Optimum Centralized Portfolio Construction with. Decentralized Portfolio Management

Size: px
Start display at page:

Download "Optimum Centralized Portfolio Construction with. Decentralized Portfolio Management"

Transcription

1 Optmum Centralzed ortfolo Constructon wth ecentralzed ortfolo Management Edwn J. Elton*and Martn J. Gruber* October 8, 00 * Nomura rofessors of nance, Stern School of usness, New York Unversty. e would lke to thank Stephen rown for hs helpful comments on our manuscrpt.

2 Many fnancal nsttutons employ outsde portfolo managers to manage part or all of ther nvestable assets. These nsttutons nclude penson funds, prvate endowments (e.g., colleges and chartes), and prvate trusts. In 999, the nvestment company nsttute estmated that these nsttutons managed 5. trllon dollars n assets. Most of these nsttutons employed outsde managers to nvest these funds. The relevancy of ths problem has been wdely recognzed n the practtoners lterature on portfolo? urthermore, t s recognzed n the prudent man law that spells out the responsbltes of the centralzed decson maker delegatng management responsblty. or example the New York State law n estate power and trust states. enson funds are the largest and most lkely organzatons to employ several outsde managers, each of whom manages a part of the overall portfolo. In ths paper we wll use the penson fund manager as the prototype of the centralzed decson-maker tryng to optmally manage a set of decentralzed portfolo managers but the analysts s general. If the centralzed decson-maker (CM) s a mean varance maxmzer, the CM could construct a portfolo usng standard portfolo theory and estmates of mean return, varances, and covarances between the portfolos constructed by a group of decentralzed managers. However, ths overall portfolo s unlkely to be optmum snce the ndvdually managed portfolos themselves were constructed wthout takng nto account the portfolos of the other managers. The purpose of ths artcle s to set up a structure that leads to the optmum portfolo from the vewpont of the CM when there are multple managers and ther portfolos are constructed wthout reference to each other. See, for example, artolomer (999), Grnald and Kahn (995), arrell (976), and osenberry (977). or a full dscusson of modern portfolo theory and the prudent man rule see Elton and Gruber n Longstaff ( ).

3 Ths paper can be vewed as a contrbuton to the extensve lterature n nancal Economcs developng condtons under whch a CM wll never make a worse decson than decentralzed managers provdng the nformaton s used optmally. 3 Ths lterature assumes the decentralzed managers are wllng to provde all nformaton to each other or to a centralzed manager. Ths case has been examned for the penson fund problem by osenberg (977) and. artolomeo (999). or example, osenberg (977) demonstrated that wth full nformaton, the decentralzed portfolo managers wll not make better decsons than that of the centralzed manager. Ths paper examnes a specal case of ths more general lterature: the case of a centralzed portfolo manager employng a set of ndvdual portfolo managers each of whom constructs hs or her own portfolo wthout communcatng wth other managers. Several authors have asserted that ths problem s too dffcult to solve (see osenberg (977) and. artolomeo (999)). They argue the only solutons are for each outsde manager to ether turn over all of ther estmates for ndvdual securty characterstcs to a centralzed manager or to supply all purchases and sales to the centralzed managers. In the latter case models are presented that allow the central manager to approxmate from ths nformaton, the ndvdual managers forecasts. hat makes ths a specal case s the realstc assumpton that a decentralzed manager s only wllng to share some nformaton wth the centralzed manager and none wth other managers. In ths artcle, we solve for sets of condtons under whch the centralzed manager can make optmum decsons despte partal nformaton through the use of gudelnes for the decentralzed managers. hle ths can be vewed as an extenson of the prevous lterature on centralzed versus decentralzed 3 See, for example, adner (96), Marshak and adner (97), and Ohlson (975 and 979). 3

4 decson makng t s of at least equal mportance because t offers a soluton to a problem whch s at the heart of nvestment allocaton today. In the frst secton we wll present a more detaled dscusson of the problem. e wll then solve the problem for one actve manager and multple passve portfolos. The model s then generalzed to multple actve managers. Next, we present solutons under a smplfed structure of the return-generatng process. nally, we dscuss the complcatons when short sales are not allowed. I. ackground In ths secton we dscuss some background materal on the penson nvestment problem and revew the relevant lterature. The same consderatons hold for prvate endowments and trusts. Most penson plans are managed by a centralzed decson maker at a frm. Most frms have one person who s prncpally n charge, although the ultmate responsblty rests wth a commttee, usually the board. Ths CM normally employs outsde portfolo managers to construct actve portfolos. Index funds are generc products and we wll assume the centralzed decson maker can potentally select one or more of these. The centralzed decson maker s task s fourfold: ) decde how much to nvest n each portfolo, ) gve the outsde managers nstructons that wll result n ther makng optmum securty allocatons from the pont of vew of the overall plan, 3) desgn ncentve systems so that the managers wll behave optmally 4, and 4) evaluate and select the portfolo managers. In ths paper we deal only wth the frst two of these problems although our solutons have maor mplcatons for the thrd and fourth problems. Throughout the paper, we assume that the portfolo managers wll not provde the 4 No one has addressed the mult-perod ncentve problem outlned here. However, there are a number of related artcles. See for example, yvg, arnsworth and Carpenter (00), Khlstrom (988), Stoughton (993), and ender (988). 4

5 centralzed decson maker wth ther return forecasts for ndvdual securtes, but wll provde aggregate nformaton about the portfolos they hold. spects of ths problem have prevously been addressed by Treynor and lack (973) and n more detal by Sharpe (98). The Treynor lack artcle dscussed the actve passve splt when the CM descrbed the returns on the passve portfolo, short sales are allowed and the sngle-ndex model descrbes the return generatng process. The clear antecedent to ths artcle s Sharpe s (98) resdental address. Sharpe develops, wth one actve and one passve manager, the nstructons for the actve manager that wll result n the actve manager producng a globally optmal portfolo for a partcular utlty functon. He assumes short sales are allowed and the varance covarance matrx s agreed on by all partes. He also solves for the nstructons to be gven to the managers that results n a global optmal for the case of two managers followng exactly the same set of securtes where the centralzed decson maker beleves the best forecast of a securtes alpha s a weghted average of the two managers alphas and where these weghts add to one. In solvng ths problem he mantans the assumpton of short sales allowed and agreement on the varance covarance matrx. Sharpe could not obtan an exact soluton for the case of managers followng non-overlappng securtes. Our analyss extends Sharpe n that we generalze to N managers, have no requrement that each manager holds the same securtes, and, by employng a multfactor model, can arrve at smple rules for formng myopc optmum portfolos, understandng the weght placed on each securty n these portfolos, and the amount to allocate to each actve and passve portfolo. e also extend the analyss to the case 5

6 where short sales are not allowed and show condtons under whch optmal decentralzed management s possble and when t s not. II. Separaton wth a sngle actve and multple passve managers In ths secton of the paper we wll assume that a centralzed decson maker (CM) exsts who hres a sngle actve manager. e wll shortly expand the case to several actve managers. e wll assume the followng: ) the CM s a mean varance decson maker, ) the CM beleves a mult-ndex model descrbes the return structure for securtes and all ndexes n the mult-ndex model are tradable. The second pont requres some clarfcaton. The CM beleves that returns can be descrbed as beng generated by a set of ndexes (not necessarly orthogonal) that the CM can take postons n as passve portfolos 5. or example, ths s consstent wth a belef that the return on securtes s a functon of the market return, the return on a portfolo of small stocks, and/or the return on a portfolo of value or growth stocks. The CM wshes to consder these sources of rsk n makng the optmum mean varance decson. or expostonal reasons we wll analyze the CM s problem wth a two ndex model though the soluton easly generalzes to any number of ndexes.. The CM s problem e start by examnng the optmum decson the CM would make f the CM had all the nformaton that s avalable to the actve managers. s mentoned earler, we beleve the CM would not be able to obtan rsk adusted return forecasts for ndvdual securtes from the actve manager, but for the moment we examne the optmum decson 5 Index funds, many of them exchange traded, exst for almost any ndex a manager mght want to use n a return generatng process. 6

