Lecture 9 Cochrane Chapter 8 Conditioning information

Size: px
Start display at page:

Download "Lecture 9 Cochrane Chapter 8 Conditioning information"

Transcription

1 Lecture 9 Cochrane Chapter 8 Condtonng normaton β u'( c t+ Pt = Et xt+ or Pt = Et mt+ xt+ or Pt = E mt+ xt+ It u'( ct normaton at tme t I x t and m t are d Vt, then uncondtonal expectatons are the same as condtonal expectatons. But ths s not always the case. We could make explct assumptons about I t (dcult. Instead o modelng condtonal dstrbutons, we would lke to use uncondtonal moments. Ths chapter dentes what condtonal dstrbutons mply or uncondtonal moments. Condtonng down Pt = Et mt+ xt+ Pt = Et mt+ xt+ Ω E( Pt = E mt+ xt+ E( Pt IcΩ = E mt+ xt+ I Law o terated expectatons: I you take an expected value (EV usng less normaton o an EV usng more normaton, you get back the EV usng less normaton. E E ( x = E( x { t } ( = E E x E x t t t+ t t+ E Ex ( Ω IcΩ = E xi

2 Multply the payos by an nstrument z t zp= E m x z t t t t+ t+ t New payo E( zp = E( m x z E( z = E( m R z New prce t t t+ t+ t t t+ t+ t Invest n asset accordng to z t managed portolo e.g. SMB,HML Checkng the (uncondtonal expected prce/return o all managed portolos s sucent to check all the mplcatons o condtonng normaton. So to deal wth condtonal dstrbutons, add managed portolos and use uncondtonal moments. A condtonal actor model does not mply an uncondtonal actor model. m = b b such that m = b ' ' t+ t t+ t+ t+ ' ' t+ = βtλt β ERt+ = β λ ER ( such that ( I senstvtes are tme-varyng, t s not OK to assume they are constant. I a portolo s MV ecent wth respect to a condtonal dstrbuton, t does not mply that the portolo s MV ecent uncondtonally.

3 Cochrane Chapter 9 Factor models m = a+ b' E( R = α + β ' λ t+ t+ t+ What characterstcs should actors have? ( based on economc oundaton e.g. related to consumpton ( orecastng varables predct returns or macro varables (3 hghly (maybe not completely unpredctable Classc dervatons o CAPM ( Consumpton CAPM, sngle perod ( Quadratc utlty, arbtrary returns, sngle perod (3 Negatve exponental utlty (general utlty, normally dstrbuted returns, sngle perod (4 Quadratc value uncton/bellman equaton, arbtrary returns, multperod (dynamc programmng (5 Intertemporal CAPM. Consumpton CAPM We dd ths at the end o Penat/Pennacch s notes enttled State Preerence Theory t Assume U '( C + = γr m perectly negatvely correlated 3

4 . Quadratc utlty, arbtrary returns t * Uc ( t = β ( ct c * * Uc ( t, ct+ = ( ct c β E ( ct+ c m * βu'( ct+ ( ct+ c t+ = = β * u'( ct ( ct c c = W t+ t+ W = R ( W c w t+ t t t N N w t t = = R = wr ; w = So m w * * Rt+ ( wt ct c βc β ( wt ct w t + = β = + R * * * t+ ct c ct c ct c Ths s a sngle actor model. c 3. Negatve exponental utlty, normally dstrbuted returns uc ( = e α, α > 0 coecent o absolute rsk averson We looked at some characterstcs o portolos chosen by an nvestor wth constant ARA n Penat/Pennacch s notes enttled Rsk Averson and Portolo Choce. α α Ec ( + σ ( c t I c η E(, c σ ( c E u( c = e wealth W, R, rsky assets return R, var-cov y = wealth ($ n each asset c= y R + y' R end o perod consumpton W = y + y' budget constrant Eu(c = e α α y R + y' E( R + y' y Max y, y E u(c gves y = ER ( R α 4

5 Amount nvested n rsky assets ndependent o wealth. E( R R = α y = αcov( R, R where R = y R + y ' R m m ER ( R m σ ( R m = α 4. Quadratc Bellman equaton, multperod U = u( c + β E V( W t t t+ η ( Wt + W * * I you have a quadratc utlty uncton uc ( t = ( ct c, you get a quadratc Bellman, so the problem looks lke the usual sngle perod quadratc utlty case. 5. Intertemporal CAPM We wll do ths later ater we go through contnuous tme mathematcs. Concerns about these models ( condtonal or uncondtonal? In general, these are condtonal models unless the structure s constant through tme (e.g. nvestment opportunty set s d, utlty uncton s the same, etc.. ( Does CAPM prce optons? Generally no apples to assets wth normally dstrbuted payos. Optons on stocks do not have normally dstrbuted returns. Yes quadratc utlty. 5

