Continuous-time evolutionary stock and bond markets with time-dependent strategies

Size: px
Start display at page:

Download "Continuous-time evolutionary stock and bond markets with time-dependent strategies"

Transcription

1 Afcan Jounal of Busness Managemen Vol. 64 pp Febuay Avalable onlne a hp:// DOI:.5897/AJBM.5 ISSN Acaemc Jounals Full Lengh Reseach Pape Connuous-me evoluonay soc an bon maes wh me-epenen saeges Zhaojun Yang * an Feng Sh School of Fnance an Sascs Hunan Unvesy Changsha 479 P. R. Chna. Busness school Bejng Insue of Peochemcal echnology 6 P. R. Chna. Accepe Sepembe hs pape evelops a geneal connuous-me evoluonay fnance moel wh me-epenen saeges base on evoluonay game heoy. We show ha he connuous moel whch s a lm of a geneal scee moel s well-efne an f hee exss one compleely vesfe saegy n he mae hen hee s no suen banupcy. We suy n eal a eemnsc evoluonay bon mae an cefy ha a bon mae s evoluonay sable f an only f he oal euns acoss all asses ae he same. By hs way we eve an explc expesson fo he bon valuaon an pove an appoach o ecove he benchma nees ae fom an effecve bon mae. ey wos: Evoluonay fnance evoluonay bon mae connuous-me moel me-epenen saeges. INRODUCION he Dawnan pncple "Suvval of he Fes" s well nown o evoluonay bologss bu ahe less nown fo s applcably n fnancal mae heoy. Howeve hs majo pncple as apple o fnancal maes means nohng else ha hose aes wh he mos successful ang saeges wll omnae he mae a las afe an evoluonay pocess has aen place. hs evoluonay pocess can be unesoo as a pocess of aapaon an maon ahe han a pocess of nheance n evoluonay bology. Fom an evoluonay pon he mae s compleely eemne by he coesponng evoluonay sable ang saegy. Evoluonay fnancal mae moels have been consee n Blume an Easley 99 Evsgneev e al. 6 an Fame an Lo 999. he man pon n seng up an evoluonay fnancal mae moel s he specfcaon of an evoluonay ynamc whch eemnes he mae shaes of he elevan ang saeges n me. In geneal such a ynamc wll epen on he sochasc payoffs vens o pces of he unelyng asses as well as he ang saeges whch ae assume o be aape o he unelyng nfomaon. he moels evelope by Evsgneev e al. 6 an *Coesponng auho. E-mal: zjyang@hnu.eu.cn. el: Hens an Schen-Hoppé 5 assume ha sochasc vens o payoffs of he unelyng asses ae exogenously gven bu ha n conas o ohe moels he asse pces ae eemne by he ang saeges an a mae cleang conon. hs pape employs a smla appoach as n Evsgneev e al. 6 an Hens an Schen-Hoppé 5 bu ses up a moel n connuous me ahe han n scee me. he choce of connuous me bngs wh he usual echncal poblems whch le n he analycal fomulaon of he moel n pacula n a pobablsc famewo bu has he majo benef. In pacula he mehos fom classcal analyss such as PDE an sochasc calculus become applcable an pove poweful ools fo he soluon of poblems. I s heefoe necessay o exen scee me evoluonay Evsgneev e al. s 6 fnance moels o connuous me famewo. As a fs sep no hs econ Yang an Ewal 8 conse a moel n whch he ang saeges ae assume o be fx-mx ha s he elave buge facons ae consan n me. In hs moel Yang an Ewal 8 se up a connuous me sochasc ynamc whch escbes he evoluon of mae shaes n a populaon of fnely many ang saeges. Yang an Ewal 8 enfy evoluonay sable nvesmen saeges ha s hose saeges ha peven enans o he fnancal mae fom ganng wealh n he long

2 464 Af. J. Bus. Manage. un. Une he assumpon ha he elave vens ae fs-oe saonay an egoc Yang an Ewal 8 eve an evoluonay sable nvesmen ule. Fx saeges ae smple an also suable n some economc envonmens bu ae of couse oo escve. Along hs eseach lne Buchmann an Webe 7 eve a connuous me appoxmaon of he evoluonay mae selecon moel of Blume an Easley 99. Conons on he payoff sucue of he asses ae enfe ha guaanee convegence. I s shown ha he connuous me appoxmaon equals he soluon of an negal equaon n a anom envonmen. Fo consan asse euns he long-un asympoc behavo s scusse n eal. Howeve he pape by Buchmann an Webe 7 s subsanally smple han wha sue n hs pape. Fs Buchmann an Webe 7 conse a mae wh only sho-lve asses an hus capal gans ae ome whch s much less neesng. Seconly o guaanee convegence Buchmann an Webe 7 mpose an unnaual conon on he payoff sucue of he asses an so scly speang s connuous-me moel s no a lm of he moel of Blume an Easley 99. Lasly he assumpon of consan asse euns whch s much smple han he one suppose by hs pape s exemely escve an hus s saeges ae fx o me-nvaan as well. ang a sep fuhe no he connuous evoluonay fnance moel hs pape conses a moel n whch saeges ae me-epenen ahe han me-nvaan. A connuous me appoxmaon of he evoluonay mae selecon of a geneal scee-me moel s fs eve whch s a genealzaon of Evsgneev e al. 6. I s shown ha he connuous moel s well-efne an only f one of he saeges s compleely vesfe - hs conon almos mposes no escveness hee s no suen banupcy n he mae. Seconly a bon mae s sue n whch he ven pocess pa by each asse s eemnsc an pces an wealh vay ue o mae neacon. I s cefe ha a bon mae s evoluonay sable f an only f all he oal euns of bons efne n hs pape ae equal o each ohe alhough he same oal eun may change along he me. Any ohe mae can be nvae jus by a pofolo ha nvess all wealh n an asse whch pays off he lages oal eun. When nouce on he mae wh abaly small nal wealh hs pofolo nceases s mae shae a he ncumben s expense. By hs way he necessay an suffcen conons ae eve fo he evoluonay sable pofolo ule. I s shown ha a bon mae s evoluonay sable f an only f each bon s evaluae In a me-epenen saegy he facon of he emanng wealh afe consumpon whch he saegy assgns o he puchase of an asse n one peo may change wh me. On he conay n a fx me-nvaan o me-nepenen saegy he facon mus eep unchange. Of couse he me-epenen saegy s much moe easonable han he lae. by an mpope negal n whch he negan s a scoune value of he ven payoff wh he scoun ae beng mae consumpon paamee. A fomula s pove o evaluae he scoun ae o he mae consumpon ae base on he ang pces n a elave effecve bon mae. By hs way an appoach o compue benchma nees ae s pesene. he sucue of he acle s as follows. hs suy ses up a geneal scee-me mae selecon ynamc whee he lengh of he ang me neval s abaly posve. hen a connuous-me evoluonay soc mae moel s eve an scusse. Fuhemoe nvesgaes an evoluonay bon mae n whch he ven pocess s eemnsc afe whch wo fomulas o pce bons wee pove an he benchma nees ae was ecovee especvely. Fnally he man conclusons of hs pape ae summaze. CONINUOUS-IME MARE SELECION PROCESS WIH IME-DEPENDEN SRAEGIES Followng Lucas 978 hs pape nouces an nfne hozon asse mae moel. Fs a scee mae moel s esablshe wh an abay ang neval an hen a geneal connuous-me moel s eve by ang a lm of ha he ang neval conveges o zeo. Le Ω F P be a pobably space enowe wh F s an nfomaon he flaon F whee flaon fo mae pacpans up o me. All anom vaables an sochasc pocesses n hs pape wll be efne on hs base. Conse an asse mae wh long-lve asses an a sngle peshable consumpon goo. he asses ae nexe by Λ { L }. me s scee an enoe by Π { l l = L} whee s he lengh of he me neval. In hs mae hee ae fnely many playes nvesos an each playe plays one saegy. All playes o saeges nexe by = L I I compee wh each ohe fo he mae capal an he amoun of he wealh manage by saegy s F aape an enoe by w = L I. Each asse pays off a ven n cash o jus a sngle peshable consumpon goo as mple by Lucas 978. As seen fuhe whehe he ven s cash o goo oes no mae only f s suppose o be oally consume. he amoun of he ven pa by asse a peo s F aape an enoe by D. In hs pape he followng assumpon s mpose: Assumpon : All saeges have a common consumpon ae a each peo enoe by c