7 as f the CM has such nformaton. e wll also assume that the CM does not have perfect fath n the return forecasts of the actve manager. Ths mples that the CM wll take postons n the passve portfolos for two reasons, to obtan dversfcaton across securtes so that the aggregate portfolo s mean varance effcent, and to elmnate some of the lack of relablty n the analyst s estmates. In order to specfy the return generatng process, defne. s the return on stock. s the rsk free rate of nterest 3., s the return on ndex and ndex respectvely, s the senstvty of stock to ndexes and s the varance of the return on ndexes and, e s the resdual rsk of stock from the two-ndex model 7. s the rsk adusted return on securty 8. e s the resdual return for securty 9. The superscrpt desgnates that the decson s from the pont of vew of the CM. Then the return generatng process s ( ) ( ) e () ssume that the CM had access to the excess return forecasts ( ) of the actve manager. urthermore, assume the CM beleves that the best estmate of rsk-adusted excess return s an average of the analysts forecasts and the value that would occur n 7

8 equlbrum namely zero. Thus, we defne the excess rsk adusted return that the CM would use as where s set by the CM between 0 and 6. To solve ths problem, assumng short sales, the CM can use the standard frst order condtons. The nvestments that can be selected are the N ndvdual securtes and the two ndexes. The frst order condton for securty and ndex s N for,,n () here. N s the number of securtes enterng nto the decson makng process. Securty N and N are ndexes whch we henceforth desgnate as and. 3. s a number proportonal to the optmal weght whch the CM would place n securty If the return generatng process descrbed n equaton () s an accurate descrpton of returns and we recognze that the ndexes need not be orthogonal, then we can defne the varance and covarance between ndvdual securtes as for,,n e for N, N 6 hle the optmum way to set s beyond the scope of ths paper, there have been a number of excellent artcles publshed n the past few years explanng optmum ways of changng alpha for estmaton rsk and bas. See awa, rown, and Kleen (979) for the fundamental applcaton of aysan analyss and aks, Metrck, and achter (00) and astor and Stambaugh (00) for recent applcatons of aysan analyss to estmatng the nputs for optmal portfolo allocaton. 8

9 or the N and N securtes (the ndexes), a smpler form exsts. or example, for ndex the varance s and the covarance wth ndex s and the covarance wth ndvdual securtes s Employng these relatonshps wth the frst order condton (), we get for securty ) ( ) ( e N N (3) N and for the ndexes N N (4) N N (5) Substtutng equatons (4) and (5) nto equaton (3) and smplfyng, we get 7 (6) e e To solve for the optmum amount n securty we consder the actve portfolo denoted by as a separate portfolo and look at the optmum composton of ths portfolo before we allocate across all three portfolos. e can treat the desgn of as a separate portfolo because from equaton (6), s not a functon of or. 7 smlar expresson but n a dfferent context can be found n Elton and Gruber and adberg (979). 9

10 The fracton to nvest n any stock, p, n the actve portfolo can be determned by recognzng that 8 p. Therefore, recognzng that the amount to nvest n an stock n the optmal actve portfolo from the vewpont of the CM s p e e (7) N N t e e Once portfolo s determned smple procedures exst for allocatng funds between the actve and passve portfolos. These are presented n Secton C below.. Optmum actve portfolo The CM can ensure that the actve manager wll hold the optmal actve portfolo from the pont of vew of the CM smply by nstructng the actve manager to compute by e for each stock and to hold them n that proporton. 9 Ths smple nstructon ensures that the actve manager wll turn over to the CM the same actve portfolo that the CM would hold f all the securty estmates were suppled drectly to the CM. Optmzaton for the actve portfolo s reached wthout the actve manager gvng up prvate nformaton. Of course the CM stll has the problem of decdng what fracton of funds to place n the actve portfolo and each of the passve portfolos. 8 See Elton, Gruber, and adburg (976) for a full exposton or Lntner (965) for the orgnal proof. 9. If the decentralzed manager were smply told to form the optmum actve portfolo assumng that he could hold the passve portfolo, he would get the same result as followng the drecton from the central manager. lthough ths rankng devce was derved n the pror secton usng two ndexes t s easy to show that the same rankng devse holds f there are N ndexes 0

11 C. Solvng the aggregate allocaton problem enote the characterstcs of the actve portfolo by the subscrpt. Then from the vewpont of the CM, gnorng for the moment any dffculty of gettng nformaton, the problem can be formulated and solved usng the followng frst order condtons 0. ) ( ) ( ( e ) ( ) ( ) These are standard frst order condtons. Snce everythng but the s are known, the equatons can be solved explctly for the optmal fracton of funds n each portfolo. To do ths we utlze a relatonshp we derve later. s shown n equaton (3), e e. Usng ths expresson, the soluton s ( ) ( ρ ) ( ) ρ ( ρ ) e ( ρ ) ( ) ( ρ ) (8) e e here ρ s the correlaton between passve portfolo and. These three equatons along wth the expresson normalzng the portfolo weghts to add to one whch s 0 The extenson to more than two ndexes s straghtforward. One new equaton would be added for each ndex, one for each new ndex would be added to each equaton and the varance and covarance terms would be modfed to account for the addtonal ndexes.

12 k k l,, and l l gve us the closed form soluton for the optmal weght to place n the actve and each passve portfolo. The optmal weghts depend on the fundamental characterstcs of each of the three portfolos n a way that makes ntutve sense. or each of the passve ndex funds, the hgher the excess return on the fund relatve to ts varance, the larger the allocaton of funds to that portfolo. Smlarly, for the actve portfolo, the larger the rsk adusted return for that portfolo relatve to ts unsystematc rsk, the greater the funds placed n t. The correlaton coeffcent between the ndexes also has a large effect on the relatve nvestment n each of the passve portfolos. The mpact of the correlaton coeffcent on allocaton depends on the rato of the excess return to standard devaton of ndex to that of ndex as well as the sze of the correlaton coeffcent tself. In order to determne the splt across portfolos, the CM needs to request the actve manager s estmate of the alpha for the actve portfolo, the resdual rsk of the actve portfolo and the actve portfolo senstvtes to the two ndexes. These are the types of estmates the actve manager should be wllng to supply snce they are aggregate portfolo values rather than ndvdual securty values. The CM needs to estmate the expected return above the rskless rate and rsk on the passve funds, the covarance between the passve s stated earler, we are assumng that the CM and the actve manager are employng dentcal estmates of the s and resdual rsks but not return characterstcs of each securty. Ths could come about naturally f the rsk parameters were estmated from the same commercal servce (e.g., or lshre). The CM could ether specfy that decentralzed managers use a partcular commercal servce or drectly supply the rsk parameters for the assumpton of our model to hold. The need for a common return generatng process mght partcularly explan the specfcaton of benchmarks n contracts wth managers.

13 3 funds, and the amount of weght () to put on the actve manager s estmates. If futures are avalable on the ndexes, the aggregate portfolo problem s smplfed.. The ggregate ortfolo roblem wth utures If futures are avalable on the ndexes, then senstvtes to the ndexes can be adusted wthout affectng the amount nvested n the actve portfolo. The expected return and rsk on the portfolo of the CM s, ( ) ( ) C e C where C s the overall portfolo held by the CM. The choce varables for the CM are how much to put n the actve portfolo, how much to place n the rskless asset and the level of senstvty of the overall portfolo to each of the factors. Takng dervatves of C C θ wth respect to and, respectvely results n the followng frst order condtons e e C C ( ) C C ( ) C C. The effcent fronter s the lne connectng the rskless asset wth the optmal rsky portfolo. If we can determne one pont on the lne, we can trace out the full effcent

14 fronter. Varyng traces out the lne. Thus, wth no loss of generalty we can solve for the portfolo wth. Settng equal to one we get that the optmum betas are ( ) ( ) ( ρ ) ( ) ( ρ ) ρ ρ e e where ρ s the correlaton between the two ndexes. The easest way to nterpret the results s to consder the case ρ equal to zero. th ths assumpton, s equal to the excess return to rsk of ndex dvded by the rato of the rsk adusted return to the resdual rsk of the actve portfolo. hen the ndexes are correlated, ths rato s modfed to take account the correlaton between the ndexes. e have now presented a set of condtons under whch a centralzed decsonmaker can optmze portfolo composton whle employng one actve manager. The next problem to solve s the case where the CM employs several actve managers. III. Multple actve managers The analyss generalzes to multple actve managers whether these managers follow some or all securtes n common or follow ndependent sectons of the market. or Sharpe (98) dd not reach an explct soluton n the case where only some securtes were n common across actve managers. 4