6 Fnance 400 A. Penat - G. Pennacch Arbtrage Prcng Theory The noton o arbtrage s smple. It nvolves the possblty o gettng somethng or nothng whle havng no possblty o loss. More speccally, suppose that an asset portolo can be constructed wthout requrng any ntal wealth. I ths zero-net-nvestment portolo can sometmes produce a postve return, but can never produce a negatve return, then t represents an arbtrage: startng rom zero wealth, a prot can sometmes be made but a loss can never occur. Aspecal case o arbtrage would be ths zero-net-nvestment portolo produces a rskless return. I ths certan return s postve (negatve, an arbtrage s to buy (sell the portolo and reap a rskless prot or ree lunch. Only the return was zero would there be no arbtrage. An arbtrage opportunty can also be dened n a slghtly derent context. I a portolo that requres a non-zero ntal net nvestment s created such that t earns a certan rate o return, then ths rate o return must equal the current (compettve maket rsk ree nterest rate. Otherwse, there would also be an arbtrage opportunty. For example, the portolo requred a postve ntal nvestment but earned less than the rsk ree rate, an arbtrage would be to (short sell the portolo and nvest the proceeds at the rsk ree rate, thereby earnng a rskless prot equal to the derence between the rsk ree rate and the portolo s certan (lower rate o return. In ecent, compettve, asset markets, t seems reasonable to thnk that easy prots dervng rom arbtrage opportuntes are rare and leetng. Should an arbtrage opportunty temporarly exst, then tradng by nvestors to earn ths rskless prot wll tend to move asset prces n a drecton that elmnates the arbtrage. For example, a zero-net-nvestment portolo produces Ths would lkely nvolve some borrowng or short sellng o assets as well as long postons n assets. Arbtrage dened n ths context s really equvalent to the prevous denton o arbtrage. For example, a portolo requrng a postve ntal nvestment produces a certan rate o return n excess o the rskless rate, then an nvestor should be able to borrow the ntal unds needed to create ths portolo and pay an nterest rate on ths loan that equals the rsk-ree nterest rate. That the nvestor should be able to borrow at the rskless nterest rate can be seen rom the act that the portolo produces a return that s always sucent to repay the loan n ull, makng the borrowng rsk-ree. Hence, combnng ths ntal borrowng wth the non-zero portolo nvestment results n an arbtrage opportunty that requres zero ntal wealth.

7 a rskless postve return, as nvestors create (buy ths portolo, the prces o the assets n the portolo wll be bd up. The cost o creatng the portolo wll then exceed zero. The portolo s cost wll rse untl t equals the present value o the portolo s rskless return, thereby elmnatng the arbtrage opportunty. Hence, n compettve asset markets, t may be reasonable to assume that equlbrum asset prces are such that no arbtrage opportuntes exst. As wll be shown, by assumng the absence o arbtrage, powerul asset prcng results can oten be derved. An early use o the arbtrage prncple s the covered nterest party condton n oregn exchange markets. To llustrate, let F 0t be the current (date 0 t-perod orward prce o one unt o oregn exchange. What ths orward prce represents s the dollar prce to be pad t perods n the uture or delvery o one unt o oregn exchange t perods n the uture. Let S 0 be the spot prce o oregn exchange, that s, the current (date 0 dollar prce o one unt o oregn currency to be delvered mmedately. Also let r 0t be the rsk ree borrowng or lendng rate or dollars over the perod 0 to t, and denote as r the rsk ree borrowng or lendng rate 0t or the oregn currency over the perod 0 to t. 3 Next consder settng up the ollowng portolo whch requres zero net wealth. Frst, let us sell orward (take a short orward poston n one unt o oregn exchange at prce F 0t. 4 Snce we are now commtted to delver one unt o oregn exchange at date t, let us also purchase the present value o one unt o oregn currency, /( + r, and nvest t at the oregn rsk 0t t ree rate, r0t. In terms o the domestc currency, ths purchase costs S 0 /( + r0t t, whch we nance by borrowng dollars at the rate r 0t. At date t, our oregn currency nvestment yelds ( + r /( + 0t t r = unt o the oregn 0t t currency whch we then delver to satsy our short poston n the orward oregn exchange contract. For delverng the currency, we receve F 0t dollars. But we also now owe rom our dollar borrowng a sum o ( + r 0t t S 0 /( + r. Thus, our net proceeds are 0t t F 0t ( + r0t t S0/( + r 0t t 3 For example, the oregn currency s the Japanese yen, r0t would be the nterest rate or a yen-denomnated rsk-ree nvestment or loan. 4 Takng a long or short poston n a orward contract requres zero ntal wealth, as payment and delvery all occur at the uture date t.