3 Yang an Sh 465 whch s F aape sasfyng < c < Π. he assumpon on common consumpon ae s obvously necessay n oe o compae pefomances among saeges snce one of he ams of he pape s o suy wha saegy wll omnae he mae a las. If on he conay he consumpon ae s ffeen hen he saegy omnaes he mae pobably also because consumes less. Moeove he assumpon ha < c < says evey saegy o playe mus consume a a scly posve consumpon ae a each peo bu s no peme o consume all hs wealh. Denoe by he facon of he emanng wealh afe consumpon w c whch saegy assgns o he puchase of he asse n peo. Fomally a saegy s a sochasc pocess whch s F aape. Fuhe he nex assumpon s mae: Assumpon : Fo evey saegy he facon nvese n each asse s F aape an non-negave ha s fo almos evey sample pah an all. hee s a leas one compleely vesfe saegy ha s gven ha Π o fo he j L I wh connuous me moel hee s a { } j w > such ha < < fo almos evey sample j pah an all. Assumpon means ha sho sellng s pohbe hough whch s que possbly unnecessay o ge he man conclusons of hs pape. Meanwhle Assumpon also maes sue ha he pces of all asses ae scly posve hans o equaon whch s acually jus he eason why s assume. In hs famewo all he asses ae jus long-lve asses whch pay off vens n cash o pouce he same peshable consumpon goo say ml. he cash o peshable consumpon goo ae consume compleely an especally can no be use o enves. Fo hs eason he oal amoun of asses ae n he mae eeps consan. On accoun of a soc spl he followng assumpon s mpose whou loss of genealy: Assumpon 3: he supply of each asse s nomalze o. Accong o hs assumpon he mae-cleang pce enoe by ρ s gven by: I = ρ = w c. Denoe he aggegae mae wealh by W ha s I W = w hen he mae-cleang pce of = consumpon goo o cash enoe by eemne by: ρ ρ Π s W c = D whee D s he aggegae ven ha s D = D. In conas o Evsgneev e al. = 6 ae a nomalze pce fo cash ha s Followng hs s wen as ρ. W c = D whch s howeve a b moe afcal alhough he ffeence s no mpoan.. Fo a gven saegy pofle an he Le Λ { L } wealh w = L I he pecenage of all shaes ssue of asse ha saegy nvess ung peo s: π w = Π Λ. I j j j w = I s even ha: I π = = 3 = =. 4 Snce he change of a wealh esuls only fom vens an capal gans he wealh of saegy a he begnnng of peo + ha s w + s eemne by: w c w = ρ D + ρ ρ π = o accong o an 3 4 eemne by: w + ρ D ρ π = = +. 6 Whle he oal amoun of asses ae n he mae eeps consan he aggegae mae wealh W oes change wh me because of ang anomly. Howeve socal welfae has evenly no elaon o he level of he 5

4 466 Af. J. Bus. Manage. mae wealh W an a bg W only means hghe pces of he asses an consumpon goo o cash. Acually hee exs nfnely many soluons o he wealh ynamcs 6 snce s by homogeneous fo all wealh vaables ha s w Π = L I. In pacula any soluon mulple by an abay non-zeo numbe s sll a soluon. Fo hs eason an an economc conseaon he aggegae mae wealh W s aen as a numéae n he followng. Base on hs numéae he nomalze pces fo asse an consumpon goo ae p W an ρ p W especvely fo each peo. Fuhe he nomalze wealh o he mae shae of saegy s w W. Accongly follows ecly fom an 3 ha: c p = c = an =. I I π = p = Obvously he mae shae pocess s he mos mpoan nex ha ells how saegy pefoms. Fo example he mae shae pocess eemnes whehe he saegy s omnae o omnang. Consequenly he ynamcs of mae shae pocess s sue fuhe n eal. Smla o Yang an Ewal 8 by an elemenay manpulaon fo all follows fom an 6 ha: I j j + π = j= = c + c whee epesens he elave ven paymen of asse ha s. Equaon 8 s calle D D mae selecon equaon. Obvously hans o 8 f =. In oe o avo hs unneesng case s suppose houghou he pape ha L I. Fuhe > fo each { } s no ffcul o pove ha 8 s well-efne. Fomally he followng heoem hols. heoem Gven a saegy pofle an all he elave ven paymen pocesses { } Π ρ 7 8 Λ an pove ha Assumpon an hol hee exss a pah-wse unque mae shae pocess { } saegy = L I. Poof Π sasfyng 8 fo each A sech of a poof s gven hee Evsgneev e al. 6. In fac hs heoem can be pove by solvng 8 sep by sep fowa. A each sep say peo + 8 s a sysem of I lnea equaons n I vaables ha s { L I} an he coeffcen max can be + pove o be nveble by vefyng ha has a column omnan agonal hans o Assumpon an an 4. hus he heoem s pove. A connuous-me evoluonay fnance moel wh me-epenen saeges s esablshe n he followng by leng n 8. o acheve hs goal moe assumpons ae neee an shown hus: Assumpon 4: Fo all Π Λ { L I} an evey sample pah he followng lms exs an he equales hol: + lm + = lm + = an fuhe lm & 9 houghou hs pape "o" noaon s use fo evaves. Assumpon 4 seems oo escve bu acually no. he fs equaly of he assumpon says he elave ven pocess s connuous as well as sochasc whch escbes he economc phenomenon ha he elave ven changes gaually nsea of suenly. In aon s well-nown ha a connuous-me pofolo n mahemacal fnance s mosly lef connuous wh gh han lms. Consequenly he pofolo s geneally no connuous le alone beng ffeenable. On he conay asse pces n hs seup ae enogenous nsea of exogenous as n mahemacal fnance an hey o change along wh he pofolo. Accongly once a pofolo s pefome he wealh manage by any playes o saeges wll be change n he same me hough a complcae ebalancng pocess fo mae-cleang. hs ebalancng pocess wll mae he amoun of wealh manage by any playes change afe ang whch s oally ffeen fom he self-fnancng ang assume by mahemacal fnance. As a esul evey aleaon of a pofolo wll ncu a song essance fom he mae an he spee of aleaon mpobably ges oo quc - ha s o say he pofolo s alee slowly an hus he ffeenal assumpons n 9 ae also accepable. Followng he seemly songly escve Assumpon 4 he nex assumpon s nuvely easonable:

5 Yang an Sh 467 Assumpon 5: he common consumpon ae fo each playe o saegy s a funcon of he me neval an he followng lms exs fo almos evey sample pah an all Π : c lm c an fuhe lm c =. hs assumpon says ha he longe he me neval he moe he consumpon ae an hee exss an nsananeous spee of he change of he consumpon ae whch s c fo all Π. Now s eay o eve he connuous-me evoluonay fnance moel wh me-epenen saeges. In oe o ge a eep nsgh he followng ex uns o he case I = whch s paculaly mpoan fom evoluonay game heoy. Une hs case only wo saeges compee wh each ohe fo he mae capal an he mae shaes sasfy ha + = fo all Π. Fo hs eason he ynamcs of only one mae shae say Π wll be sue n eal subsequenly he followng heoem s he man concluson of connuous-me mae selecon pocess wh me-epenen saeges n whch s calle connuous-me mae selecon equaon wh me-epenen saeges. heoem Suppose a saegy pofle { } Π = Λ s gven an Assumpon 5 hol: Fo all Π an = < < f an only f < < ; Fo almos evey sample pah: lm = lm = ; Fuhe fo almos evey sample pah he mae shae = s ffeenable an sasfes he followng anom ffeenal equaon: & + & + c = + = + c + = & Poof I suffces o vefy he conclusons abou he mae shae of saegy.fs I follows fom 8 an he case I = ha: c + π + c π = = + + c + c + π + + π = =. 3 As a esul pa of hs heoem s mmeaely pove hans o he assumpons of he heoem an: + = Π. 4 Fom 4 an 7 s conclue ha: π π π = = = + = + =. Consequenly one ges ha: π + π + = = = c + c + π + + π = c c =. 6 Nex le he me neval shn o zeo ha s hen by 9 an 4 he numeao conveges o zeo an he enomnao of he gh-han se of 6 conveges o: + = >. π π = = = + 7 Accongly he secon equaly of s eve. Fuhemoe one nfes fom 9 an 6 ha: c π π + + & = = = lm = + & = =. heefoe pa of he heoem s shown afe a smple subsuon fom 7. Mae selecon equaon ffes fom Iô Sochasc ffeenal equaon snce s negal can be wh nal value whle & = &. We only gve a sho poof fom nuon hee. Recenly Palczews an Schen-Hoppé pove a sc poof fo almos he same concluson.