15 smplcty we wll solve for the case of two actve managers, but the analyss easly generalzes. ssume that the CM has all the nformaton produced by each manager but dfferent confdence n the forecasts of each manager. urthermore, the CM beleves that all the managers estmates are too extreme but that the approprate estmate s some combnaton of them. 3 If we desgnate the weght the CM puts on the estmate prepared by manager as and manager as. Then. Once agan t s necessary for the CM to supply estmates of betas and resdual varances to all actve managers ether drectly or by specfyng that they use a common servce such as. Snce e s suppled by the CM to all managers, t s common and e (9) e e Earler we showed that e was proportoned to the optmum amount that the CM wshed to place n securty f all alphas were suppled to the CM. The ssue we address n ths secton s the nstructons to gve to the ndvdual managers and the correct proportons to nvest n each actve portfolo so that the CM, by combnng the portfolos of the actve managers, ends up wth a fracton n the actve portfolo proportonal to e for each securty. Summng both sdes of equaton (9) across all securtes 3 Implct n what follows s f only one manager follows a securty, the CM assumes the best estmate of the second manager s alpha f he/she followed t would be zero. 5

16 6 e e e (0) If the CM nstructs each manager to compute e for each securty and to place a fracton of money n each securty proportonal to ths rato we can defne the fracton any manager (e.g., manager ) places n any securty as e N e. e wll now show ths nstructon results n an overall optmum. However, before we do so, we need to derve some of the attrbutes of the portfolo whch manager (or any manager) wll hold. The rsk-adusted excess return on the portfolo held by manager s e e e e () and the resdual rsk of ths actve portfolo s

17 7 e e e e e e e () Takng the rato of () and () yelds e e (3) urthermore, K where the subscrpt K s a counter, ndcaton ether ndex or ndex equals e K e k K (4) earrangng and substtutng equaton (3) yelds e e K K (5) Havng developed these expressons, we can now show that there exsts an allocaton across the actve portfolos along wth the nstructon to the ndvdual managers to hold

18 8 stocks n proporton e, whch results n an overall optmum to the CM. Substtutng equaton (3) nto (0) yelds e e e (6) ecall that the ndvdual portfolo manager has been nstructed to form a portfolo by holdng securtes proportonal to the rato of excess return to resdual rsk. ecognzng ths nstructon and usng equaton (3) to smplfy the denomnator e e (7) vdng both sdes of equaton (9) by e, the correct amount n securty n the actve portfolos from the pont of vew of the CM s e e e e e e e e e e (8) e e e e

19 here the terms n brackets represent the proporton of the actve portfolo to nvest wth manager and manager, respectvely. Snce e can be computed from equaton (6), f the CM obtans and from manager, and e and from e manager, he or she can determne optmum proportons among actve managers. In addton, snce the CM knows the characterstcs of the aggregate actve portfolo, the CM can act n determnng the splt between the actve and passve portfolos as f there s a sngle portfolo. Thus, the allocaton between the actve portfolo and the two passve portfolos can be determned usng the equatons n Secton II C. IV. Orthogonal Indexes Up to ths pont we have assumed that the ndexes are not orthogonal. The advantage of ths s that t allows the passve portfolos to be portfolos that exst n the market such as small stocks, the S& Index, growth stocks, etc. However, f we are wllng to assume orthogonal ndexes the allocaton across actve and passve managers s smplfed. th orthogonal ndexes, the covarance among ndexes s zero, and there exsts a smple formula for the amount to nvest n the passve ndex. or passve ndex equaton (4) becomes Solvng for 9

20 0 N Substtutng for from equaton (6) yelds e N Expressng e n terms of the two actve portfolos e N e N nally, usng equaton (5): e e Thus, the centralzed decson maker can determne the total and the splt between each of the passve portfolos and each of the actve portfolos usng a smple formula f all managers provde ther estmates of and, e on each ndex, and the centralzed decson maker estmates the s and excess return and rsk on the ndex. The actve managers also need to have common rsk measures, s and e for all securtes under consderaton. In the case of orthogonal ndexes, characterstcs of ndexes other than the

21 one beng analyzed do not mpact the assocated wth any ndex. Thus, the equaton apples to any number of ndexes 4. IV. Short sales not allowed Let s start wth the case of a sngle actve manager where short sales of the ndexes are allowed but short sales of securtes are not. Ths case s realstc for some centralzed decson makers. utures exchange traded funds or future replcatons wth optons exst for many ndexes. In ths case a CM can effectvely short sell ndexes. To determne the optmum when securtes cannot be short sold, we need to use Kuhn, Tucker condtons. Ths smply nvolves addng the dual varables M s (one for each securty) to equaton (3) the frst order condtons for each securty when short sales are allowed. The soluton to the portfolo problem makes use of the complmentary condtons that the product of the dual and the prmal must be zero ( M 0 for all ) and that M and must be equal to or greater than zero for all. Snce there are no duals on the frst order condtons for ndexes, equatons (4) and (5) are unchanged. Equaton (6) holds wth the addton of the dual for the securty 5. ddng the dual, equaton (6) becomes M * e. If s postve, must be postve snce postve from the complementary correlaton, * M must be postve so that * M cannot be negatve. If s * M must be zero. If s negatve then s not negatve and from the complementary condton 5 * M s a transformaton of the M added to each equaton, but has the same sgn as M.

22 must be zero. Thus, all ether equal e or zero. The optmum portfolo for the CM s obtaned by havng the manager nvest n all securtes for whch > 0 and as before n proporton to e. The equatons n secton II C, then defne the optmal splt between the actve and passve portfolos. If there are multple actve managers, the condton under whch an optmal soluton can be reached are more restrctve. To understand the problem, consder the case where manager forecasts > 0 and manager forecasts < 0 where the absolute value of s greater than and the CM puts equal weghts on the estmates of each manager. In ths case the CM would want to hold zero n securty. However, manager wll hold postve proportons and wthout short sales, manager wll hold zero rather than short sell. No combnaton wll provde an optmum to the CM. The only excepton to ths scenaro s the case where the centralzed manager wshes to place no weght on a forecast of a negatve alpha. Ths mples that the CM beleves the managers have no ablty to forecast below normal returns but have some ablty on the upsde. In the case where > 0 and < 0, the CM would want to use and, provdng all passve portfolos are held long or short sales of passve portfolos are allowed, the analyss outlned above goes through wth each actve manager not allowed to have short sales.

23 V. Concluson In ths artcle we have shown that under realstc condtons when short sales are allowed, t s possble, and ndeed qute easy, for a centralzed decson maker to form an optmal overall portfolo whle employng multple outsde portfolo managers 6. Ths s on contrast to the assertons n the practtoner lterature that argue ths s not possble or possble only wth full nformaton. Outsde managers should be wllng to supply the nformaton the CM needs n our models snce t does not requre them to reveal prvate nformaton on ndvdual securtes. Managers should be hestant to reveal nformaton on ndvdual securtes, snce t s useful for multple portfolos and to reveal t opens up the possblty of resale or drect use of the nformaton. hen short sales are not allowed and f there s a sngle actve manager to combne wth passve ndexes, a soluton exsts f t s optmum for the manager to place some funds n each ndex and/or the ndexes (as opposed to the securtes) can be sold short 7. hen short sales are not allowed and there are multple actve managers, the prevous analyss holds as long as a forecast of a negatve alpha by a manager s taken to convey no nformaton and the manager s smply told not to hold securtes wth negatve alpha. e have shown that n the case of multple managers, f short sales are not allowed and the centralzed manager makes use of estmates of negatve alphas as well as postve alphas, a general optmum soluton does not exst. 6 llowng short sales s an ncreasngly realstc case wth the ablty to use futures to short and wth funds lke hedge funds routnely shortng. 7 The assumpton that ndexes can be sold short becomes ncreasngly realstc over tme as exchange traded funds and futures have been created for an ncreasng number of ndexes. It can be shown f the ndexes cannot be sold short, a soluton stll exsts as long as one and only one ndex s not held long 3