8 Note that these net proceeds are a certan return, that s, ths amount s known at date 0 snce t depends only on prces and rskless rates quoted at date 0. I ths amount was postve, then we should ndeed create ths portolo as t represents an arbtrage. I, nstead, ths amount was negatve, then an arbtrage would be or us to sell ths portolo, that s, we reverse each trade dscussed above (take a long orward poston, nvest n the domestc currency nanced by borrowng n oregn currency markets. Thus, the only nstance n whch arbtrage would not occur would be the net proceeds were zero, that s, F 0t = S 0 ( + r 0t t / ( + r 0t t whch s reerred to as the covered nterest party condton. Note that the orward exchange rate, F 0t, s determned wthout knowledge o the utlty unctons o ndvduals or ther expectatons regardng uture values o oregn currency. For ths reason, prcng (valung assets or contracts by usng arguments that rule out the exstence o arbtrage opportuntes can be very appealng. To motvate how arbtrage prcng mght apply to a very smple verson o the CAPM, suppose that there s a rsk ree asset that returns R and multple rsky assets. However, t s assumed that only a sngle source o (market rsk determnes all rsky asset returns and that these returns can be expressed by the lnear relatonshp R = a + b ( where R s the return on the th asset, a s ths asset s expected return, that s, E R =a. Further, s the sngle rsk actor generatng all asset returns, where E = 0, and b s the senstvty o asset to ths rsk actor. b can be vewed as asset s beta coecent. Note that ths s a hghly smpled example n that all rsky assets are perectly correlated wth each other. Now suppose that a portolo o two assets s constructed, where a proporton o wealth o w s nvested n asset and the remanng proporton o ( w s nvested n asset j. Ths portolo s return s gven by 3

9 R p = wa +( wa j +wb +( wb j ( = w(a a j +a j +w(b b j +b j I the portolo weghts are chosen such that w = b j b j b (3 then the uncertan (random component o the portolo s return s elmnated. The absence o arbtrage then requres that R p = R,sothat R p =w (a a j +a j =R or b j (a a j + a b j j = R b whch mples a R b = a j R b j λ (4 Ths condton states that the expected return n excess o the rsk ree rate, per unt o rsk, must be equal or all assets, and we dene ths rato as λ. λ s the rsk premum per unt o the actor rsk. The denomnator, b, can be nterpreted as asset s quantty o rsk rom the sngle rsk actor, whle a R can be thought o as asset s compensaton or premum n terms o excess expected return gven to nvestors or holdng asset. Thus, ths no-arbtrage condton s lke a law o one prce n that the prce o rsk, λ, whch s the premum dvded by the quantty, must be the same or all assets. Suppose that asset m has the same degree o rsk as the actor, that s, b m =. Thus, rom the above equlbrum condton λ = a m R, or we nterpret asset m as the beta = 4

10 market portolo, then λ = R m R. In terms o asset, the equlbrum condton can then be wrtten as a = R + b λ (5 = R + b ( R m R whch s the CAPM relaton. Thus, the CAPM can be derved by assumng there s only a sngle lnear rsk actor and that ths rsk actor has the same rsk as the market portolo. Let us now generalze the arbtrage prcng prncple to the case o multple rsk actors and allow ndvdual asset returns to have dosyncratc components. Thus, let there be k rsk actors and N assets n the economy, where k<n. Let b z be the senstvty o the th asset to the z th rsk actor, gven by z. Also let ε be the dosyncratc rsk component specc to asset, whch by denton s ndependent o the k rsk actors,,..., k, and the specc rsk component o any other asset j, εj. ε must be ndependent o the rsk actors or else t would aect all assets, thus not beng truly a specc source o rsk to just asset. I a s the expected return on asset, then the return generatng process or asset s gven by the lnear model where E ε = E z E z x = E ε ε j = E R = a + ε z k b z z + ε (6 z= = 0. For smplcty, we wll also assume that = 0, that s, the rsk actors are mutually ndependent. As t turns out, ths last assumpton s not mportant, as a lnear transormaton o correlated rsk actors can always be ound such that they can be redened as ndependent rsk actors. Another assumpton s that the dosyncratc rsk (varance or each asset be nte, that s E ε s <S (7 where S s some nte number. varance equal to one, so that we wll assume E ( cov R, z = cov (b z z, z Fnally, one can always normalze each rsk actor to have z =. Under these assumptons, note that ( = b z cov z, z = b z. Thus, b z s the covarance between the 5