6 468 Af. J. Bus. Manage. efne pah by pah as a Remann negal. emonsaes explcly ha he evoluon of each mae shae s eemne by all saeges as well as he elave ven an s well efne n he sense ha fo an abay nal value s soluon exss an s pah-wse unque. Wh a vew o povng hs concluson a geneal exsence an unqueness ae shown n he followng. Le: = & & + c + = x x h ω x x + x + x+ c an g ω x xh ω x hen can be equvalenly wen as: x& = g ω x o x& = xh ω x 8 n whch nal value = x = an x x. Geneally speang hee s a pah-wse unque soluon o 8 fo an abay nal value x [ nsea of only = x = [ ]. In oe o ge hs esul he nex assumpon nsea of Assumpon s suffcen: Assumpon 6: he consumpon ae an he evaves of he facon nvese n each asse ae almos suely pah-wse connuous fne an F -aape. ha s o say < c < & < an c & ae connuous funcons of fo all Λ { } an almos evey sample pah. hs assumpon nealy pus no exa escon fom an economc vewpon on accoun of he commens followng Assumpon 4. Now he exsence an unqueness of 8 ae fomally pesene hus. heoem 3 If Assumpon 6 hols fo a gven saegy pofle hen fo x [ an abay nal value wh x + x fo all Λ hee exss a pah-wse unque local soluon of anom ffeenal equaon 8. Poof Accong o he assumpon of he heoem hee s a c null se N F such ha fo evey ω N one can fn an open subse U sasfyng x U [ on whch funcon g ω x s Lpschz connuous n he h agumen unfomly wh espec o he fs fo moe eals efe o he poof of heoem 4 below. Hence he heoem s pove hans o he well-nown Pca-Lnelöf heoem. Base on heoem 3 an Assumpon he exsence an unqueness of mae selecon equaon ae scusse nex an a moe nsghful esul s summe up n he followng. heoem 4 Fo a gven saegy pofle Assumpon an 6 hol: < < = hee Fo an abay nal value exss a pah-wse unque soluon of mae selecon equaon whch sasfes < < = fo all > ; Fo almos evey sample pah f = hen = fo = an ; f = hen = fo = an. Poof Accong o heoem 3 pa of he heoem s obvous an hus whou loss of genealy only pa fo = s shown n he followng. can be wen as: & = g ω o & = h ω 9 wh nal value < <. hans o heoem 3 an pa of he heoem he phase space of 9 s nclue n he neval [ ] fo an abay nal value < <. Fs hee exss a posve > such ha hee s a pah-wse unque soluon of he nal value poblem 9 fo a gven sample pah up o owng o heoem 3 an n pacula < < can be [ guaanee fo. Seconly he neval s exene as we as possble n he followng way. Fo a gven saegy pofle an an abay posve nege n efne soppng me: n ω nf Λ s.. < + < n o max{ c } } & & > n

7 Yang an Sh 469 whee he nfmum of he empy se s unesoo o be. Noe ha fo all x [ ] an < ω n + an mn{ } max{ } n x + x mn{ } x x max{ } an hus follows fom a lenghy bu elemenay calculaon ha fo all x [ ] < n ω an ω Ω 4 3 f x < 6n an h x > n. x ω Fo hs eason hee exss a pah-wse unque soluon of 9 up o by means of exensbly n ω of soluons. Moeove accong o he secon equaly of 9 he soluon sasfes: ω ω u = exp h u u > exp n u > 3 fo ha n ω. On he ohe han s even n < snce + = an one can also show > n he same way. Lasly can be vefe ha lm n n ω = a. s.. In fac f hee s a measuable se A F wh P A > such ha lm n n ω = τ ω < fo all ω A hen hee exss Λ an { } such ha + = o = o τ ω τ ω τ ω τ ω & = fo all ω A τ ω c τ ω. he las wo equales conac Assumpon 6 an he fs equaly leas o τ ω = ha s τ ω =.e. w τ ω = an w τ ω = an = o τ ω τ ω = whch conacs Assumpon. Hence he poof s fnshe. I follows ecly fom heoem 4 ha f one of he saeges s compleely vesfe hen hee s no suen eah o banupcy n he economy even some saeges ae no compleely vesfe. Fo example suppose n a mae hee ae only wo asses: One pays an anohe pays nohng all he me ha s = an = especvely. he c c >. consumpon paamee s consan.e. Saegy s compleely vesfe wh µ = an = µ < µ < all he me bu saegy s no wh = an =. Saegy s clealy vey ba snce nvess all he wealh n asse whch pays nohng all he me. Howeve he ba saegy wll no go banup foeve only f s nal wealh s scly posve ha s < <. In fac a smple calculaon leas o: µ exp c = > fo all + exp µ µ c alhough lm = an hus lm = ha s saegy omnaes he mae a las. EVOLUIONARY SABLE BOND MARE Mae selecon equaon s a ahe geneal connuous-me evoluonay fnance moel n whch s ffcul o answe wha s he "opmal" saegy snce he saeges ae me-epenen n a sochasc envonmen. In oe o avo a oo complex poblem suenly whle suyng hs geneal moel Yang an Ewal 8 eal wh he case of consan popoons saeges hough n a sochasc wol whch s subsanally smple han he geneal moel esablshe n subsequenly. Fo he same eason neveheless fom anohe pon of vew he followng ex focuses on a eemnsc bon mae bu eeps he saeges me-epenen. By a eemnsc bon mae we mean nohng ohe han he mae scusse above n whch he elave ven pocess s a eemnsc funcon of me. Whle funamenals ae fxe pces an wealh vay ue o mae neacon. hs mae appeas oo escve bu n fac nclues a vaey of maeable easuy secues ssue by he Une Saes Depamen of he easuy hough he Bueau of he Publc Deb: easuy blls easuy noes easuy bons an easuy Inflaon Poece Secues IPS. hs mae also nclues Accoun easuy bons ssue by he Chna Depamen of Fnance whch wee fs ssue n 997 bu he amoun nceases wh an exemely quc spee. In a eemnsc wol he ven s ece n avance an hus fo a gven saegy pofle s an onay ffeenal equaon. Le: & + & + c c + = + f ;. = +

8 47 Af. J. Bus. Manage. he mae selecon equaon n a eemnsc wol s ewen as: & = f ; an & = &. hee ae obvously only wo fxe pons n ha s an especvely accong o pa of heoem 4. Whou loss of genealy he sably of fxe pon s scusse below. Namely we nvesgae a bon mae whee hee ae wo playes: One s an ncumben o he omnan mae saegy saegy wh an nal mae shae an anohe s a muan saegy wh an nal mae shae. I s ou am o answe whehe he ncumben s evoluonay sable. A fs sgh he assumpon ha hee ae only such wo saeges n a mae seems unealsc bu n fac no. Fo example one can nepe saegy as he mae pofolo an saegy as an abay saegy say one playe by an nvual o even a fnancal nsuon. Fo hs eason whehe he ncumben s evoluonay sable equals o whehe he mae s effecve. An f he ncumben s evoluonay sable hen a "fa pce" of each asse can be eve by he followng 4. Accongly a suy on a mae even wh only such wo saeges can sll lea o a lo of neesng conclusons. I s clea ha he evoluon of s eemne by he sgn of funcon f ;. In pacula f he sgn s posve he mae shae of saegy wll ncease bu ecease on he conay. heefoe he followng efnon s pesene. Defnon : Saegy s calle evoluonay sable f hee exss a posve ε > such ha fo evey saegy say saegy wh an nal mae shae < < ε s mpossble o fn a me neval say a b such ha a b whle f ; > fo f ; fo a b c an ; On he conay saegy s calle evoluonay unsable f hee exss a me neval say a b an a saegy enoe by saegy wh an abay nal mae shae ha < < such f ; > fo a b whle f ; fo a b c an. I follows fom hs efnon ha an ncumben s evoluonay sable f an only f hee s no abage oppouny n he mae. Noe ha a he begnnng of he eny of a muan he mae shaes sasfy an hus he sgn of eemne by s lnea appoxmaon: f ; s f ; c + c +. & = Defnon : Fo a gven ncumben he oal eun of asse s efne by: c + & Γ Λ. Λ; { } 3 Γ s calle he oal eun because compleely eemne he nvesmen value of he asse as seen n Γ s a sum of he he followng heoem 5. In fac capal gan an he ven eun. o mae hs clea ecall 7 an an noe ha. hen one fns: p = + Λ 4 whch means he elave pce of an asse appoxmaely equals o he facon nvese n hs asse by he ncumben. Especally f he mae pofolo s aen as he unque saegy n a mae ha s = all he me hen he elave pce s jus he facon nvese by he mae pofolo accong o 4. I follows fom 4 ha & / p& / p an c / p. Clealy c p p& s a capal gan whle c p epesens a ven eun. 3 says ha he bgge he changng spee c of consumpon ae he moe epenen he oal eun on he elave ven bu he less epenen on he capal gan. Hence explans ha n a socey wh excess consumpon he ven pa by an asse shoul be much moe appecae. heoem 5 Fo a gven ncumben pove ha he oal eun of a mae wh he ncumben s no encal fo all asses a some me hs ncumben s evoluonay unsable. Poof. In fac f a muan nvess all wealh n an asse wh he lages oal eun a fs an hen gaually evse he pofolo o equal o he ncumben hen he muan wll gan he mae. Namely f ; s

