carlo Simulation of Backward Stochastic Differential Equations

Discrete Time Approximation and Monte-Carlo Simulation of Backward Stochastic Differential Equations Dscree Tme Approxmaon and Mone-Carlo Smulaon of Backward Sochasc Dfferenal Equaons Bruno Bouchard Unversé Pars VI, PMA, and CREST Pars, France bouchard@ccrjusseufr Nzar Touz CREST Pars, France ouz@ensaefr

More information

Relative controllability of nonlinear systems with delays in control

Relative controllability of nonlinear systems with delays in control Relave conrollably o nonlnear sysems wh delays n conrol Jerzy Klamka Insue o Conrol Engneerng, Slesan Techncal Unversy, 44- Glwce, Poland. phone/ax : 48 32 37227, {jklamka}@a.polsl.glwce.pl Keywor: Conrollably.

More information

Variants of Pegasos. December 11, 2009

Variants of Pegasos. December 11, 2009 Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on

More information

Existence of Time Periodic Solutions for the Ginzburg-Landau Equations. model of superconductivity

Existence of Time Periodic Solutions for the Ginzburg-Landau Equations. model of superconductivity Journal of Mahemacal Analyss and Applcaons 3, 3944 999 Arcle ID jmaa.999.683, avalable onlne a hp:www.dealbrary.com on Exsence of me Perodc Soluons for he Gnzburg-Landau Equaons of Superconducvy Bxang

More information

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s Ordnary Dfferenal Equaons n Neuroscence wh Malab eamples. Am - Gan undersandng of how o se up and solve ODE s Am Undersand how o se up an solve a smple eample of he Hebb rule n D Our goal a end of class

More information

F-Tests and Analysis of Variance (ANOVA) in the Simple Linear Regression Model. 1. Introduction

F-Tests and Analysis of Variance (ANOVA) in the Simple Linear Regression Model. 1. Introduction ECOOMICS 35* -- OTE 9 ECO 35* -- OTE 9 F-Tess and Analyss of Varance (AOVA n he Smple Lnear Regresson Model Inroducon The smple lnear regresson model s gven by he followng populaon regresson equaon, or

More information

Motion of Wavepackets in Non-Hermitian. Quantum Mechanics

Motion of Wavepackets in Non-Hermitian. Quantum Mechanics Moon of Wavepaces n Non-Herman Quanum Mechancs Nmrod Moseyev Deparmen of Chemsry and Mnerva Cener for Non-lnear Physcs of Complex Sysems, Technon-Israel Insue of Technology www.echnon echnon.ac..ac.l\~nmrod

More information

John Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany

John Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany Herarchcal Markov Normal Mxure models wh Applcaons o Fnancal Asse Reurns Appendx: Proofs of Theorems and Condonal Poseror Dsrbuons John Geweke a and Gann Amsano b a Deparmens of Economcs and Sascs, Unversy

More information

. The geometric multiplicity is dim[ker( λi. number of linearly independent eigenvectors associated with this eigenvalue.

. The geometric multiplicity is dim[ker( λi. number of linearly independent eigenvectors associated with this eigenvalue. Lnear Algebra Lecure # Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons

More information

Generalized Snell envelope and BSDE With Two general Reflecting Barriers

Generalized Snell envelope and BSDE With Two general Reflecting Barriers 1/22 Generalized Snell envelope and BSDE Wih Two general Reflecing Barriers EL HASSAN ESSAKY Cadi ayyad Universiy Poly-disciplinary Faculy Safi Work in progress wih : M. Hassani and Y. Ouknine Iasi, July

More information

Fundamentals of PLLs (I)

Fundamentals of PLLs (I) Phae-Locked Loop Fundamenal of PLL (I) Chng-Yuan Yang Naonal Chung-Hng Unvery Deparmen of Elecrcal Engneerng Why phae-lock? - Jer Supreon - Frequency Synhe T T + 1 - Skew Reducon T + 2 T + 3 PLL fou =

More information

Modern Dynamic Asset Pricing Models

Modern Dynamic Asset Pricing Models Modern Dynamc Asse Prcng Models Lecure Noes 2. Equlbrum wh Complee Markes 1 Pero Verones The Unversy of Chcago Booh School of Busness CEPR, NBER 1 These eachng noes draw heavly on Duffe (1996, Chapers

More information

Algorithmic Discrete Mathematics 6. Exercise Sheet

Algorithmic Discrete Mathematics 6. Exercise Sheet Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap

More information

A numerical scheme for backward doubly stochastic differential equations

A numerical scheme for backward doubly stochastic differential equations Bernoull 191, 213, 93 114 DOI: 1.315/11-BEJ391 A numercal scheme for backward doubly sochasc dfferenal equaons AUGUSTE AMAN UFR Mahémaques e Informaque, Unversé de Cocody, BP 582 Abdjan 22, Côe d Ivore.

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signal & Syem Prof. Mark Fowler Noe Se #27 C-T Syem: Laplace Tranform Power Tool for yem analyi Reading Aignmen: Secion 6.1 6.3 of Kamen and Heck 1/18 Coure Flow Diagram The arrow here how concepual

More information

The Pricing of Basket Options: A Weak Convergence Approach

The Pricing of Basket Options: A Weak Convergence Approach The Prcng of Baske Opons: A Weak Convergence Approach Ljun Bo Yongjn Wang Absrac We consder a lm prce of baske opons n a large porfolo where he dynamcs of baske asses s descrbed as a CEV jump dffuson sysem.