11 return on asset and actor z. Let us now dene an asymptotc arbtrage opportunty. Denton: Let a portolo contanng n assets be descrbed by the vector o nvestment amounts n each o the n assets, w n w n wn... wn n. Consder a sequence o these portolos where n s ncreasng, n =,,.... Let σj be the covarance between the returns on assets and j. Then an asymptotc arbtrage exsts the ollowng condtons hold: (A The portolo requres zero net nvestment: w n =0 = (B The portolo return becomes certan as n gets large: lm n = j= w n wn j σ j 0 (C The portolo return s always bounded above zero j= w n a δ>0 We can now state the Arbtrage Prcng Theorem (APT: Theorem: I no asymptotc arbtrage opportuntes exst, then the expected return o asset, =,..., n, wll be descrbed by the ollowng lnear relaton a = λ0 + k z= bz λ z + ν where λ0 s a constant, λz can be nterpreted as the rsk premum or actor z, z =,..., k, and the expected return devatons, ν, satsy = ν =0 bz ν =0, z =,...,k ( = ( ( 6

12 lm n n = ν =0 ( Note that condton ( says that the average squared error (devaton rom the prcng rule ( goes to zero as nbecomes large. Thus, as the number o assets ncrease relatve to the rsk actors, expected returns wll, on average, become closely approxmated by the relaton a = λ0 + k z= b z λ z. Also note that the economy contans a rsk ree asset (mplyng b z =0, z, the rsk ree return wll be approxmated by λ 0. Proo: For a gven number o n assets >k, run a regresson o the a s on the bz s. In other words, project the dependent varable vector a =a a... an on the k explanatory varable vectors bz =bz bz... bnz, z=,..., k. Dene ν as the regresson resdual or observaton, =,...,n. Denote λ0 as the regresson ntercept and λz, z =,...,k, as the estmated coecent on explanatory varable z. The regresson estmates and resduals must then satsy k a = λ0 + bz λ z + ν (8 z= where by the propertes o an orthogonal projecton (Ordnary Least Squares regresson the resduals sum to zero, n = ν = 0, and are orthogonal to the regressors, n = bz ν = 0, z =,...,k. Thus, we have shown that (, (, and (, can be satsed. The last, but most mportant part o the proo, s to show that ( must hold n the absence o asymptotc arbtrage. Thus, let us construct an arbtrage portolo wth the ollowng weghts w = ν n= ν n (9 so that greater weghts are gven to assets havng the greatest expected return devaton. The total arbtrage portolo return s gven by R p = n = νn n ν R = = n = νn n = ν (a + k z= b z z + ε (0 Snce n = b zν =0,z=,...,k, ths equals 7

13 R p = n = νn n ν (a + ε = Let us calculate ths portolo s mean and varance. Takng expectatons, we obtan n E Rp = n ν = ν a n = ( ( snce E ε = 0. Substtutng n or a = λ0 + k z= b zλ z + ν,wehave E Rp = n = νn λ0 = ν + ( k z= λ z ν b z + = = ν (3 and snce n = ν = 0 and n = ν b z = 0, ths smples to E Rp = n = νn ν = = n ν (4 = To calculate the portolo s varance, start by subtractng ( rom ( Rp E Rp = n n= ν ν ε n = (5 Then because E ε εj =0or jand E ε =s, the portolo varance s E ( Rp E Rp = n= ν s n n = ν < n= ν S n n = ν = S n (6 Thus, as n becomes large (n, the varance o the portolo goes to zero, that s, the expected return on the portolo becomes certan. Ths mples that n the lmt the actual return equals the expected return n (4 lm n R p = E Rp = n ν (7 = and so there are no asymptotc arbtrage opportuntes, ths certan return on the portolo must equal zero, that s, 8

14 n ν = 0 (8 = whch s condton (. Q.E.D. Note that the APT can be vewed as a mult-beta generalzaton o CAPM. However, whereas CAPM says that ts sngle beta should be the senstvty o an asset s return to that o the market portolo, APT gves no gudance as to what are the economy s multple underlyng rsk-actors. Emprcal researchers have tended to select rsk actors based on those actors that provde the best t to hstorcal asset returns. We wll see another mult-beta asset prcng model, namely Merton s Intertemporal CAPM, whch s derved rom an ntertemporal consumer-nvestor optmzaton problem. However, that model predcts that the multple betas are not lkely to reman constant through tme, whch would cause sgncant dcultes when attemptng to estmate betas rom hstorcal data. 9

15 APT Cochrane Chapter 9 APT starts wth a statstcal characterzaton o outcomes/payos/returns. Ths eectvely places restrctons on the structure o the covarance matrx. e.g. cov( r, r = ββσ j j m Alternatvely, you can start wth the nvestor s utlty uncton and ask what varables/actors drve margnal utlty. The law o one prce (no arbtrage condton s very powerul when prcng redundant assets, but you want to prce a new non-redundant asset (.e. one that has senstvty to a new actor, the APT wll not help you. Exact actor model no resduals Approxmate actor model ncludes resduals I the resduals are small or dosyncratc, can the prce o an ndvdual asset be very derent rom the prce predcted by APT? In general, yes. It depends on cov( m, ε. See gure 7. How do you get rom the approxmate to the exact actor model? 6