24 blography aks, Klaas, ndrew Metrck and Jessca achter (00), Should nvestors abort all actvely managed mutual funds? Journal of nance, Vol. 56, pp away, Vay, Stephen rown and oger Klen (979), Estmaton rsk and optmal portfolo choce, (North Holland, msterdam). artolomeo (999), radcal proposal for the operaton of mult-manager nvestment funds, Northfeld Informaton Servces. ypvg, hlp, Heber arnsworth, and Jennfer Carpenter (000), ortfolo performance and agency, unpublshed manuscrpt, New York Unversty. Elton, Edwn J., Martn J. Gruber and Manfred adberg (976). Smple crtera for optmal portfolo selecton. Journal of nance Vol., pp Elton, Edwn J., Martn J. Gruber, and adberg Manfred (979), Smple crtera for optmal portfolo selecton, n Edwn J. Elton and Martn J. Gruber ortfolo Theory: Twenty-ve Years Later. msterdam, North Holland. 4

25 errell, James L. (976), The mult-ndex model and practcal portfolo analyss, esearch oundaton of the Insttute of? nancal nalysts. Grnold, chard, and onal Kaken (965), ctve ortfolo Management, robus ublshng, Chcago, Illnos. Khlstrom,. E. (988), Optmal contracts for securty analysts and portfolo managers, Studes n ankng and nance, 5, Lntner, John (965), The valuaton of rsk assets on the selecton of nvestments n stock portfolos n captal budgets, evew of Economcs and Statstcs 47, Longtreth, evs (986), Modern Investment Management and the rudent Man ule. Oxford Unversty ress. Marhsak, J. and adner,. (97), Economc theory of teams, New Haven, CT. Yale Unversty ress. New York State Estates owers and Trust Law. Secton -.3, Subsecton (b) (4) (c). Ohlson, Jm (979), esdual (I) analyss and the prvate value of nformaton, Journal of ccountng esearch, Vol 7,, utumn,

26 Ohlson, Jm (975), The complete orderng of nformaton alternatves for a class of ortfolo selecton models, Journal of ccountng esearch, utumn. astor, Lubos, and obert Stambaugh (00), Investng n equty mutual funds. Unpublshed manuscrpt, harton School of usness. adner, oy (96), Team decson problems, nnals of Mathematcal Statstcs March. osenberg, arr (997), Insttutonal nvestment wth multple portfolo managers, roceedngs of the Semnar on the nalyss of Securty rces, Unversty of Chcago, Sharpe,.. (98). ecentralzed nvestment management. Journal of nance Vol. 36, pp Stoughton, N. M. (993), Moral hazard and the portfolo management problem, Journal of nance, 48(5), Treynor, Jack and sher lack (973). How to use securty analyss to mprove portfolo selecton. Journal of usness 46,

27 ender, J.. (988), symmetrc Informaton n nancal Markets, h.. thess, Yale Unversty. 7

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 9

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 9 Elton, Gruber, Brown, and Goetzmann Modern Portfolo Theory and Investment Analyss, 7th Edton Solutons to Text Problems: Chapter 9 Chapter 9: Problem In the table below, gven that the rskless rate equals

More information

Mutual Funds and Management Styles. Active Portfolio Management

Mutual Funds and Management Styles. Active Portfolio Management utual Funds and anagement Styles ctve Portfolo anagement ctve Portfolo anagement What s actve portfolo management? How can we measure the contrbuton of actve portfolo management? We start out wth the CP

More information

Elton, Gruber, Brown and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 4

Elton, Gruber, Brown and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 4 Elton, Gruber, Brown and Goetzmann Modern ortfolo Theory and Investment Analyss, 7th Edton Solutons to Text roblems: Chapter 4 Chapter 4: roblem 1 A. Expected return s the sum of each outcome tmes ts assocated

More information

Tests for Two Correlations

Tests for Two Correlations PASS Sample Sze Software Chapter 805 Tests for Two Correlatons Introducton The correlaton coeffcent (or correlaton), ρ, s a popular parameter for descrbng the strength of the assocaton between two varables.

More information

Risk and Return: The Security Markets Line

Risk and Return: The Security Markets Line FIN 614 Rsk and Return 3: Markets Professor Robert B.H. Hauswald Kogod School of Busness, AU 1/25/2011 Rsk and Return: Markets Robert B.H. Hauswald 1 Rsk and Return: The Securty Markets Lne From securtes

More information

Principles of Finance

Principles of Finance Prncples of Fnance Grzegorz Trojanowsk Lecture 6: Captal Asset Prcng Model Prncples of Fnance - Lecture 6 1 Lecture 6 materal Requred readng: Elton et al., Chapters 13, 14, and 15 Supplementary readng:

More information

Problem Set 6 Finance 1,

Problem Set 6 Finance 1, Carnege Mellon Unversty Graduate School of Industral Admnstraton Chrs Telmer Wnter 2006 Problem Set 6 Fnance, 47-720. (representatve agent constructon) Consder the followng two-perod, two-agent economy.

More information

MgtOp 215 Chapter 13 Dr. Ahn

MgtOp 215 Chapter 13 Dr. Ahn MgtOp 5 Chapter 3 Dr Ahn Consder two random varables X and Y wth,,, In order to study the relatonshp between the two random varables, we need a numercal measure that descrbes the relatonshp The covarance

More information

Elements of Economic Analysis II Lecture VI: Industry Supply

Elements of Economic Analysis II Lecture VI: Industry Supply Elements of Economc Analyss II Lecture VI: Industry Supply Ka Hao Yang 10/12/2017 In the prevous lecture, we analyzed the frm s supply decson usng a set of smple graphcal analyses. In fact, the dscusson

More information

Teaching Note on Factor Model with a View --- A tutorial. This version: May 15, Prepared by Zhi Da *

Teaching Note on Factor Model with a View --- A tutorial. This version: May 15, Prepared by Zhi Da * Copyrght by Zh Da and Rav Jagannathan Teachng Note on For Model th a Ve --- A tutoral Ths verson: May 5, 2005 Prepared by Zh Da * Ths tutoral demonstrates ho to ncorporate economc ves n optmal asset allocaton

More information

REFINITIV INDICES PRIVATE EQUITY BUYOUT INDEX METHODOLOGY

REFINITIV INDICES PRIVATE EQUITY BUYOUT INDEX METHODOLOGY REFINITIV INDICES PRIVATE EQUITY BUYOUT INDEX METHODOLOGY 1 Table of Contents INTRODUCTION 3 TR Prvate Equty Buyout Index 3 INDEX COMPOSITION 3 Sector Portfolos 4 Sector Weghtng 5 Index Rebalance 5 Index

More information

Investment Management Active Portfolio Management

Investment Management Active Portfolio Management Investment Management Actve Portfolo Management Road Map The Effcent Markets Hypothess (EMH) and beatng the market Actve portfolo management Market tmng Securty selecton Securty selecton: Treynor&Black

More information

Finance 402: Problem Set 1 Solutions

Finance 402: Problem Set 1 Solutions Fnance 402: Problem Set 1 Solutons Note: Where approprate, the fnal answer for each problem s gven n bold talcs for those not nterested n the dscusson of the soluton. 1. The annual coupon rate s 6%. A

More information

Quiz on Deterministic part of course October 22, 2002

Quiz on Deterministic part of course October 22, 2002 Engneerng ystems Analyss for Desgn Quz on Determnstc part of course October 22, 2002 Ths s a closed book exercse. You may use calculators Grade Tables There are 90 ponts possble for the regular test, or

More information

Evaluating Performance

Evaluating Performance 5 Chapter Evaluatng Performance In Ths Chapter Dollar-Weghted Rate of Return Tme-Weghted Rate of Return Income Rate of Return Prncpal Rate of Return Daly Returns MPT Statstcs 5- Measurng Rates of Return

More information

Quantitative Portfolio Theory & Performance Analysis

Quantitative Portfolio Theory & Performance Analysis 550.447 Quanttatve ortfolo Theory & erformance Analyss Wee of March 4 & 11 (snow), 013 ast Algorthms, the Effcent ronter & the Sngle-Index Model Where we are Chapters 1-3 of AL: erformance, Rs and MT Chapters

More information

Introduction. Chapter 7 - An Introduction to Portfolio Management

Introduction. Chapter 7 - An Introduction to Portfolio Management Introducton In the next three chapters, we wll examne dfferent aspects of captal market theory, ncludng: Brngng rsk and return nto the pcture of nvestment management Markowtz optmzaton Modelng rsk and

More information

Consumption Based Asset Pricing

Consumption Based Asset Pricing Consumpton Based Asset Prcng Mchael Bar Aprl 25, 208 Contents Introducton 2 Model 2. Prcng rsk-free asset............................... 3 2.2 Prcng rsky assets................................ 4 2.3 Bubbles......................................