9 Yang an Sh 47 scly posve n a small neghbohoo of an eep non-negave all he me. Hence hs heoem s shown fom Defnon. hs heoem means ha a mae s abage-fee only f he oal euns of an ncumben efne by 3 ae he same acoss all asses. o ae one sep fuhe nex we pove ha f he oal euns of an ncumben efne by 3 ae he same acoss all asses hen he ncumben s evoluonay sable.e. he mae s abage-fee: Assumpon 7: Fo a gven ncumben saegy he oal eun efne by 3 s encal fo all asses all he me. hs assumpon also appeas o be oo escve bu as pove n heoem 5 f he assumpon oes no hol hen hee exss an abage oppouny n he mae whch s no neesng o suy also n mahemacal fnance. By vue of Assumpon 7 he value Γ s nepenen of an s heefoe enoe by ν n he followng. Accongly one ges: c + & = ν Λ. 5 Noe ha: = = = = = & =. 6 Aggegang 5 ove asses one fns c c ν = c namely: + & =. 7 Consequenly une Assumpon 7 he lnea appoxmaon n s always zeo whch howeve oes no ecly mean saegy s evoluonay sable. Hence a moe eale analyss of he secon an even hghe oe appoxmaon s necessay. Fo hs pupose a secon-oe appoxmaon of funcon f ; s shown hus: & + c & = ; = + + c 3 f O = 8 whee a funcon h x s sa o be O g x f lm x h x / g x <. Equvalenly fo an abay emnal me one has: & + = + +. c c O = 9 heefoe f he age of a muan s o maxmze s mae shae a a gven emnal me ha s hen he opmal muan followng vaaon poblem: mn ; Λ { } c c = =.. = Λ s s a soluon of he & + 3 whee saegy s consane o be ffeenal accong o Assumpon 4. Regang hs poblem hee exss an ε opmal saegy shown fuhe. heoem 6 Le be a mnmum value of he se ε > { } Λ. hen fo any gven small an ε -opmal soluon o 3 s gven by: = δ ε = ; =. In aon δ ε 3 { Λ } whch passes δ ε an passes δ ε an whch δ ε an ae ffeenable a δ ε an whee δ ε s a suffcenly small posve numbe. he opmal objecve funcon equals o / / + whch can be scly negave snce ε s a suffcenly small posve numbe. Poof I follows fom 7 ha: c c = ε

10 47 Af. J. Bus. Manage. Consequenly applyng he ule fo negaon by pas 3 s equvalen o: mn ; Λ = c c c c + = =.. = Λ. s + 3 Obvously he opmal saegy s myopc. In aon he objecve funcon s quac an he consane conons ae convex. hus hee exss a unque globally opmal soluon o 3. Moe conceely hee opmzaon poblems ae solve below: he fs one s: mn ; Λ = = s.. = Λ n whch hee s a unque global soluon - ha s = Λ an he opmal value of he objecve funcon s /. he secon one s: max ; Λ = = s.. = Λ n whch hee s a unque global soluon - ha s = whle { } = Λ an he opmal value of he objecve funcon s s:. he las one mn ; Λ c c c c + = =.. = Λ s 33 n whch hee s a unque global soluon.e. = Λ an he opmal value of he objecve funcon s zeo. Accongly on accoun of ha he saeges mus be ffeenal he heoem s pove. hs heoem shows ha he opmal muan s almos he same as he ncumben excep ha whle appoachng o he emnal me he muan gaually bu qucly nvess all he wealh n only one asse of whch he facon of he wealh he ncumben assgns o he puchase s mnmum a he emnal me. I s also shown ha he opmal objecve funcon s scly negave. hs mples fom 9 ha he mae shae of he muan s scly nceasng a he emnal me alhough eeps unchange po o he en. Howeve ha oes no epesen he ncumben s evoluonay unsable. o mae hs pon clea one noes ha f he muan plays he ε -opmal saegy gven by 3 he oal eun on asse mus be he smalles among all asses a he emnal me n he new mae pofolo nclung he nvesmen of he muan afe he eny. As a esul Assumpon 7 oes no hol anymoe a me an he only asse he muan puchases has he leas value fo nvesmen snce no aonal nveso wll buy a he puchase pce of he muan accong o heoem 5. Meanwhle f he pofolo of he muan eeps nvaan he gh-han se of s scly negave a leas n a sho peo afe he emnal me an so he muan s mae shae wll scly ecease. Fo example suppose an nsuonal nveso buys an asse on a lage scale ung a sho peo. Unoubely he asse pce wll sho up an hs mae shae wll ncease. Howeve hs phenomenon wll no las long an he pce wll efnely fall. Afewas he wll pobably lose wha he gane. Accongly anohe conon s mpose on saegy playe by he muan. he am s o mae sue ha he new exene mae pofolo afe he eny sasfes Assumpon 7 sll a he emnal me - ha s o say he consan = Λ s ae n he followng. heefoe he vaaon poblem 3 s change no:

11 Yang an Sh 473 mn ; Λ c c = = = s.. Λ = Λ. & + 34 Base on heoem 6 he followng heoem s even an hence he poof s ome. heoem 7 If Assumpon 7 hols hen hee s a unque soluon of 34 whch s gven by: = Λ. 35 he opmal objecve funcon an f ; equal o zeo fo all [ ]. Fo an abay saegy whch s ffeen fom he saegy gven by 35 he objecve funcon an f ; a some me [ ] ae scly negave n a small neghbohoo of. Hence he ncumben sasfyng Assumpon 7 s evoluonay sable. Noce ha he emnal me s abaly selece an n pacula f le hen one conclues 35 hols anyme. heefoe he followng coollay s ec fom heoems 5 an 7: Coollay : An ncumben s evoluonay sable f an only f he pofolo of he ncumben sasfes Assumpon 7. EXPLICI EXPRESSION FOR BOND VALUAION AND BENCHMAR INERES RAE hs scuss poves an expesson fo bon valuaon f he mae s abage-fee. Owng o Defnon a mae s abage-fee f an only f he ncumben ha s he mae pofolo s evoluonay sable o equvalenly f an only f Assumpon 7 hols accong o Coollay. hus hee s suppose ha Assumpon 7 hols. Clealy Assumpon 7 leas o 7 whch yels by negaon: u c u c u c s = exp u exp s u. u o equvalenly: u c u u s c c = exp u + exp s u. u 36 Followng ha he man esul hee s pove subsequenly. heoem 8 A bon mae s evoluonay sable f an only f each bon elave pce s gven by: c s p u = c u exp s u Λ; u 37 On he conay f he bon pces ae collece aleay n an evoluonay sable mae hen he scoun ae consumpon paamee s ecovee by: c = p& p Λ. Poof 38 In hs bon mae he mae pofolo can be consee as he unque saegy say saegy wh. heefoe we conclue fom 4 ha p = fo Λ. Le n 36 hen 37 s eve snce: c uu lm exp =. Lasly 38 follows ecly fom 7 an he equaly p = fo all Λ. Snce p = as shown n he afoe poof he fs pa of he heoem accos wh economc nuon. I says ha n an evoluonay sable bon mae one shoul ve wealh acoss asses accong o he elave asse pces ha s he abage-fee pces whch equal o he scoune values of he elave vens wh he scoun ae jus beng he consumpon paamee c. Howeve he concluson of he secon pa appeas moe neesng. Fo example he benchma nees ae s exemely mpoan n fnance nusy howeve how o fx s open o my bes nowlege. In oe o appoach hs poblem he h pa of heoem 8