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

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

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

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

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

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

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

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

Answers to exercises in Macroeconomics by Nils Gottfries 2013

Answers to exercises in Macroeconomics by Nils Gottfries 2013 . a) C C b C C s the ntercept o the consumpton uncton, how much consumpton wll be at zero ncome. We can thnk that, at zero ncome, the typcal consumer would consume out o hs assets. The slope b s the margnal

More information

iii) pay F P 0,T = S 0 e δt when stock has dividend yield δ.

iii) pay F P 0,T = S 0 e δt when stock has dividend yield δ. Fnal s Wed May 7, 12:50-2:50 You are allowed 15 sheets of notes and a calculator The fnal s cumulatve, so you should know everythng on the frst 4 revews Ths materal not on those revews 184) Suppose S t

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

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

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

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

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

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

Effects of a capital gains tax on asset pricing

Effects of a capital gains tax on asset pricing Busness Research (2018) 11:115 148 https://do.org/10.1007/s40685-017-0058-7 ORIGINAL RESEARCH Eects o a captal gans tax on asset prcng Marko Volker Krause 1 Receved: 21 Aprl 2016 / Accepted: 23 November

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

Option pricing and numéraires

Option pricing and numéraires Opton prcng and numérares Daro Trevsan Unverstà degl Stud d Psa San Mnato - 15 September 2016 Overvew 1 What s a numerare? 2 Arrow-Debreu model Change of numerare change of measure 3 Contnuous tme Self-fnancng

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

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

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

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

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

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

Which of the following provides the most reasonable approximation to the least squares regression line? (a) y=50+10x (b) Y=50+x (d) Y=1+50x

Which of the following provides the most reasonable approximation to the least squares regression line? (a) y=50+10x (b) Y=50+x (d) Y=1+50x Whch of the followng provdes the most reasonable approxmaton to the least squares regresson lne? (a) y=50+10x (b) Y=50+x (c) Y=10+50x (d) Y=1+50x (e) Y=10+x In smple lnear regresson the model that s begn

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

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

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

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

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

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

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

Testing for Omitted Variables

Testing for Omitted Variables Testng for Omtted Varables Jeroen Weese Department of Socology Unversty of Utrecht The Netherlands emal J.weese@fss.uu.nl tel +31 30 2531922 fax+31 30 2534405 Prepared for North Amercan Stata users meetng

More information

ACADEMIC ARTICLES ON THE TESTS OF THE CAPM

ACADEMIC ARTICLES ON THE TESTS OF THE CAPM ACADEMIC ARTICLES ON THE TESTS OF THE CAPM Page: o 5 The table below s a summary o the results o the early academc tests o the Captal Asset Prcng Model. The table lst the alpha correcton needed accordng

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

Midterm Exam. Use the end of month price data for the S&P 500 index in the table below to answer the following questions.

Midterm Exam. Use the end of month price data for the S&P 500 index in the table below to answer the following questions. Unversty of Washngton Summer 2001 Department of Economcs Erc Zvot Economcs 483 Mdterm Exam Ths s a closed book and closed note exam. However, you are allowed one page of handwrtten notes. Answer all questons

More information

Numerical Analysis ECIV 3306 Chapter 6

Numerical Analysis ECIV 3306 Chapter 6 The Islamc Unversty o Gaza Faculty o Engneerng Cvl Engneerng Department Numercal Analyss ECIV 3306 Chapter 6 Open Methods & System o Non-lnear Eqs Assocate Pro. Mazen Abualtaye Cvl Engneerng Department,

More information

the arbtrage cannot exst for long and ts lfetme depends on a lqudty of the market. Ths, however, does not mean that the arbtrage opportuntes do not ex

the arbtrage cannot exst for long and ts lfetme depends on a lqudty of the market. Ths, however, does not mean that the arbtrage opportuntes do not ex Vrtual Arbtrage Prcng Theory Krll Ilnsk School of Physcs and Space Research, Unversty of Brmngham, Edgbaston B5 2TT, Brmngham, Unted Kngdom Abstract We generalze the Arbtrage Prcng Theory (APT) to nclude

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

Economics 1410 Fall Section 7 Notes 1. Define the tax in a flexible way using T (z), where z is the income reported by the agent.