More information

FORD MOTOR CREDIT COMPANY SUGGESTED ANSWERS. Richard M. Levich. New York University Stern School of Business. Revised, February 1999

FORD MOTOR CREDIT COMPANY SUGGESTED ANSWERS. Richard M. Levich. New York University Stern School of Business. Revised, February 1999 FORD MOTOR CREDIT COMPANY SUGGESTED ANSWERS by Rchard M. Levch New York Unversty Stern School of Busness Revsed, February 1999 1 SETTING UP THE PROBLEM The bond s beng sold to Swss nvestors for a prce

More information

Problems to be discussed at the 5 th seminar Suggested solutions

Problems to be discussed at the 5 th seminar Suggested solutions ECON4260 Behavoral Economcs Problems to be dscussed at the 5 th semnar Suggested solutons Problem 1 a) Consder an ultmatum game n whch the proposer gets, ntally, 100 NOK. Assume that both the proposer

More information

Money, Banking, and Financial Markets (Econ 353) Midterm Examination I June 27, Name Univ. Id #

Money, Banking, and Financial Markets (Econ 353) Midterm Examination I June 27, Name Univ. Id # Money, Bankng, and Fnancal Markets (Econ 353) Mdterm Examnaton I June 27, 2005 Name Unv. Id # Note: Each multple-choce queston s worth 4 ponts. Problems 20, 21, and 22 carry 10, 8, and 10 ponts, respectvely.

More information

Domestic Savings and International Capital Flows

Domestic Savings and International Capital Flows Domestc Savngs and Internatonal Captal Flows Martn Feldsten and Charles Horoka The Economc Journal, June 1980 Presented by Mchael Mbate and Chrstoph Schnke Introducton The 2 Vews of Internatonal Captal

More information

UNIVERSITY OF NOTTINGHAM

UNIVERSITY OF NOTTINGHAM UNIVERSITY OF NOTTINGHAM SCHOOL OF ECONOMICS DISCUSSION PAPER 99/28 Welfare Analyss n a Cournot Game wth a Publc Good by Indraneel Dasgupta School of Economcs, Unversty of Nottngham, Nottngham NG7 2RD,

More information

To Rebalance or Not to Rebalance? Edward Qian, PhD, CFA PanAgora Asset Management

To Rebalance or Not to Rebalance? Edward Qian, PhD, CFA PanAgora Asset Management To Rebalance or Not to Rebalance? Edward Qan, PhD, CFA PanAgora Asset anagement To Rebalance or Not to Rebalance It s not THE QUESTION but a very mportant one»to rebalance fxed-weght (FW); Not to Buy and

More information

Appendix - Normally Distributed Admissible Choices are Optimal

Appendix - Normally Distributed Admissible Choices are Optimal Appendx - Normally Dstrbuted Admssble Choces are Optmal James N. Bodurtha, Jr. McDonough School of Busness Georgetown Unversty and Q Shen Stafford Partners Aprl 994 latest revson September 00 Abstract

More information

Ch Rival Pure private goods (most retail goods) Non-Rival Impure public goods (internet service)

Ch Rival Pure private goods (most retail goods) Non-Rival Impure public goods (internet service) h 7 1 Publc Goods o Rval goods: a good s rval f ts consumpton by one person precludes ts consumpton by another o Excludable goods: a good s excludable f you can reasonably prevent a person from consumng

More information

CHAPTER 9 FUNCTIONAL FORMS OF REGRESSION MODELS

CHAPTER 9 FUNCTIONAL FORMS OF REGRESSION MODELS CHAPTER 9 FUNCTIONAL FORMS OF REGRESSION MODELS QUESTIONS 9.1. (a) In a log-log model the dependent and all explanatory varables are n the logarthmc form. (b) In the log-ln model the dependent varable

More information

Tests for Two Ordered Categorical Variables

Tests for Two Ordered Categorical Variables Chapter 253 Tests for Two Ordered Categorcal Varables Introducton Ths module computes power and sample sze for tests of ordered categorcal data such as Lkert scale data. Assumng proportonal odds, such

More information

Price and Quantity Competition Revisited. Abstract

Price and Quantity Competition Revisited. Abstract rce and uantty Competton Revsted X. Henry Wang Unversty of Mssour - Columba Abstract By enlargng the parameter space orgnally consdered by Sngh and Vves (984 to allow for a wder range of cost asymmetry,

More information

An Application of Alternative Weighting Matrix Collapsing Approaches for Improving Sample Estimates

An Application of Alternative Weighting Matrix Collapsing Approaches for Improving Sample Estimates Secton on Survey Research Methods An Applcaton of Alternatve Weghtng Matrx Collapsng Approaches for Improvng Sample Estmates Lnda Tompkns 1, Jay J. Km 2 1 Centers for Dsease Control and Preventon, atonal

More information

Chapter 10 Making Choices: The Method, MARR, and Multiple Attributes

Chapter 10 Making Choices: The Method, MARR, and Multiple Attributes Chapter 0 Makng Choces: The Method, MARR, and Multple Attrbutes INEN 303 Sergy Butenko Industral & Systems Engneerng Texas A&M Unversty Comparng Mutually Exclusve Alternatves by Dfferent Evaluaton Methods

More information

Chapter 11: Optimal Portfolio Choice and the Capital Asset Pricing Model

Chapter 11: Optimal Portfolio Choice and the Capital Asset Pricing Model Chapter 11: Optmal Portolo Choce and the CAPM-1 Chapter 11: Optmal Portolo Choce and the Captal Asset Prcng Model Goal: determne the relatonshp between rsk and return key to ths process: examne how nvestors

More information

4. Greek Letters, Value-at-Risk

4. Greek Letters, Value-at-Risk 4 Greek Letters, Value-at-Rsk 4 Value-at-Rsk (Hull s, Chapter 8) Math443 W08, HM Zhu Outlne (Hull, Chap 8) What s Value at Rsk (VaR)? Hstorcal smulatons Monte Carlo smulatons Model based approach Varance-covarance

More information

Lecture Note 2 Time Value of Money

Lecture Note 2 Time Value of Money Seg250 Management Prncples for Engneerng Managers Lecture ote 2 Tme Value of Money Department of Systems Engneerng and Engneerng Management The Chnese Unversty of Hong Kong Interest: The Cost of Money

More information

OPERATIONS RESEARCH. Game Theory

OPERATIONS RESEARCH. Game Theory OPERATIONS RESEARCH Chapter 2 Game Theory Prof. Bbhas C. Gr Department of Mathematcs Jadavpur Unversty Kolkata, Inda Emal: bcgr.umath@gmal.com 1.0 Introducton Game theory was developed for decson makng

More information

Optimal Portfolio Construction (A Case Study of LQ45 Index in Indonesia Stock Exchange)

Optimal Portfolio Construction (A Case Study of LQ45 Index in Indonesia Stock Exchange) Internatonal Journal of Scence and Research (IJSR) ISS (Onlne): 319-7064 Index Coperncus Value (013): 6.14 Impact Factor (013): 4.438 Optmal Portfolo Constructon (A Case Study of LQ45 Index n Indonesa

More information

Clearing Notice SIX x-clear Ltd

Clearing Notice SIX x-clear Ltd Clearng Notce SIX x-clear Ltd 1.0 Overvew Changes to margn and default fund model arrangements SIX x-clear ( x-clear ) s closely montorng the CCP envronment n Europe as well as the needs of ts Members.

