EDC Introduction
|
|
- Darcy Roberts
- 5 years ago
- Views:
Transcription
1 .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, penalty factors? How to obtan the penalty factors n practce?.0 What are penalty factors? Recall the defnton: (,, m) () In order to gan ntutve nsght nto what s a penalty factor, let s replace the numerator and denomnator of the partal dervatve n () wth the approxmaton of Δ /Δ, so:
2 () Multplyng top and bottom by Δ, we get: (3) What s Δ? It s a small change n generaton. But that cannot be all, because f you mae a change n generaton, then there must be a change n njecton at, at least, one other bus. et s assume that a compensatng change s dstrbuted throughout all other load buses accordng to a fxed percentage for each bus. By dong so, we are embracng the so-called conformng load assumpton, whch ndcates that all loads change proportonally. Therefore Δ =Δ D. But ths wll also cause a change n losses of Δ, whch wll be offset by a compensatng change n swng bus generaton Δ. So,
3 D (4) where we see generaton changes are on the left and load & loss changes are on the rght. Solvng for Δ -Δ (because t s n the denomnator of (3)), we get D (5) Substtutng (5) nto (3), we obtan: D (6a) Recognze that Δ n (6a) reflects the losses, we have D (6b) So from (6b), we extract the followng nterpretaton of the penalty factor: It s the amount of generaton at unt necessary to supply Δ D, as a percentage of Δ D -Δ. Ths depends on how the load s changed (whch s why we use the conformng load assumpton). If the change ncreases losses (Δ >0), then >. If the change decreases losses(δ <0), then <. 3
4 An example wll llustrate the sgnfcance of (6a) & (6b). Consder Fg.. Observe that the flows gven on the crcuts are nto bus (the flows along the lne out of buses and 3, respectvely, are hgher). Basecase Increase load by MW at each bus, compensated by gen ncrease at bus ( 0.) Increase load by MW at each bus, compensated by gen ncrease at bus Fg ( 0.)
5 One observes that <. Ths s because a load change compensated by a gen change at bus decreases the losses as ndcated by the fact that the bus generaton decreased by 0. MW. On the other hand, 3 >. Ths s because a load change compensated by a gen change at bus 3 ncreases the losses as ndcated by the fact that the bus generaton ncreases by 0.. MW. Why does the bus generaton reduce losses whereas the bus 3 generaton ncreases losses? Answer: Because ncreasng bus tends to reduce lne flows, whereas ncreasng bus 3 tends to ncrease lne flows. So we see that n general, generators on the recevng end of flows wll tend to have lower penalty factors (below.0); generators on the sendng end of flows wll tend to have hgher penalty factors (above.0). 5
6 Because transmsson systems are n fact relatvely effcent, wth reasonably small losses n the crcuts, the amount of generaton necessary to supply a load change tends to be very close to that load change. Therefore penalty factors tend to be relatvely close to.0. A lst of typcal penalty factors for the power system n Northern Calforna s llustrated n Fg.. enerators mared to the rght are unts n the San Francsco Bay Area, whch s a relatvely hgh mport area for the Northern Calforna system. Most of the penalty factors for these unts are below.0. Unts havng penalty factors>. are manly unts close to the Oregon border (a long way from the SF load center), such that they tend to add to the north-to-south flow that results from the northwest hydro beng sold nto the Calforna load centers. 6
7 Fg. But why do we actually call them penalty factors? Consder the crteron for optmalty n the EDC wth losses: C ( ),... m (7) 7
8 Ths says that all unts (or all regulatng unts) must be at a generaton level such that the product of ther ncremental cost and ther penalty factor must be equal to the system ncremental cost λ. et s do an experment to see what ths means. Consder that we have three dentcal unts such that ther ncremental cost-rate curves are dentcal, gven by IC( )= Now consder the three unts are so located such that unt has penalty factor of 0.98, unt has penalty factor of.0, and unt 3 has penalty factor of.0, and the demand s 300 MW. Wthout accountng for losses, ths problem would be very smple n that each unt would carry 00 MW. But wth losses, the problem s as follows: 8
9 9 λ=0.98( )= λ=.0( )= λ=.0( )= uttng these three equatons nto matrx form results n: Solvng n Matlab yelds: One notes that the unt wth the lower penalty (unt ) was turned up and the unt wth the hgher penalty (unt 3) was turned down. The reason for ths s that unt has a better effect on losses.