Economics 1410 Fall Section 7 Notes 1. Define the tax in a flexible way using T (z), where z is the income reported by the agent. Economcs 1410 Fall 2017 Harvard Unversty Yaan Al-Karableh Secton 7 Notes 1 I. The ncome taxaton problem Defne the tax n a flexble way usng T (), where s the ncome reported by the agent. Retenton functon:

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

ECONOMETRICS - FINAL EXAM, 3rd YEAR (GECO & GADE)

ECONOMETRICS - FINAL EXAM, 3rd YEAR (GECO & GADE) ECONOMETRICS - FINAL EXAM, 3rd YEAR (GECO & GADE) May 17, 2016 15:30 Frst famly name: Name: DNI/ID: Moble: Second famly Name: GECO/GADE: Instructor: E-mal: Queston 1 A B C Blank Queston 2 A B C Blank Queston

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

/ 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

CS 286r: Matching and Market Design Lecture 2 Combinatorial Markets, Walrasian Equilibrium, Tâtonnement

CS 286r: Matching and Market Design Lecture 2 Combinatorial Markets, Walrasian Equilibrium, Tâtonnement CS 286r: Matchng and Market Desgn Lecture 2 Combnatoral Markets, Walrasan Equlbrum, Tâtonnement Matchng and Money Recall: Last tme we descrbed the Hungaran Method for computng a maxmumweght bpartte matchng.

More information

Mode is the value which occurs most frequency. The mode may not exist, and even if it does, it may not be unique.

Mode is the value which occurs most frequency. The mode may not exist, and even if it does, it may not be unique. 1.7.4 Mode Mode s the value whch occurs most frequency. The mode may not exst, and even f t does, t may not be unque. For ungrouped data, we smply count the largest frequency of the gven value. If all

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

Understanding Annuities. Some Algebraic Terminology.

Understanding Annuities. Some Algebraic Terminology. Understandng Annutes Ma 162 Sprng 2010 Ma 162 Sprng 2010 March 22, 2010 Some Algebrac Termnology We recall some terms and calculatons from elementary algebra A fnte sequence of numbers s a functon of natural

More information

THIRTY YEARS AGO marked the publication of what has come to be

THIRTY YEARS AGO marked the publication of what has come to be ONE NO ARBITRAGE: THE FUNDAMENTAL THEOREM OF FINANCE THIRTY YEARS AGO marked the publcaton of what has come to be known as the Fundamental Theorem of Fnance and the dscovery of rsk-neutral prcng. The earler

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

Chapter 5 Student Lecture Notes 5-1

Chapter 5 Student Lecture Notes 5-1 Chapter 5 Student Lecture Notes 5-1 Basc Busness Statstcs (9 th Edton) Chapter 5 Some Important Dscrete Probablty Dstrbutons 004 Prentce-Hall, Inc. Chap 5-1 Chapter Topcs The Probablty Dstrbuton of a Dscrete

More information

Introduction to PGMs: Discrete Variables. Sargur Srihari

Introduction to PGMs: Discrete Variables. Sargur Srihari Introducton to : Dscrete Varables Sargur srhar@cedar.buffalo.edu Topcs. What are graphcal models (or ) 2. Use of Engneerng and AI 3. Drectonalty n graphs 4. Bayesan Networks 5. Generatve Models and Samplng

More information

Measures of Spread IQR and Deviation. For exam X, calculate the mean, median and mode. For exam Y, calculate the mean, median and mode.

Measures of Spread IQR and Deviation. For exam X, calculate the mean, median and mode. For exam Y, calculate the mean, median and mode. Part 4 Measures of Spread IQR and Devaton In Part we learned how the three measures of center offer dfferent ways of provdng us wth a sngle representatve value for a data set. However, consder the followng

More information

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

AN EMPIRICAL TESTING OF CAPITAL ASSET PRICING MODEL IN BANGLADESH

AN EMPIRICAL TESTING OF CAPITAL ASSET PRICING MODEL IN BANGLADESH Journal o Research (Scence), Bahauddn Zakarya Unversty, Multan, Pakstan. Vol.17, No.4, October 2006, pp. 225-234 ISSN 1021-1012 AN EMPIRICAL TESTING OF CAPITAL ASSET PRICING MODEL IN BANGLADESH Md. Mostazur

More information

Survey of Math Test #3 Practice Questions Page 1 of 5

Survey of Math Test #3 Practice Questions Page 1 of 5 Test #3 Practce Questons Page 1 of 5 You wll be able to use a calculator, and wll have to use one to answer some questons. Informaton Provded on Test: Smple Interest: Compound Interest: Deprecaton: A =

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

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

Notes are not permitted in this examination. Do not turn over until you are told to do so by the Invigilator.