12 474 Af. J. Bus. Manage. suggess ha n a elavely effecve ha s evoluonay sable bon mae he elave bon pces ae collece fs an hen he consumpon paamee c ae ecovee by 38. hs paamee shoul be a goo canae fo he benchma nees ae. CONCLUSIONS hs pape evelops a connuous-me evoluonay fnance moel wh me-epenen saeges fom whch an evoluonay sable bon mae s sue. Fs a geneal scee-me evoluonay fnance s esablshe wh an abay ang me neval. A connuous-me moel s eve by leng he me neval convege o zeo. I s shown ha he connuous-me moel s well-efne an hee s no suen banupcy n he geneal mae only f all he asse pces eep posve. Secon as a specal case of he geneal moel a bon mae wh eemnsc ven payoffs s scusse n eal. hs bon mae s no so afcal as one may conse a fs sgh snce nclues a vaey of maeable easuy secues say easuy blls easuy noes easuy bons an easuy Inflaon Poece Secues IPS ssue by he Une Saes Depamen of he easuy. hs mae also nclues Accoun easuy bons ssue by he Chna Depamen of Fnance. I s cefe ha a bon mae s evoluonay sable whch mples he mae s abage-fee f an only f he oal eun of each asse n he mae s encal all he me. Fuhe he abage-fee pce of each bon s eve whch equals an mpope negal wh he negan beng a scoune value of he ven payoff. he scoun ae s encal fo all bons an equals he mae consumpon paamee. o my bes nowlege hee s no an accepe appoach o evaluae he scoun ae o he benchma nees ae alhough hs ae s val fo asse pcng. Equaon 38 a leas poves a new aemp o aac hs poblem. Fo example f one ges bon pces n a elavely effecve o evoluonay sable bon mae hen he scoun ae o he benchma nees ae can be ecovee fom 38. In pacula along hs eseach lne mus be vey neesng o have hs moel ese wh mae aa. Snce hs s no a smple wo an wll lea o anohe pape so we leave n fuue eseach. Fnally alhough a geneal connuous-me evoluonay soc mae wh me-epenen saeges s esablshe n hs pape we afewas focus on an evoluonay bon mae n whch he funamenals ae eemnsc an boh pces an wealh vay ue o mae neacon. Clealy a pofoun suy on connuous-me evoluonay soc mae n a sochasc wol s moe neesng an of couse moe challengng. hs wo s also lef n fuue eseach. ACNOWLEDGEMENS he eseach fo hs pape was suppoe by Socal Scence Funs of Hunan Povnce n Chna Pojec No. YBA58 by Naonal Naual Scence Founaon of Chna Pojec No an No an by Docoal Fun of Mnsy of Eucaon of Chna Pojec No. 6. I am gaeful o Pofesso laus Rene Schen-Hoppé an Pofesso Ja an Yan. hs pape was nae by Pofesso Schen-Hoppé whle I vse he Unvesy of Lees n 5 an he man wo was one whle I vse Chnese Acaemy of Scences n 7. A subsanal evson s mae n hs veson an all emanng eos ae mne. he auhos ae gaeful o he anonymous efeee fo he commens. REFERENCES Blume L Easley D 99. Evoluon an mae behavo. J. Econ. heoy 58: 9-4. Buchmann B Webe S 7. A connuous me appoxmaon of an evoluonay soc mae moel. In. J. heoecal Appl. Fnance : Evsgneev IV Hens Schen-Hoppé R 6. Evoluonay sable soc maes. Econ. heoy 7: Fame JD Lo W 999. Fones of fnance: evoluon an effcen maes. Poceengs of he Naonal Acaemy of Scences 96: Hens Schen-Hoppé R 5. Evoluonay sably of pofolo ules n ncomplee maes. J. Mah. Econ. 4: Lucas R 978. Asse pces n an exchange economy. Economeca 46: Yang ZJ Ewal CO 8. Connuous me evoluonay mae ynamcs: he case of fx-mx saeges. Inves. Manage. Fnan. Innov. 5: 34-4.

FIRMS IN THE TWO-PERIOD FRAMEWORK (CONTINUED)

FIRMS IN THE TWO-PERIOD FRAMEWORK (CONTINUED) FIRMS IN THE TWO-ERIO FRAMEWORK (CONTINUE) OCTOBER 26, 2 Model Sucue BASICS Tmelne of evens Sa of economc plannng hozon End of economc plannng hozon Noaon : capal used fo poducon n peod (decded upon n

More information

1 Constant Real Rate C 1

1 Constant Real Rate C 1 Consan Real Rae. Real Rae of Inees Suppose you ae equally happy wh uns of he consumpon good oday o 5 uns of he consumpon good n peod s me. C 5 Tha means you ll be pepaed o gve up uns oday n eun fo 5 uns

More information

University of California, Davis Date: June xx, PRELIMINARY EXAMINATION FOR THE Ph.D. DEGREE ANSWER KEY

University of California, Davis Date: June xx, PRELIMINARY EXAMINATION FOR THE Ph.D. DEGREE ANSWER KEY Unvesy of Calfona, Davs Dae: June xx, 009 Depamen of Economcs Tme: 5 hous Mcoeconomcs Readng Tme: 0 mnues PRELIMIARY EXAMIATIO FOR THE Ph.D. DEGREE Pa I ASWER KEY Ia) Thee ae goods. Good s lesue, measued

More information

Name of the Student:

Name of the Student: Engneeng Mahemacs 05 SUBJEC NAME : Pobably & Random Pocess SUBJEC CODE : MA645 MAERIAL NAME : Fomula Maeal MAERIAL CODE : JM08AM007 REGULAION : R03 UPDAED ON : Febuay 05 (Scan he above QR code fo he dec

More information

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( )

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( ) 5-1. We apply Newon s second law (specfcally, Eq. 5-). (a) We fnd he componen of he foce s ( ) ( ) F = ma = ma cos 0.0 = 1.00kg.00m/s cos 0.0 = 1.88N. (b) The y componen of he foce s ( ) ( ) F = ma = ma

More information

New Stability Condition of T-S Fuzzy Systems and Design of Robust Flight Control Principle

New Stability Condition of T-S Fuzzy Systems and Design of Robust Flight Control Principle 96 JOURNAL O ELECRONIC SCIENCE AND ECHNOLOGY, VOL., NO., MARCH 3 New Sably Conon of -S uzzy Sysems an Desgn of Robus lgh Conol Pncple Chun-Nng Yang, Ya-Zhou Yue, an Hu L Absac Unlke he pevous eseach woks

More information

Comparative Study of Inventory Model for Duopolistic Market under Trade Credit Deepa H Kandpal *, Khimya S Tinani #

Comparative Study of Inventory Model for Duopolistic Market under Trade Credit Deepa H Kandpal *, Khimya S Tinani # Inenaonal Jounal of Saska an Mahemaka ISSN: 77-79 E-ISSN: 49-865 Volume 6 Issue pp -9 ompaave Suy of Invenoy Moel fo Duopolsc Make une ae e Deepa H Kanpal * Khmya S nan # Depamen of Sascs Faculy of Scence

More information

I-POLYA PROCESS AND APPLICATIONS Leda D. Minkova

I-POLYA PROCESS AND APPLICATIONS Leda D. Minkova The XIII Inenaonal Confeence Appled Sochasc Models and Daa Analyss (ASMDA-009) Jne 30-Jly 3, 009, Vlns, LITHUANIA ISBN 978-9955-8-463-5 L Sakalaskas, C Skadas and E K Zavadskas (Eds): ASMDA-009 Seleced

More information

p E p E d ( ) , we have: [ ] [ ] [ ] Using the law of iterated expectations, we have:

p E p E d ( ) , we have: [ ] [ ] [ ] Using the law of iterated expectations, we have: Poblem Se #3 Soluons Couse 4.454 Maco IV TA: Todd Gomley, gomley@m.edu sbued: Novembe 23, 2004 Ths poblem se does no need o be uned n Queson #: Sock Pces, vdends and Bubbles Assume you ae n an economy

More information

( ) ( )) ' j, k. These restrictions in turn imply a corresponding set of sample moment conditions:

( ) ( )) ' j, k. These restrictions in turn imply a corresponding set of sample moment conditions: esng he Random Walk Hypohess If changes n a sees P ae uncoelaed, hen he followng escons hold: va + va ( cov, 0 k 0 whee P P. k hese escons n un mply a coespondng se of sample momen condons: g µ + µ (,,

More information

Modern Energy Functional for Nuclei and Nuclear Matter. By: Alberto Hinojosa, Texas A&M University REU Cyclotron 2008 Mentor: Dr.

Modern Energy Functional for Nuclei and Nuclear Matter. By: Alberto Hinojosa, Texas A&M University REU Cyclotron 2008 Mentor: Dr. Moden Enegy Funconal fo Nucle and Nuclea Mae By: lbeo noosa Teas &M Unvesy REU Cycloon 008 Meno: D. Shalom Shlomo Oulne. Inoducon.. The many-body poblem and he aee-fock mehod. 3. Skyme neacon. 4. aee-fock

More information

General Non-Arbitrage Model. I. Partial Differential Equation for Pricing A. Traded Underlying Security

General Non-Arbitrage Model. I. Partial Differential Equation for Pricing A. Traded Underlying Security 1 Geneal Non-Abiage Model I. Paial Diffeenial Equaion fo Picing A. aded Undelying Secuiy 1. Dynamics of he Asse Given by: a. ds = µ (S, )d + σ (S, )dz b. he asse can be eihe a sock, o a cuency, an index,

More information

Nanoparticles. Educts. Nucleus formation. Nucleus. Growth. Primary particle. Agglomeration Deagglomeration. Agglomerate

Nanoparticles. Educts. Nucleus formation. Nucleus. Growth. Primary particle. Agglomeration Deagglomeration. Agglomerate ucs Nucleus Nucleus omaon cal supesauaon Mng o eucs, empeaue, ec. Pmay pacle Gowh Inegaon o uson-lme pacle gowh Nanopacles Agglomeaon eagglomeaon Agglomeae Sablsaon o he nanopacles agans agglomeaon! anspo

More information

Rotations.