More information

25.1. Arbitrage Pricing Theory Introduction

25.1. Arbitrage Pricing Theory Introduction NPTEL Course Course Ttle: Securty Analyss and Portfolo Management Course Coordnator: Dr. Jtendra Mahakud Module-13 Sesson-25 Arbtrage Prcng Theory 25.1. Arbtrage Prcng Theory The fundamental prncple of

More information

Prospect Theory and Asset Prices

Prospect Theory and Asset Prices Fnance 400 A. Penat - G. Pennacch Prospect Theory and Asset Prces These notes consder the asset prcng mplcatons of nvestor behavor that ncorporates Prospect Theory. It summarzes an artcle by N. Barbers,

More information

Linear Combinations of Random Variables and Sampling (100 points)

Linear Combinations of Random Variables and Sampling (100 points) Economcs 30330: Statstcs for Economcs Problem Set 6 Unversty of Notre Dame Instructor: Julo Garín Sprng 2012 Lnear Combnatons of Random Varables and Samplng 100 ponts 1. Four-part problem. Go get some

More information

2) In the medium-run/long-run, a decrease in the budget deficit will produce:

2) In the medium-run/long-run, a decrease in the budget deficit will produce: 4.02 Quz 2 Solutons Fall 2004 Multple-Choce Questons ) Consder the wage-settng and prce-settng equatons we studed n class. Suppose the markup, µ, equals 0.25, and F(u,z) = -u. What s the natural rate of

More information

3: Central Limit Theorem, Systematic Errors

3: Central Limit Theorem, Systematic Errors 3: Central Lmt Theorem, Systematc Errors 1 Errors 1.1 Central Lmt Theorem Ths theorem s of prme mportance when measurng physcal quanttes because usually the mperfectons n the measurements are due to several

More information

- contrast so-called first-best outcome of Lindahl equilibrium with case of private provision through voluntary contributions of households

- contrast so-called first-best outcome of Lindahl equilibrium with case of private provision through voluntary contributions of households Prvate Provson - contrast so-called frst-best outcome of Lndahl equlbrum wth case of prvate provson through voluntary contrbutons of households - need to make an assumpton about how each household expects

More information

Final Exam. 7. (10 points) Please state whether each of the following statements is true or false. No explanation needed.

Final Exam. 7. (10 points) Please state whether each of the following statements is true or false. No explanation needed. Fnal Exam Fall 4 Econ 8-67 Closed Book. Formula Sheet Provded. Calculators OK. Tme Allowed: hours Please wrte your answers on the page below each queston. (5 ponts) Assume that the rsk-free nterest rate

More information

Scribe: Chris Berlind Date: Feb 1, 2010

Scribe: Chris Berlind Date: Feb 1, 2010 CS/CNS/EE 253: Advanced Topcs n Machne Learnng Topc: Dealng wth Partal Feedback #2 Lecturer: Danel Golovn Scrbe: Chrs Berlnd Date: Feb 1, 2010 8.1 Revew In the prevous lecture we began lookng at algorthms

More information

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 16

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 16 lton, Gruer, rown, and Goetzmann Modern Portfolo Theory and Investment nalyss, 7th dton Solutons to Text Prolems: hapter 6 hapter 6: Prolem From the text we know that three ponts determne a plane. The

More information

occurrence of a larger storm than our culvert or bridge is barely capable of handling? (what is The main question is: What is the possibility of

occurrence of a larger storm than our culvert or bridge is barely capable of handling? (what is The main question is: What is the possibility of Module 8: Probablty and Statstcal Methods n Water Resources Engneerng Bob Ptt Unversty of Alabama Tuscaloosa, AL Flow data are avalable from numerous USGS operated flow recordng statons. Data s usually

More information

Country Portfolios in Open Economy Macro Models *

Country Portfolios in Open Economy Macro Models * Federal Reserve Bank of Dallas Globalzaton and Monetary Polcy Insttute Workng Paper No. 9 http://www.dallasfed.org/assets/documents/nsttute/wpapers/2008/0009.pdf Country Portfolos n Open Economy Macro

More information

Financial Risk Management in Portfolio Optimization with Lower Partial Moment

Financial Risk Management in Portfolio Optimization with Lower Partial Moment Amercan Journal of Busness and Socety Vol., o., 26, pp. 2-2 http://www.ascence.org/journal/ajbs Fnancal Rsk Management n Portfolo Optmzaton wth Lower Partal Moment Lam Weng Sew, 2, *, Lam Weng Hoe, 2 Department

More information

A MODEL OF COMPETITION AMONG TELECOMMUNICATION SERVICE PROVIDERS BASED ON REPEATED GAME

A MODEL OF COMPETITION AMONG TELECOMMUNICATION SERVICE PROVIDERS BASED ON REPEATED GAME A MODEL OF COMPETITION AMONG TELECOMMUNICATION SERVICE PROVIDERS BASED ON REPEATED GAME Vesna Radonć Đogatovć, Valentna Radočć Unversty of Belgrade Faculty of Transport and Traffc Engneerng Belgrade, Serba

More information

3/3/2014. CDS M Phil Econometrics. Vijayamohanan Pillai N. Truncated standard normal distribution for a = 0.5, 0, and 0.5. CDS Mphil Econometrics

3/3/2014. CDS M Phil Econometrics. Vijayamohanan Pillai N. Truncated standard normal distribution for a = 0.5, 0, and 0.5. CDS Mphil Econometrics Lmted Dependent Varable Models: Tobt an Plla N 1 CDS Mphl Econometrcs Introducton Lmted Dependent Varable Models: Truncaton and Censorng Maddala, G. 1983. Lmted Dependent and Qualtatve Varables n Econometrcs.

More information

Chapter 11: Optimal Portfolio Choice and the Capital Asset Pricing Model

Chapter 11: Optimal Portfolio Choice and the Capital Asset Pricing Model Chapter 11: Optmal Portolo Choce and the CAPM-1 Chapter 11: Optmal Portolo Choce and the Captal Asset Prcng Model Goal: determne the relatonshp between rsk and return => key to ths process: examne how

More information

Test Bank to accompany Modern Portfolio Theory and Investment Analysis, 9 th Edition

Test Bank to accompany Modern Portfolio Theory and Investment Analysis, 9 th Edition Test ank to accopany Modern ortfolo Theory and Investent Analyss, 9 th Edton Test ank to accopany Modern ortfolo Theory and Investent Analyss, 9th Edton Copleted download lnk: https://testbankarea.co/download/odern-portfolotheory-nvestent-analyss-9th-edton-test-bank-eltongruber-brown-goetzann/

More information

/ Computational Genomics. Normalization

/ Computational Genomics. Normalization 0-80 /02-70 Computatonal Genomcs Normalzaton Gene Expresson Analyss Model Computatonal nformaton fuson Bologcal regulatory networks Pattern Recognton Data Analyss clusterng, classfcaton normalzaton, mss.

More information

ECE 586GT: Problem Set 2: Problems and Solutions Uniqueness of Nash equilibria, zero sum games, evolutionary dynamics

ECE 586GT: Problem Set 2: Problems and Solutions Uniqueness of Nash equilibria, zero sum games, evolutionary dynamics Unversty of Illnos Fall 08 ECE 586GT: Problem Set : Problems and Solutons Unqueness of Nash equlbra, zero sum games, evolutonary dynamcs Due: Tuesday, Sept. 5, at begnnng of class Readng: Course notes,

More information

Equilibrium in Prediction Markets with Buyers and Sellers

Equilibrium in Prediction Markets with Buyers and Sellers Equlbrum n Predcton Markets wth Buyers and Sellers Shpra Agrawal Nmrod Megddo Benamn Armbruster Abstract Predcton markets wth buyers and sellers of contracts on multple outcomes are shown to have unque

More information

Highlights of the Macroprudential Report for June 2018

Highlights of the Macroprudential Report for June 2018 Hghlghts of the Macroprudental Report for June 2018 October 2018 FINANCIAL STABILITY DEPARTMENT Preface Bank of Jamaca frequently conducts assessments of the reslence and strength of the fnancal system.

More information

Online Appendix for Merger Review for Markets with Buyer Power

Online Appendix for Merger Review for Markets with Buyer Power Onlne Appendx for Merger Revew for Markets wth Buyer Power Smon Loertscher Lesle M. Marx July 23, 2018 Introducton In ths appendx we extend the framework of Loertscher and Marx (forthcomng) to allow two

More information

Random Variables. b 2.

Random Variables. b 2. Random Varables Generally the object of an nvestgators nterest s not necessarly the acton n the sample space but rather some functon of t. Techncally a real valued functon or mappng whose doman s the sample

More information

Economic Design of Short-Run CSP-1 Plan Under Linear Inspection Cost

Economic Design of Short-Run CSP-1 Plan Under Linear Inspection Cost Tamkang Journal of Scence and Engneerng, Vol. 9, No 1, pp. 19 23 (2006) 19 Economc Desgn of Short-Run CSP-1 Plan Under Lnear Inspecton Cost Chung-Ho Chen 1 * and Chao-Yu Chou 2 1 Department of Industral

More information

Jeffrey Ely. October 7, This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License.