Notes are not permitted in this examination. Do not turn over until you are told to do so by the Invigilator. UNIVERSITY OF EAST ANGLIA School of Economcs Man Seres PG Examnaton 2016-17 BANKING ECONOMETRICS ECO-7014A Tme allowed: 2 HOURS Answer ALL FOUR questons. Queston 1 carres a weght of 30%; queston 2 carres

More information

Chapter 15: Debt and Taxes

Chapter 15: Debt and Taxes Chapter 15: Debt and Taxes-1 Chapter 15: Debt and Taxes I. Basc Ideas 1. Corporate Taxes => nterest expense s tax deductble => as debt ncreases, corporate taxes fall => ncentve to fund the frm wth debt

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

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

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

Understanding Predictability (JPE, 2004)

Understanding Predictability (JPE, 2004) Understandng Predctablty (JPE, 2004) Lor Menzly, Tano Santos, and Petro Verones Presented by Peter Gross NYU October 27, 2009 Presented by Peter Gross (NYU) Understandng Predctablty October 27, 2009 1

More information

LECTURE 3. Chapter # 5: Understanding Interest Rates: Determinants and Movements

LECTURE 3. Chapter # 5: Understanding Interest Rates: Determinants and Movements LECTURE 3 Hamza Al alk Econ 3215: oney and ankng Wnter 2007 Chapter # 5: Understandng Interest Rates: Determnants and ovements The Loanable Funds Approach suggests that nterest rate levels are determned

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

Macroeconomic Theory and Policy

Macroeconomic Theory and Policy ECO 209 Macroeconomc Theory and Polcy Lecture 7: The Open Economy wth Fxed Exchange Rates Gustavo Indart Slde 1 Open Economy under Fxed Exchange Rates Let s consder an open economy wth no captal moblty

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

Correlations and Copulas

Correlations and Copulas Correlatons and Copulas Chapter 9 Rsk Management and Fnancal Insttutons, Chapter 6, Copyrght John C. Hull 2006 6. Coeffcent of Correlaton The coeffcent of correlaton between two varables V and V 2 s defned

More information

THIRD MIDTERM EXAM EC26102: MONEY, BANKING AND FINANCIAL MARKETS MARCH 24, 2004

THIRD MIDTERM EXAM EC26102: MONEY, BANKING AND FINANCIAL MARKETS MARCH 24, 2004 THIRD MIDTERM EXAM EC26102: MONEY, BANKING AND FINANCIAL MARKETS MARCH 24, 2004 Ths exam has questons on eght pages. Before you begn, please check to make sure that your copy has all questons and all eght

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

Module Contact: Dr P Moffatt, ECO Copyright of the University of East Anglia Version 2

Module Contact: Dr P Moffatt, ECO Copyright of the University of East Anglia Version 2 UNIVERSITY OF EAST ANGLIA School of Economcs Man Seres PG Examnaton 2012-13 FINANCIAL ECONOMETRICS ECO-M017 Tme allowed: 2 hours Answer ALL FOUR questons. Queston 1 carres a weght of 25%; Queston 2 carres

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

THE IMPORTANCE OF THE NUMBER OF DIFFERENT AGENTS IN A HETEROGENEOUS ASSET-PRICING MODEL WOUTER J. DEN HAAN

THE IMPORTANCE OF THE NUMBER OF DIFFERENT AGENTS IN A HETEROGENEOUS ASSET-PRICING MODEL WOUTER J. DEN HAAN THE IMPORTANCE OF THE NUMBER OF DIFFERENT AGENTS IN A HETEROGENEOUS ASSET-PRICING MODEL WOUTER J. DEN HAAN Department of Economcs, Unversty of Calforna at San Dego and Natonal Bureau of Economc Research

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

Increasing the Accuracy of Option Pricing by Using Implied Parameters Related to Higher Moments. Dasheng Ji. and. B. Wade Brorsen*

Increasing the Accuracy of Option Pricing by Using Implied Parameters Related to Higher Moments. Dasheng Ji. and. B. Wade Brorsen* Increasng the Accuracy of Opton Prcng by Usng Impled Parameters Related to Hgher Moments Dasheng J and B. Wade Brorsen* Paper presented at the CR-34 Conference on Appled Commodty Prce Analyss, orecastng,

More information

EPPE6024: Macroeconomics Lecture 2: Aggregate Demand (AD), Aggregate Supply (AS), and Business Cycle

EPPE6024: Macroeconomics Lecture 2: Aggregate Demand (AD), Aggregate Supply (AS), and Business Cycle EE6024: Macroeconomcs Lecture 2: Aggregate Demand (AD), Aggregate Suppl (AS), and Busness Ccle The Goods Market: the IS curve IS curve shows the combnaton of the nterest rates and output level at whch