More information

. The geometric multiplicity is dim[ker( λi. A )], i.e. the number of linearly independent eigenvectors associated with this eigenvalue.

. The geometric multiplicity is dim[ker( λi. A )], i.e. the number of linearly independent eigenvectors associated with this eigenvalue. Mah E-b Lecure #0 Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons are

More information

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,

More information

A Deza Frankl type theorem for set partitions

A Deza Frankl type theorem for set partitions A Deza Frankl ype heorem for se parons Cheng Yeaw Ku Deparmen of Mahemacs Naonal Unversy of Sngapore Sngapore 117543 makcy@nus.edu.sg Kok Bn Wong Insue of Mahemacal Scences Unversy of Malaya 50603 Kuala

More information

Lower and Upper Approximation of Fuzzy Ideals in a Semiring

Lower and Upper Approximation of Fuzzy Ideals in a Semiring nernaional Journal of Scienific & Engineering eearch, Volume 3, ue, January-0 SSN 9-558 Lower and Upper Approximaion of Fuzzy deal in a Semiring G Senhil Kumar, V Selvan Abrac n hi paper, we inroduce he

More information

SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β

SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β SARAJEVO JOURNAL OF MATHEMATICS Vol.3 (15) (2007), 137 143 SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β M. A. K. BAIG AND RAYEES AHMAD DAR Absrac. In hs paper, we propose

More information

FI 3103 Quantum Physics

FI 3103 Quantum Physics /9/4 FI 33 Quanum Physcs Aleander A. Iskandar Physcs of Magnesm and Phooncs Research Grou Insu Teknolog Bandung Basc Conces n Quanum Physcs Probably and Eecaon Value Hesenberg Uncerany Prncle Wave Funcon

More information

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he

More information

Outline. GW approximation. Electrons in solids. The Green Function. Total energy---well solved Single particle excitation---under developing

Outline. GW approximation. Electrons in solids. The Green Function. Total energy---well solved Single particle excitation---under developing Peenaon fo Theoecal Condened Mae Phyc n TU Beln Geen-Funcon and GW appoxmaon Xnzheng L Theoy Depamen FHI May.8h 2005 Elecon n old Oulne Toal enegy---well olved Sngle pacle excaon---unde developng The Geen

More information

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair TECHNI Inernaonal Journal of Compung Scence Communcaon Technologes VOL.5 NO. July 22 (ISSN 974-3375 erformance nalyss for a Nework havng Sby edundan Un wh ang n epar Jendra Sngh 2 abns orwal 2 Deparmen

More information

Research Article Governance Mechanism for Global Greenhouse Gas Emissions: A Stochastic Differential Game Approach

Research Article Governance Mechanism for Global Greenhouse Gas Emissions: A Stochastic Differential Game Approach Hndaw Publhng Corporaon Mahemacal Problem n Engneerng Volume 3, Arcle ID 3585, 3 page hp://dx.do.org/.55/3/3585 Reearch Arcle Governance Mechanm for Global Greenhoue Ga Emon: A Sochac Dfferenal Game Approach

More information

Robust and Accurate Cancer Classification with Gene Expression Profiling

Robust and Accurate Cancer Classification with Gene Expression Profiling Robus and Accurae Cancer Classfcaon wh Gene Expresson Proflng (Compuaonal ysems Bology, 2005) Auhor: Hafeng L, Keshu Zhang, ao Jang Oulne Background LDA (lnear dscrmnan analyss) and small sample sze problem

More information

Econ107 Applied Econometrics Topic 5: Specification: Choosing Independent Variables (Studenmund, Chapter 6)

Econ107 Applied Econometrics Topic 5: Specification: Choosing Independent Variables (Studenmund, Chapter 6) Econ7 Appled Economercs Topc 5: Specfcaon: Choosng Independen Varables (Sudenmund, Chaper 6 Specfcaon errors ha we wll deal wh: wrong ndependen varable; wrong funconal form. Ths lecure deals wh wrong ndependen

More information

Risky Swaps. Munich Personal RePEc Archive. Gikhman, Ilya Independent Research. 08. February 2008

Risky Swaps. Munich Personal RePEc Archive. Gikhman, Ilya Independent Research. 08. February 2008 MPR Munch Peronal RePEc rchve Ry Swap Ghman Ilya Independen Reearch 8. February 28 Onlne a hp://mpra.ub.un-muenchen.de/779/ MPR Paper o. 779 poed 9. February 28 / 4:45 Ry Swap. Ilya Ghman 677 Ivy Wood

More information

Optimal Filtering for Linear Discrete-Time Systems with Single Delayed Measurement

Optimal Filtering for Linear Discrete-Time Systems with Single Delayed Measurement 378 Hong-Guo Inernaonal Zhao, Journal Huan-Shu of Conrol, Zhang, Auomaon, Cheng-Hu an Zhang, Syem, an vol. Xn-Mn 6, no. Song 3, pp. 378-385, June 28 Opmal Flerng for Lnear Dcree-me Syem h Sngle Delaye

More information