Rotations. oons j.lbb@phscs.o.c.uk To s summ Fmes of efeence Invnce une nsfomons oon of wve funcon: -funcons Eule s ngles Emple: e e - - Angul momenum s oon geneo Genec nslons n Noehe s heoem Fmes of efeence Conse

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

Physics 201 Lecture 15

Physics 201 Lecture 15 Phscs 0 Lecue 5 l Goals Lecue 5 v Elo consevaon of oenu n D & D v Inouce oenu an Iulse Coens on oenu Consevaon l oe geneal han consevaon of echancal eneg l oenu Consevaon occus n sses wh no ne eenal foces

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

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 note on characterization related to distributional properties of random translation, contraction and dilation of generalized order statistics

A note on characterization related to distributional properties of random translation, contraction and dilation of generalized order statistics PobSa Foum, Volume 6, July 213, Pages 35 41 ISSN 974-3235 PobSa Foum is an e-jounal. Fo eails please visi www.pobsa.og.in A noe on chaaceizaion elae o isibuional popeies of anom anslaion, conacion an ilaion

More information

The shortest path between two truths in the real domain passes through the complex domain. J. Hadamard

The shortest path between two truths in the real domain passes through the complex domain. J. Hadamard Complex Analysis R.G. Halbud R.Halbud@ucl.ac.uk Depamen of Mahemaics Univesiy College London 202 The shoes pah beween wo uhs in he eal domain passes hough he complex domain. J. Hadamad Chape The fis fundamenal

More information

Handling Fuzzy Constraints in Flow Shop Problem

Handling Fuzzy Constraints in Flow Shop Problem Handlng Fuzzy Consans n Flow Shop Poblem Xueyan Song and Sanja Peovc School of Compue Scence & IT, Unvesy of Nongham, UK E-mal: {s sp}@cs.no.ac.uk Absac In hs pape, we pesen an appoach o deal wh fuzzy

More information

Chapter 3: Vectors and Two-Dimensional Motion

Chapter 3: Vectors and Two-Dimensional Motion Chape 3: Vecos and Two-Dmensonal Moon Vecos: magnude and decon Negae o a eco: eese s decon Mulplng o ddng a eco b a scala Vecos n he same decon (eaed lke numbes) Geneal Veco Addon: Tangle mehod o addon

More information

The Unique Solution of Stochastic Differential Equations. Dietrich Ryter. Midartweg 3 CH-4500 Solothurn Switzerland

The Unique Solution of Stochastic Differential Equations. Dietrich Ryter. Midartweg 3 CH-4500 Solothurn Switzerland The Unque Soluon of Sochasc Dffeenal Equaons Dech Rye RyeDM@gawne.ch Mdaweg 3 CH-4500 Solohun Swzeland Phone +4132 621 13 07 Tme evesal n sysems whou an exenal df sngles ou he an-iô negal. Key wods: Sochasc

More information

Answers to Tutorial Questions

Answers to Tutorial Questions Inoducoy Mahs ouse Answes.doc Answes o Tuoal Quesons Enjoy wokng hough he examples. If hee ae any moe quesons, please don hesae o conac me. Bes of luck fo he exam and beyond, I hope you won need. Tuoal

More information

On Control Problem Described by Infinite System of First-Order Differential Equations

On Control Problem Described by Infinite System of First-Order Differential Equations Ausalian Jounal of Basic and Applied Sciences 5(): 736-74 ISS 99-878 On Conol Poblem Descibed by Infinie Sysem of Fis-Ode Diffeenial Equaions Gafujan Ibagimov and Abbas Badaaya J'afau Insiue fo Mahemaical

More information

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2 Joh Rley Novembe ANSWERS O ODD NUMBERED EXERCISES IN CHAPER Seo Eese -: asvy (a) Se y ad y z follows fom asvy ha z Ehe z o z We suppose he lae ad seek a oado he z Se y follows by asvy ha z y Bu hs oads

More information

s = rθ Chapter 10: Rotation 10.1: What is physics?

s = rθ Chapter 10: Rotation 10.1: What is physics? Chape : oaon Angula poson, velocy, acceleaon Consan angula acceleaon Angula and lnea quanes oaonal knec enegy oaonal nea Toque Newon s nd law o oaon Wok and oaonal knec enegy.: Wha s physcs? In pevous

More information

Variability Aware Network Utility Maximization

Variability Aware Network Utility Maximization aably Awae Newok ly Maxmzaon nay Joseph and Gusavo de ecana Depamen of Eleccal and Compue Engneeng, he nvesy of exas a Ausn axv:378v3 [cssy] 3 Ap 0 Absac Newok ly Maxmzaon NM povdes he key concepual famewok

More information

Delay-Range-Dependent Stability Analysis for Continuous Linear System with Interval Delay

Delay-Range-Dependent Stability Analysis for Continuous Linear System with Interval Delay Inernaonal Journal of Emergng Engneerng esearch an echnology Volume 3, Issue 8, Augus 05, PP 70-76 ISSN 349-4395 (Prn) & ISSN 349-4409 (Onlne) Delay-ange-Depenen Sably Analyss for Connuous Lnear Sysem

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

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

(,,, ) (,,, ). 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

Lecture 6: Learning for Control (Generalised Linear Regression)

Lecture 6: Learning for Control (Generalised Linear Regression) Lecure 6: Learnng for Conrol (Generalsed Lnear Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure 6: RLSC - Prof. Sehu Vjayakumar Lnear Regresson

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

Exponential and Logarithmic Equations and Properties of Logarithms. Properties. Properties. log. Exponential. Logarithmic.

Exponential and Logarithmic Equations and Properties of Logarithms. Properties. Properties. log. Exponential. Logarithmic. Eponenial and Logaihmic Equaions and Popeies of Logaihms Popeies Eponenial a a s = a +s a /a s = a -s (a ) s = a s a b = (ab) Logaihmic log s = log + logs log/s = log - logs log s = s log log a b = loga

More information

ScienceDirect. Behavior of Integral Curves of the Quasilinear Second Order Differential Equations. Alma Omerspahic *

ScienceDirect. Behavior of Integral Curves of the Quasilinear Second Order Differential Equations. Alma Omerspahic * Avalable onlne a wwwscencedeccom ScenceDec oceda Engneeng 69 4 85 86 4h DAAAM Inenaonal Smposum on Inellgen Manufacung and Auomaon Behavo of Inegal Cuves of he uaslnea Second Ode Dffeenal Equaons Alma

More information

The Feigel Process. The Momentum of Quantum Vacuum. Geert Rikken Vojislav Krstic. CNRS-France. Ariadne call A0/1-4532/03/NL/MV 04/1201

The Feigel Process. The Momentum of Quantum Vacuum. Geert Rikken Vojislav Krstic. CNRS-France. Ariadne call A0/1-4532/03/NL/MV 04/1201 The Fegel Pocess The Momenum of Quanum Vacuum a an Tggelen CNRS -Fance Laboaoe e Physque e Moélsaon es Mleux Complexes Unesé Joseph Foue/CNRS, Genoble, Fance Gee Ren Vosla Ksc CNRS Fance CNRS-Fance Laboaoe

More information

CHAPTER 10: LINEAR DISCRIMINATION

CHAPTER 10: LINEAR DISCRIMINATION HAPER : LINEAR DISRIMINAION Dscmnan-based lassfcaon 3 In classfcaon h K classes ( k ) We defned dsmnan funcon g () = K hen gven an es eample e chose (pedced) s class label as f g () as he mamum among g

More information

Simulation of Non-normal Autocorrelated Variables

Simulation of Non-normal Autocorrelated Variables Jounal of Moden Appled Sascal Mehods Volume 5 Issue Acle 5 --005 Smulaon of Non-nomal Auocoelaed Vaables HT Holgesson Jönöpng Inenaonal Busness School Sweden homasholgesson@bshse Follow hs and addonal

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

STABILITY CRITERIA FOR A CLASS OF NEUTRAL SYSTEMS VIA THE LMI APPROACH

STABILITY CRITERIA FOR A CLASS OF NEUTRAL SYSTEMS VIA THE LMI APPROACH Asan Jounal of Conol, Vol. 6, No., pp. 3-9, Mach 00 3 Bef Pape SABILIY CRIERIA FOR A CLASS OF NEURAL SYSEMS VIA HE LMI APPROACH Chang-Hua Len and Jen-De Chen ABSRAC In hs pape, he asypoc sably fo a class

More information

Testing a new idea to solve the P = NP problem with mathematical induction

Testing a new idea to solve the P = NP problem with mathematical induction Tesng a new dea o solve he P = NP problem wh mahemacal nducon Bacground P and NP are wo classes (ses) of languages n Compuer Scence An open problem s wheher P = NP Ths paper ess a new dea o compare he

More information

Today - Lecture 13. Today s lecture continue with rotations, torque, Note that chapters 11, 12, 13 all involve rotations

Today - Lecture 13. Today s lecture continue with rotations, torque, Note that chapters 11, 12, 13 all involve rotations Today - Lecue 13 Today s lecue coninue wih oaions, oque, Noe ha chapes 11, 1, 13 all inole oaions slide 1 eiew Roaions Chapes 11 & 1 Viewed fom aboe (+z) Roaional, o angula elociy, gies angenial elociy

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

Optimal Control Strategies for Speed Control of Permanent-Magnet Synchronous Motor Drives