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

International Financial Management

International Financial Management Multnatonal Corporatons (MNC Internatonal nancal Management nance ummer 006 xed versus loatng Exchange Rates loatng xed Managed floatng rate Currences float freely n ths, and s (prces are set by supply

More information

4: SPOT MARKET MODELS

4: SPOT MARKET MODELS 4: SPOT MARKET MODELS INCREASING COMPETITION IN THE BRITISH ELECTRICITY SPOT MARKET Rchard Green (1996) - Journal of Industral Economcs, Vol. XLIV, No. 2 PEKKA SULAMAA The obect of the paper Dfferent polcy

More information

Financial mathematics

Financial mathematics Fnancal mathematcs Jean-Luc Bouchot jean-luc.bouchot@drexel.edu February 19, 2013 Warnng Ths s a work n progress. I can not ensure t to be mstake free at the moment. It s also lackng some nformaton. But

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

Finite Math - Fall Section Future Value of an Annuity; Sinking Funds

Finite Math - Fall Section Future Value of an Annuity; Sinking Funds Fnte Math - Fall 2016 Lecture Notes - 9/19/2016 Secton 3.3 - Future Value of an Annuty; Snkng Funds Snkng Funds. We can turn the annutes pcture around and ask how much we would need to depost nto an account

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

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

Solution of periodic review inventory model with general constrains

Solution of periodic review inventory model with general constrains Soluton of perodc revew nventory model wth general constrans Soluton of perodc revew nventory model wth general constrans Prof Dr J Benkő SZIU Gödöllő Summary Reasons for presence of nventory (stock of

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

INTRODUCTION TO MACROECONOMICS FOR THE SHORT RUN (CHAPTER 1) WHY STUDY BUSINESS CYCLES? The intellectual challenge: Why is economic growth irregular?

INTRODUCTION TO MACROECONOMICS FOR THE SHORT RUN (CHAPTER 1) WHY STUDY BUSINESS CYCLES? The intellectual challenge: Why is economic growth irregular? INTRODUCTION TO MACROECONOMICS FOR THE SHORT RUN (CHATER 1) WHY STUDY BUSINESS CYCLES? The ntellectual challenge: Why s economc groth rregular? The socal challenge: Recessons and depressons cause elfare

More information

Allocating fixed costs in the postal sector in the presence of changing letter and parcel volumes: applied in outdoor delivery

Allocating fixed costs in the postal sector in the presence of changing letter and parcel volumes: applied in outdoor delivery IDEI- 764 February 3 Allocatng ed costs n the postal sector n the presence o changng letter and parcel volumes: appled n outdoor delvery P.De Donder H.remer P.Dudley and F.Rodrguez Allocatng ed costs n

More information

Consolidating Distribution Centers Can Reduce Lost Sales

Consolidating Distribution Centers Can Reduce Lost Sales Consoldatng Dstrbuton Centers Can Reduce Lost Sales Robert Bordley, Mark Beltramo & Denns Blumenfeld General Motors Research & Development Center Warren, Mchgan 48090-9055 June 15, 2006 Abstract Ths paper

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

Measuring the Risk and Performance in Plantation Sector Using CAPM Based Jensen s Alpha

Measuring the Risk and Performance in Plantation Sector Using CAPM Based Jensen s Alpha Measurng the Rsk and Perormance n Plantaton Sector Usng CAPM Based Jensen s Alpha D.A.I. Dayaratne D.G Dharmaratne SA Hars Department o Accountancy and Fnance Sabaragamuwa Unversty, Belhuloya Abstract

More information

ISyE 512 Chapter 9. CUSUM and EWMA Control Charts. Instructor: Prof. Kaibo Liu. Department of Industrial and Systems Engineering UW-Madison

ISyE 512 Chapter 9. CUSUM and EWMA Control Charts. Instructor: Prof. Kaibo Liu. Department of Industrial and Systems Engineering UW-Madison ISyE 512 hapter 9 USUM and EWMA ontrol harts Instructor: Prof. Kabo Lu Department of Industral and Systems Engneerng UW-Madson Emal: klu8@wsc.edu Offce: Room 317 (Mechancal Engneerng Buldng) ISyE 512 Instructor:

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

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

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

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

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

ECO 209Y MACROECONOMIC THEORY AND POLICY LECTURE 8: THE OPEN ECONOMY WITH FIXED EXCHANGE RATES

ECO 209Y MACROECONOMIC THEORY AND POLICY LECTURE 8: THE OPEN ECONOMY WITH FIXED EXCHANGE RATES ECO 209 MACROECONOMIC THEOR AND POLIC LECTURE 8: THE OPEN ECONOM WITH FIXED EXCHANGE RATES Gustavo Indart Slde 1 OPEN ECONOM UNDER FIXED EXCHANGE RATES Let s consder an open economy wth no captal moblty

More information