Jeffrey Ely. October 7, This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. October 7, 2012 Ths work s lcensed under the Creatve Commons Attrbuton-NonCommercal-ShareAlke 3.0 Lcense. Recap We saw last tme that any standard of socal welfare s problematc n a precse sense. If we want

More information

15-451/651: Design & Analysis of Algorithms January 22, 2019 Lecture #3: Amortized Analysis last changed: January 18, 2019

15-451/651: Design & Analysis of Algorithms January 22, 2019 Lecture #3: Amortized Analysis last changed: January 18, 2019 5-45/65: Desgn & Analyss of Algorthms January, 09 Lecture #3: Amortzed Analyss last changed: January 8, 09 Introducton In ths lecture we dscuss a useful form of analyss, called amortzed analyss, for problems

More information

Digital assets are investments with

Digital assets are investments with SANJIV R. DAS s a professor at Santa Clara Unversty n Santa Clara, CA. srdas@scu.edu Dgtal Portfolos SANJIV R. DAS Dgtal assets are nvestments wth bnary returns: the payoff s ether very large or very small.

More information

Risk, return and stock performance measures

Risk, return and stock performance measures Rsk, return and stock performance measures MIRELA MOMCILOVIC Hgher School of Professonal Busness Studes Vladmra Perca-Valtera 4, Nov Sad bznscentar@gmal.com http://www.vps.ns.ac.rs/sr/nastavnk.1.30.html?sn=237

More information

Accounting Information, Disclosure, and the Cost of Capital

Accounting Information, Disclosure, and the Cost of Capital Unversty of Pennsylvana ScholarlyCommons Accountng Papers Wharton Faculty Research 5-2007 Accountng Informaton, Dsclosure, and the Cost of Captal Rchard A. Lambert Unversty of Pennsylvana Chrstan Leuz

More information

MULTIPLE CURVE CONSTRUCTION

MULTIPLE CURVE CONSTRUCTION MULTIPLE CURVE CONSTRUCTION RICHARD WHITE 1. Introducton In the post-credt-crunch world, swaps are generally collateralzed under a ISDA Master Agreement Andersen and Pterbarg p266, wth collateral rates

More information

The Integration of the Israel Labour Force Survey with the National Insurance File

The Integration of the Israel Labour Force Survey with the National Insurance File The Integraton of the Israel Labour Force Survey wth the Natonal Insurance Fle Natale SHLOMO Central Bureau of Statstcs Kanfey Nesharm St. 66, corner of Bach Street, Jerusalem Natales@cbs.gov.l Abstact:

More information

Using Conditional Heteroskedastic

Using Conditional Heteroskedastic ITRON S FORECASTING BROWN BAG SEMINAR Usng Condtonal Heteroskedastc Varance Models n Load Research Sample Desgn Dr. J. Stuart McMenamn March 6, 2012 Please Remember» Phones are Muted: In order to help

More information

Lecture 7. We now use Brouwer s fixed point theorem to prove Nash s theorem.

Lecture 7. We now use Brouwer s fixed point theorem to prove Nash s theorem. Topcs on the Border of Economcs and Computaton December 11, 2005 Lecturer: Noam Nsan Lecture 7 Scrbe: Yoram Bachrach 1 Nash s Theorem We begn by provng Nash s Theorem about the exstance of a mxed strategy

More information

Applications of Myerson s Lemma

Applications of Myerson s Lemma Applcatons of Myerson s Lemma Professor Greenwald 28-2-7 We apply Myerson s lemma to solve the sngle-good aucton, and the generalzaton n whch there are k dentcal copes of the good. Our objectve s welfare

More information

New Distance Measures on Dual Hesitant Fuzzy Sets and Their Application in Pattern Recognition

New Distance Measures on Dual Hesitant Fuzzy Sets and Their Application in Pattern Recognition Journal of Artfcal Intellgence Practce (206) : 8-3 Clausus Scentfc Press, Canada New Dstance Measures on Dual Hestant Fuzzy Sets and Ther Applcaton n Pattern Recognton L Xn a, Zhang Xaohong* b College

More information

IND E 250 Final Exam Solutions June 8, Section A. Multiple choice and simple computation. [5 points each] (Version A)

IND E 250 Final Exam Solutions June 8, Section A. Multiple choice and simple computation. [5 points each] (Version A) IND E 20 Fnal Exam Solutons June 8, 2006 Secton A. Multple choce and smple computaton. [ ponts each] (Verson A) (-) Four ndependent projects, each wth rsk free cash flows, have the followng B/C ratos:

More information

c slope = -(1+i)/(1+π 2 ) MRS (between consumption in consecutive time periods) price ratio (across consecutive time periods)

c slope = -(1+i)/(1+π 2 ) MRS (between consumption in consecutive time periods) price ratio (across consecutive time periods) CONSUMPTION-SAVINGS FRAMEWORK (CONTINUED) SEPTEMBER 24, 2013 The Graphcs of the Consumpton-Savngs Model CONSUMER OPTIMIZATION Consumer s decson problem: maxmze lfetme utlty subject to lfetme budget constrant

More information

Optimal Service-Based Procurement with Heterogeneous Suppliers

Optimal Service-Based Procurement with Heterogeneous Suppliers Optmal Servce-Based Procurement wth Heterogeneous Supplers Ehsan Elah 1 Saf Benjaafar 2 Karen L. Donohue 3 1 College of Management, Unversty of Massachusetts, Boston, MA 02125 2 Industral & Systems Engneerng,

More information

OCR Statistics 1 Working with data. Section 2: Measures of location

OCR Statistics 1 Working with data. Section 2: Measures of location OCR Statstcs 1 Workng wth data Secton 2: Measures of locaton Notes and Examples These notes have sub-sectons on: The medan Estmatng the medan from grouped data The mean Estmatng the mean from grouped data

More information

Single-Item Auctions. CS 234r: Markets for Networks and Crowds Lecture 4 Auctions, Mechanisms, and Welfare Maximization

Single-Item Auctions. CS 234r: Markets for Networks and Crowds Lecture 4 Auctions, Mechanisms, and Welfare Maximization CS 234r: Markets for Networks and Crowds Lecture 4 Auctons, Mechansms, and Welfare Maxmzaton Sngle-Item Auctons Suppose we have one or more tems to sell and a pool of potental buyers. How should we decde

More information

Two Period Models. 1. Static Models. Econ602. Spring Lutz Hendricks

Two Period Models. 1. Static Models. Econ602. Spring Lutz Hendricks Two Perod Models Econ602. Sprng 2005. Lutz Hendrcks The man ponts of ths secton are: Tools: settng up and solvng a general equlbrum model; Kuhn-Tucker condtons; solvng multperod problems Economc nsghts:

More information

Advisory. Category: Capital

Advisory. Category: Capital Advsory Category: Captal NOTICE* Subject: Alternatve Method for Insurance Companes that Determne the Segregated Fund Guarantee Captal Requrement Usng Prescrbed Factors Date: Ths Advsory descrbes an alternatve

More information

General Examination in Microeconomic Theory. Fall You have FOUR hours. 2. Answer all questions

General Examination in Microeconomic Theory. Fall You have FOUR hours. 2. Answer all questions HARVARD UNIVERSITY DEPARTMENT OF ECONOMICS General Examnaton n Mcroeconomc Theory Fall 2010 1. You have FOUR hours. 2. Answer all questons PLEASE USE A SEPARATE BLUE BOOK FOR EACH QUESTION AND WRITE THE

More information

Lecture 6 Foundations of Finance. Lecture 6: The Intertemporal CAPM (ICAPM): A Multifactor Model and Empirical Evidence

Lecture 6 Foundations of Finance. Lecture 6: The Intertemporal CAPM (ICAPM): A Multifactor Model and Empirical Evidence Lecture 6 Foundatons of Fnance Lecture 6: The Intertemporal CAPM (ICAPM): A Multfactor Model and Emprcal Evdence I. Readng. II. ICAPM Assumptons. III. When do ndvduals care about more than expected return

More information

Taxation and Externalities. - Much recent discussion of policy towards externalities, e.g., global warming debate/kyoto