Optimal Control Strategies for Speed Control of Permanent-Magnet Synchronous Motor Drives Wol Acaemy of Scence, Engneeng an echnology 44 8 Opmal Conol Saeges fo Spee Conol of Pemanen-Magne Synchonos Moo Dves Roozbeh Molav, an Davoo A. Khab Absac he pemanen magne synchonos moo (PMSM) s vey sefl

More information

Reinforcement learning

Reinforcement learning Lecue 3 Reinfocemen leaning Milos Hauskech milos@cs.pi.edu 539 Senno Squae Reinfocemen leaning We wan o lean he conol policy: : X A We see examples of x (bu oupus a ae no given) Insead of a we ge a feedback

More information

Lecture VI Regression

Lecture VI Regression Lecure VI Regresson (Lnear Mehods for Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure VI: MLSC - Dr. Sehu Vjayakumar Lnear Regresson Model M

More information

STUDY OF THE STRESS-STRENGTH RELIABILITY AMONG THE PARAMETERS OF GENERALIZED INVERSE WEIBULL DISTRIBUTION

STUDY OF THE STRESS-STRENGTH RELIABILITY AMONG THE PARAMETERS OF GENERALIZED INVERSE WEIBULL DISTRIBUTION Inenaional Jounal of Science, Technology & Managemen Volume No 04, Special Issue No. 0, Mach 205 ISSN (online): 2394-537 STUDY OF THE STRESS-STRENGTH RELIABILITY AMONG THE PARAMETERS OF GENERALIZED INVERSE

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

Advanced Macroeconomics II: Exchange economy

Advanced Macroeconomics II: Exchange economy Advanced Macroeconomcs II: Exchange economy Krzyszof Makarsk 1 Smple deermnsc dynamc model. 1.1 Inroducon Inroducon Smple deermnsc dynamc model. Defnons of equlbrum: Arrow-Debreu Sequenal Recursve Equvalence

More information

2 shear strain / L for small angle

2 shear strain / L for small angle Sac quaons F F M al Sess omal sess foce coss-seconal aea eage Shea Sess shea sess shea foce coss-seconal aea llowable Sess Faco of Safe F. S San falue Shea San falue san change n lengh ognal lengh Hooke

More information

ON TOTAL TIME ON TEST TRANSFORM ORDER ABSTRACT

ON TOTAL TIME ON TEST TRANSFORM ORDER ABSTRACT V M Chacko E CONVE AND INCREASIN CONVE OAL IME ON ES RANSORM ORDER R&A # 4 9 Vol. Decembe ON OAL IME ON ES RANSORM ORDER V. M. Chacko Depame of Sascs S. homas Collee hss eala-68 Emal: chackovm@mal.com

More information

Computer Propagation Analysis Tools

Computer Propagation Analysis Tools Compue Popagaion Analysis Tools. Compue Popagaion Analysis Tools Inoducion By now you ae pobably geing he idea ha pedicing eceived signal sengh is a eally impoan as in he design of a wieless communicaion

More information

ENGI 4430 Advanced Calculus for Engineering Faculty of Engineering and Applied Science Problem Set 9 Solutions [Theorems of Gauss and Stokes]

ENGI 4430 Advanced Calculus for Engineering Faculty of Engineering and Applied Science Problem Set 9 Solutions [Theorems of Gauss and Stokes] ENGI 44 Avance alculus fo Engineeing Faculy of Engineeing an Applie cience Poblem e 9 oluions [Theoems of Gauss an okes]. A fla aea A is boune by he iangle whose veices ae he poins P(,, ), Q(,, ) an R(,,

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

ROBUST EXPONENTIAL ATTRACTORS FOR MEMORY RELAXATION OF PATTERN FORMATION EQUATIONS

ROBUST EXPONENTIAL ATTRACTORS FOR MEMORY RELAXATION OF PATTERN FORMATION EQUATIONS IJRRAS 8 () Augus www.apapess.com/olumes/ol8issue/ijrras_8.pdf ROBUST EXONENTIAL ATTRACTORS FOR EORY RELAXATION OF ATTERN FORATION EQUATIONS WANG Yuwe, LIU Yongfeng & A Qaozhen* College of ahemacs and

More information

Representing Knowledge. CS 188: Artificial Intelligence Fall Properties of BNs. Independence? Reachability (the Bayes Ball) Example

Representing Knowledge. CS 188: Artificial Intelligence Fall Properties of BNs. Independence? Reachability (the Bayes Ball) Example C 188: Aificial Inelligence Fall 2007 epesening Knowledge ecue 17: ayes Nes III 10/25/2007 an Klein UC ekeley Popeies of Ns Independence? ayes nes: pecify complex join disibuions using simple local condiional

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

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

Field due to a collection of N discrete point charges: r is in the direction from

Field due to a collection of N discrete point charges: r is in the direction from Physcs 46 Fomula Shee Exam Coulomb s Law qq Felec = k ˆ (Fo example, f F s he elecc foce ha q exes on q, hen ˆ s a un veco n he decon fom q o q.) Elecc Feld elaed o he elecc foce by: Felec = qe (elecc

More information

Monetary policy and models

Monetary policy and models Moneay polcy and odels Kes Næss and Kes Haae Moka Noges Bank Moneay Polcy Unvesy of Copenhagen, 8 May 8 Consue pces and oney supply Annual pecenage gowh. -yea ovng aveage Gowh n oney supply Inflaon - 9

More information

2 Aggregate demand in partial equilibrium static framework

2 Aggregate demand in partial equilibrium static framework Unversy of Mnnesoa 8107 Macroeconomc Theory, Sprng 2009, Mn 1 Fabrzo Perr Lecure 1. Aggregaon 1 Inroducon Probably so far n he macro sequence you have deal drecly wh represenave consumers and represenave

More information

The balanced budget multiplier and labour intensity in home production

The balanced budget multiplier and labour intensity in home production Inenaonal Jounal of Economc Behavo and Oganzaon 205; 3(2-): 23-30 Publshed onlne Febuay 26, 205 (hp://www.scencepublshnggoup.com/j/jebo) do: 0.648/j.jebo.s.20503020.5 ISSN: 2328-7608 (Pn); ISSN: 2328-766

More information

A New Generalized Gronwall-Bellman Type Inequality

A New Generalized Gronwall-Bellman Type Inequality 22 Inernaonal Conference on Image, Vson and Comung (ICIVC 22) IPCSIT vol. 5 (22) (22) IACSIT Press, Sngaore DOI:.7763/IPCSIT.22.V5.46 A New Generalzed Gronwall-Bellman Tye Ineualy Qnghua Feng School of

More information

Sections 3.1 and 3.4 Exponential Functions (Growth and Decay)

Sections 3.1 and 3.4 Exponential Functions (Growth and Decay) Secions 3.1 and 3.4 Eponenial Funcions (Gowh and Decay) Chape 3. Secions 1 and 4 Page 1 of 5 Wha Would You Rahe Have... $1million, o double you money evey day fo 31 days saing wih 1cen? Day Cens Day Cens

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

A multi-band approach to arterial traffic signal optimization. Nathan H. Gartner Susan F. Assmann Fernando Lasaga Dennin L. Hou

A multi-band approach to arterial traffic signal optimization. Nathan H. Gartner Susan F. Assmann Fernando Lasaga Dennin L. Hou A mul-an appoach o aeal affc sgnal opmzaon Nahan H. Gane Susan F. Assmann Fenano Lasaga Dennn L. Hou MILP- The asc, symmec, unfom-h anh maxmzaon polem MILP- Exens he asc polem o nclue asymmec anhs n opposng

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

Density Matrix Description of NMR BCMB/CHEM 8190

Density Matrix Description of NMR BCMB/CHEM 8190 Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon Alernae approach o second order specra: ask abou x magnezaon nsead of energes and ranson probables. If we say wh one bass se, properes vary

More information

Lecture-V Stochastic Processes and the Basic Term-Structure Equation 1 Stochastic Processes Any variable whose value changes over time in an uncertain

Lecture-V Stochastic Processes and the Basic Term-Structure Equation 1 Stochastic Processes Any variable whose value changes over time in an uncertain Lecue-V Sochasic Pocesses and he Basic Tem-Sucue Equaion 1 Sochasic Pocesses Any vaiable whose value changes ove ime in an unceain way is called a Sochasic Pocess. Sochasic Pocesses can be classied as

More information

Weights of Markov Traces on Cyclotomic Hecke Algebras

Weights of Markov Traces on Cyclotomic Hecke Algebras Jounal of Algeba 238, 762775 2001 do:10.1006jab.2000.8636, avalable onlne a hp:www.dealbay.com on Weghs of Maov Taces on Cycloomc Hece Algebas Hebng Ru 1 Depamen of Mahemacs, Eas Chna Nomal Unesy, Shangha,

More information

Real-coded Quantum Evolutionary Algorithm for Global Numerical Optimization with Continuous Variables

Real-coded Quantum Evolutionary Algorithm for Global Numerical Optimization with Continuous Variables Chnese Jounal of Eleconcs Vol.20, No.3, July 2011 Real-coded Quanum Evoluonay Algohm fo Global Numecal Opmzaon wh Connuous Vaables GAO Hu 1 and ZHANG Ru 2 (1.School of Taffc and Tanspoaon, Souhwes Jaoong

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

RELATIVE MOTION OF SYSTEMS IN A PARAMETRIC FORMULATION OF MECHANICS UDC Đorđe Mušicki

RELATIVE MOTION OF SYSTEMS IN A PARAMETRIC FORMULATION OF MECHANICS UDC Đorđe Mušicki FCT UNIVESITTIS Sees: Mechancs, uoac Conol an obocs Vol.3, N o,, pp. 39-35 ELTIVE MOTION OF SYSTEMS IN PMETIC FOMULTION OF MECHNICS UDC 53. Đođe Mušck Faculy of Physcs, Unvesy of Belgae, an Maheacal Insue

More information

2 Aggregate demand in partial equilibrium static framework

2 Aggregate demand in partial equilibrium static framework Unversy of Mnnesoa 8107 Macroeconomc Theory, Sprng 2012, Mn 1 Fabrzo Perr Lecure 1. Aggregaon 1 Inroducon Probably so far n he macro sequence you have deal drecly wh represenave consumers and represenave

More information

Fuzzy Control of Inverted Robot Arm with Perturbed Time-Delay Affine Takagi-Sugeno Fuzzy Model

Fuzzy Control of Inverted Robot Arm with Perturbed Time-Delay Affine Takagi-Sugeno Fuzzy Model 7 IEEE Inenaonal Confeence on Robocs an Auomaon Roma Ialy -4 Al 7 FD5. Fuzzy Conol of Invee Robo Am wh Peube me-delay Affne akag-sugeno Fuzzy Moel Wen-Je Chang We-Han Huang an We Chang Absac A sably analyss

More information

Chapter Finite Difference Method for Ordinary Differential Equations

Chapter Finite Difference Method for Ordinary Differential Equations Chape 8.7 Fne Dffeence Mehod fo Odnay Dffeenal Eqaons Afe eadng hs chape, yo shold be able o. Undesand wha he fne dffeence mehod s and how o se o solve poblems. Wha s he fne dffeence mehod? The fne dffeence

More information

SCIENCE CHINA Technological Sciences

SCIENCE CHINA Technological Sciences SIENE HINA Technologcal Scences Acle Apl 4 Vol.57 No.4: 84 8 do:.7/s43-3-5448- The andom walkng mehod fo he seady lnea convecondffuson equaon wh axsymmec dsc bounday HEN Ka, SONG MengXuan & ZHANG Xng *

More information

Density Matrix Description of NMR BCMB/CHEM 8190

Density Matrix Description of NMR BCMB/CHEM 8190 Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon If we say wh one bass se, properes vary only because of changes n he coeffcens weghng each bass se funcon x = h< Ix > - hs s how we calculae

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

Variance and Covariance Processes

Variance and Covariance Processes Vaiance and Covaiance Pocesses Pakash Balachandan Depamen of Mahemaics Duke Univesiy May 26, 2008 These noes ae based on Due s Sochasic Calculus, Revuz and Yo s Coninuous Maingales and Bownian Moion, Kaazas

More information

Banking in a Matching Model of Money and Capital 1

Banking in a Matching Model of Money and Capital 1 Bankng n a Machng Moel of Money an Capal Valee R. Bencvenga Dep. of Economcs Unvesy of Teas a Ausn Gabele Camea Dep. of Economcs Puue Unvesy Absac We nouce banks n a moel of money an capal h ang fcons.

More information

Combinatorial Approach to M/M/1 Queues. Using Hypergeometric Functions

Combinatorial Approach to M/M/1 Queues. Using Hypergeometric Functions Inenaional Mahemaical Foum, Vol 8, 03, no 0, 463-47 HIKARI Ld, wwwm-hikaicom Combinaoial Appoach o M/M/ Queues Using Hypegeomeic Funcions Jagdish Saan and Kamal Nain Depamen of Saisics, Univesiy of Delhi,

More information

) from i = 0, instead of i = 1, we have =

) from i = 0, instead of i = 1, we have = Chape 3: Adjusmen Coss n he abou Make I Movaonal Quesons and Execses: Execse 3 (p 6): Illusae he devaon of equaon (35) of he exbook Soluon: The neempoal magnal poduc of labou s epesened by (3) = = E λ

More information

Lesson 2 Transmission Lines Fundamentals

Lesson 2 Transmission Lines Fundamentals Lesson Transmsson Lnes Funamenals 楊尚達 Shang-Da Yang Insue of Phooncs Technologes Deparmen of Elecrcal Engneerng Naonal Tsng Hua Unersy Tawan Sec. -1 Inroucon 1. Why o scuss TX lnes srbue crcus?. Crera

More information

Relative and Circular Motion

Relative and Circular Motion Relaie and Cicula Moion a) Relaie moion b) Cenipeal acceleaion Mechanics Lecue 3 Slide 1 Mechanics Lecue 3 Slide 2 Time on Video Pelecue Looks like mosly eeyone hee has iewed enie pelecue GOOD! Thank you

More information

On The Estimation of Two Missing Values in Randomized Complete Block Designs

On The Estimation of Two Missing Values in Randomized Complete Block Designs Mahemaical Theoy and Modeling ISSN 45804 (Pape ISSN 505 (Online Vol.6, No.7, 06 www.iise.og On The Esimaion of Two Missing Values in Randomized Complee Bloc Designs EFFANGA, EFFANGA OKON AND BASSE, E.

More information

Numerical solution of differential equations

Numerical solution of differential equations Numecal soluon of ffeenal euaons Devng an solvng ffeenal euaons DE s a common ask n compuaonal eseac. Many pyscal laws/elaons ae fomulae n ems of DE. Mos connuum smulaon meos ae base on soluon of DE. Aloug

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

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

CHAPTER 13 LAGRANGIAN MECHANICS

CHAPTER 13 LAGRANGIAN MECHANICS CHAPTER 3 AGRANGIAN MECHANICS 3 Inoucon The usual way of usng newonan mechancs o solve a poblem n ynamcs s fs of all o aw a lage, clea agam of he sysem, usng a ule an a compass Then mak n he foces on he

More information

Measuring capital market integration

Measuring capital market integration Measung capal make negaon Mana Ems, 1 Naonal Bank of Belgum Absac The convegence of Euopean economes n he wake of Euopean moneay unon, ogehe wh nceasngly common dynamcs n cuency and equy euns, suggess

More information

Integer Programming Models for Decision Making of. Order Entry Stage in Make to Order Companies 1. INTRODUCTION

Integer Programming Models for Decision Making of. Order Entry Stage in Make to Order Companies 1. INTRODUCTION Inege Pogammng Models fo Decson Makng of Ode Eny Sage n Make o Ode Companes Mahendawah ER, Rully Soelaman and Rzal Safan Depamen of Infomaon Sysems Depamen of Infomacs Engneeng Insu eknolog Sepuluh Nopembe,

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

APPROXIMATIONS FOR AND CONVEXITY OF PROBABILISTICALLY CONSTRAINED PROBLEMS WITH RANDOM RIGHT-HAND SIDES

APPROXIMATIONS FOR AND CONVEXITY OF PROBABILISTICALLY CONSTRAINED PROBLEMS WITH RANDOM RIGHT-HAND SIDES R U C O R R E S E A R C H R E P O R APPROXIMAIONS FOR AND CONVEXIY OF PROBABILISICALLY CONSRAINED PROBLEMS WIH RANDOM RIGH-HAND SIDES M.A. Lejeune a A. PREKOPA b RRR 7-005, JUNE 005 RUCOR Ruges Cene fo

More information

7 Wave Equation in Higher Dimensions

7 Wave Equation in Higher Dimensions 7 Wave Equaion in Highe Dimensions We now conside he iniial-value poblem fo he wave equaion in n dimensions, u c u x R n u(x, φ(x u (x, ψ(x whee u n i u x i x i. (7. 7. Mehod of Spheical Means Ref: Evans,

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

β A Constant-G m Biasing

β A Constant-G m Biasing p 2002 EE 532 Anal IC Des II Pae 73 Cnsan-G Bas ecall ha us a PTAT cuen efeence (see p f p. 66 he nes) bas a bpla anss pes cnsan anscnucance e epeaue (an als epenen f supply lae an pcess). Hw h we achee

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

Sharif University of Technology - CEDRA By: Professor Ali Meghdari

Sharif University of Technology - CEDRA By: Professor Ali Meghdari Shaif Univesiy of echnology - CEDRA By: Pofesso Ali Meghai Pupose: o exen he Enegy appoach in eiving euaions of oion i.e. Lagange s Meho fo Mechanical Syses. opics: Genealize Cooinaes Lagangian Euaion

More information