Taxation and Externalities. - Much recent discussion of policy towards externalities, e.g., global warming debate/kyoto Taxaton and Externaltes - Much recent dscusson of polcy towards externaltes, e.g., global warmng debate/kyoto - Increasng share of tax revenue from envronmental taxaton 6 percent n OECD - Envronmental

More information

Notes on experimental uncertainties and their propagation

Notes on experimental uncertainties and their propagation Ed Eyler 003 otes on epermental uncertantes and ther propagaton These notes are not ntended as a complete set of lecture notes, but nstead as an enumeraton of some of the key statstcal deas needed to obtan

More information

Problem Set #4 Solutions

Problem Set #4 Solutions 4.0 Sprng 00 Page Problem Set #4 Solutons Problem : a) The extensve form of the game s as follows: (,) Inc. (-,-) Entrant (0,0) Inc (5,0) Usng backwards nducton, the ncumbent wll always set hgh prces,

More information

A Meta Analysis of Real Estate Fund Performance

A Meta Analysis of Real Estate Fund Performance A Meta Analyss of Real Estate Fund Performance A Paper Presented at the ARES Annual Meetng Aprl 00 Naples, Florda Abstract Stephen Lee, Unversty of Readng * and Smon Stevenson, Unversty College Dubln Ths

More information

EDC Introduction

EDC Introduction .0 Introducton EDC3 In the last set of notes (EDC), we saw how to use penalty factors n solvng the EDC problem wth losses. In ths set of notes, we want to address two closely related ssues. What are, exactly,

More information

SOCIETY OF ACTUARIES FINANCIAL MATHEMATICS. EXAM FM SAMPLE SOLUTIONS Interest Theory

SOCIETY OF ACTUARIES FINANCIAL MATHEMATICS. EXAM FM SAMPLE SOLUTIONS Interest Theory SOCIETY OF ACTUARIES EXAM FM FINANCIAL MATHEMATICS EXAM FM SAMPLE SOLUTIONS Interest Theory Ths page ndcates changes made to Study Note FM-09-05. January 14, 014: Questons and solutons 58 60 were added.

More information

Asset Management. Country Allocation and Mutual Fund Returns

Asset Management. Country Allocation and Mutual Fund Returns Country Allocaton and Mutual Fund Returns By Dr. Lela Heckman, Senor Managng Drector and Dr. John Mulln, Managng Drector Bear Stearns Asset Management Bear Stearns Actve Country Equty Executve Summary

More information

Lecture 10: Valuation Models (with an Introduction to Capital Budgeting).

Lecture 10: Valuation Models (with an Introduction to Capital Budgeting). Foundatons of Fnance Lecture 10: Valuaton Models (wth an Introducton to Captal Budgetng). I. Readng. II. Introducton. III. Dscounted Cash Flow Models. IV. Relatve Valuaton Approaches. V. Contngent Clam

More information

Multifactor Term Structure Models

Multifactor Term Structure Models 1 Multfactor Term Structure Models A. Lmtatons of One-Factor Models 1. Returns on bonds of all maturtes are perfectly correlated. 2. Term structure (and prces of every other dervatves) are unquely determned

More information

Chapter 5 Bonds, Bond Prices and the Determination of Interest Rates

Chapter 5 Bonds, Bond Prices and the Determination of Interest Rates Chapter 5 Bonds, Bond Prces and the Determnaton of Interest Rates Problems and Solutons 1. Consder a U.S. Treasury Bll wth 270 days to maturty. If the annual yeld s 3.8 percent, what s the prce? $100 P

More information

THE MARKET PORTFOLIO MAY BE MEAN-VARIANCE EFFICIENT AFTER ALL

THE MARKET PORTFOLIO MAY BE MEAN-VARIANCE EFFICIENT AFTER ALL THE ARKET PORTFOIO AY BE EA-VARIACE EFFICIET AFTER A OSHE EVY and RICHARD RO ABSTRACT Testng the CAP bols down to testng the mean-varance effcency of the market portfolo. any studes have examned the meanvarance

More information

Simple Regression Theory II 2010 Samuel L. Baker

Simple Regression Theory II 2010 Samuel L. Baker SIMPLE REGRESSIO THEORY II Smple Regresson Theory II 00 Samuel L. Baker Assessng how good the regresson equaton s lkely to be Assgnment A gets nto drawng nferences about how close the regresson lne mght

More information

THE VOLATILITY OF EQUITY MUTUAL FUND RETURNS

THE VOLATILITY OF EQUITY MUTUAL FUND RETURNS North Amercan Journal of Fnance and Bankng Research Vol. 4. No. 4. 010. THE VOLATILITY OF EQUITY MUTUAL FUND RETURNS Central Connectcut State Unversty, USA. E-mal: BelloZ@mal.ccsu.edu ABSTRACT I nvestgated

More information

FM303. CHAPTERS COVERED : CHAPTERS 5, 8 and 9. LEARNER GUIDE : UNITS 1, 2 and 3.1 to 3.3. DUE DATE : 3:00 p.m. 19 MARCH 2013

FM303. CHAPTERS COVERED : CHAPTERS 5, 8 and 9. LEARNER GUIDE : UNITS 1, 2 and 3.1 to 3.3. DUE DATE : 3:00 p.m. 19 MARCH 2013 Page 1 of 11 ASSIGNMENT 1 ST SEMESTER : FINANCIAL MANAGEMENT 3 () CHAPTERS COVERED : CHAPTERS 5, 8 and 9 LEARNER GUIDE : UNITS 1, 2 and 3.1 to 3.3 DUE DATE : 3:00 p.m. 19 MARCH 2013 TOTAL MARKS : 100 INSTRUCTIONS

More information

University of Toronto November 9, 2006 ECO 209Y MACROECONOMIC THEORY. Term Test #1 L0101 L0201 L0401 L5101 MW MW 1-2 MW 2-3 W 6-8

University of Toronto November 9, 2006 ECO 209Y MACROECONOMIC THEORY. Term Test #1 L0101 L0201 L0401 L5101 MW MW 1-2 MW 2-3 W 6-8 Department of Economcs Prof. Gustavo Indart Unversty of Toronto November 9, 2006 SOLUTION ECO 209Y MACROECONOMIC THEORY Term Test #1 A LAST NAME FIRST NAME STUDENT NUMBER Crcle your secton of the course:

More information

University of Toronto November 9, 2006 ECO 209Y MACROECONOMIC THEORY. Term Test #1 L0101 L0201 L0401 L5101 MW MW 1-2 MW 2-3 W 6-8

University of Toronto November 9, 2006 ECO 209Y MACROECONOMIC THEORY. Term Test #1 L0101 L0201 L0401 L5101 MW MW 1-2 MW 2-3 W 6-8 Department of Economcs Prof. Gustavo Indart Unversty of Toronto November 9, 2006 SOLUTION ECO 209Y MACROECONOMIC THEORY Term Test #1 C LAST NAME FIRST NAME STUDENT NUMBER Crcle your secton of the course:

More information

Analysis of Variance and Design of Experiments-II

Analysis of Variance and Design of Experiments-II Analyss of Varance and Desgn of Experments-II MODULE VI LECTURE - 4 SPLIT-PLOT AND STRIP-PLOT DESIGNS Dr. Shalabh Department of Mathematcs & Statstcs Indan Insttute of Technology Kanpur An example to motvate

More information

II. Random Variables. Variable Types. Variables Map Outcomes to Numbers

II. Random Variables. Variable Types. Variables Map Outcomes to Numbers II. Random Varables Random varables operate n much the same way as the outcomes or events n some arbtrary sample space the dstncton s that random varables are smply outcomes that are represented numercally.

More information

Harry M. Markowitz. Investors Do Not Get Paid for Bearing Risk 1

Harry M. Markowitz. Investors Do Not Get Paid for Bearing Risk 1 Investors Do Not Get Pad for Bearng Rsk Harry M. Markowtz The relatonshp between the excess return of each securty and ts beta, where beta s defned as ts regresson aganst the return on the market portfolo,

More information

Efficient Project Portfolio as a Tool for Enterprise Risk Management

Efficient Project Portfolio as a Tool for Enterprise Risk Management Effcent Proect Portfolo as a Tool for Enterprse Rsk Management Valentn O. Nkonov Ural State Techncal Unversty Growth Traectory Consultng Company Enterprse Rsk Management Symposum Socety of Actuares Chcago,

More information