10 3.0 enalty factor calculaton There are several methods for penalty factor calculaton. We wll revew several of them n ths secton. Ths method s descrbed n []. Consder a power system wth total of n buses of whch bus s the swng bus, buses m are the V buses, and buses m+ n are the Q buses. Consder that losses must be equal to the dfference between the total system generaton and the total system demand: D (8) Recall the defnton for bus njectons, whch s D (9) Now sum the njectons over all buses to get: 0
11 D n D n n D n ) ( (0) Therefore, n () Now dfferentate wth respect to a partcular bus angle θ (where s any bus number except ) to obtan: n n m m,...,, () Assumpton to the above: All voltages are fxed at.0; ths releves us from accountng for varaton n power wth angle through the voltage magntude term. Otherwse, each term n () would appear as V V
12 Now let s assume that we have an expresson for losses as a functon of generaton, 3,, m,.e., = (, 3,, m ) (3) Then we can use the chan rule of dfferentaton to express that n m m,...,, ) ( ) ( (4) In (4), we assume that at generator buses, loads are constant, and / θ = / θ. Subtractng (4) from (), we obtan, for =,,n: n m m m m m n m m ) ( ) ( 0 from (4) ) ( ) ( from () Now brng the frst term to the left-handsde, for =,,n
13 3 Wrtng the above n m m m ) ( ) ( The above equaton, when wrtten for =,,n, can be expressed n matrx form as ) ( ) ( m n n n m n n m (5) The matrx on the left-hand sde s the transpose of the upper left-hand submatrx of the power flow Jacoban (we called t J θ ), and so codes are readly avalable to compute t. The elements of the rght-handsde vector may be found by dfferentatng the real power equaton for bus, whch s: ) sn( ) cos( N B V V (6) wth respect to each angle, resultng n
14 V V sn cos B The soluton vector contans the nverse of the penalty factors n the frst m- terms. 4.0 Usng loss formula The method of loss formula results n an approxmate expresson gven by T T 0 B 00 B B (7) where s the vector of generaton T (8) m Development of the coeffcent matrces n (7) has been done n several ways. The frst edton of the W&W text (986) presented a method developed by Meyer [] n Appendx B of chapter 4; t was removed from the second edton. I developed another method based on the wor of Kron, whch s partally artculated n the boo by El-Harawry and Chrstenson, and attached to the end of these notes. 4
15 Some mportant smlartes n the methods:. Both are dependent on the followng assumptons: Each bus can be clearly dstngushed as ether a load bus or a generaton bus. Reactve generaton vares lnearly wth generaton,.e., Q g =Q go +f g.. Both end up wth expressons for of the same form. 3. Both expressons for are dependent on the elements of the Z bus matrx. But there s one major dfference between the formulatons n that Kron s approach maes no assumpton regardng conformng loads. However, the method of W&W (Meyers) does,.e., n Meyer s approach, all loads must ncrease or decrease unformly. We assume that we have the so-called B- coeffcents n the example whch follows. 5
16 6
17 7
18 8
19 9
20 0
21 [] A. Bergen and V. Vttal, ower System Analyss, rentce-hall, 000. [] W. Meyer, Effcent computer soluton for Kron and Kron-Early oss Formulas, roc of the 973 ICA conference, IEEE 73 CHO 740-, WR, pp
22
23
24
25
26
27
28
29
30
31
32
33
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
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 informationPrice 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 informationTests 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 informationElton, 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 informationQuiz 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 informationEvaluating 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 informationAnswers 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 informationECE 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 informationApplications 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 information15-451/651: 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 informationEconomic 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 informationElton, 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 informationMgtOp 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 informationRandom 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 informationCHAPTER 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 informationFinance 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 informationConsumption 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>1 indicates country i has a comparative advantage in production of j; the greater the index, the stronger the advantage. RCA 1 ij
69 APPENDIX 1 RCA Indces In the followng we present some maor RCA ndces reported n the lterature. For addtonal varants and other RCA ndces, Memedovc (1994) and Vollrath (1991) provde more thorough revews.
More informationFinal Examination MATH NOTE TO PRINTER
Fnal Examnaton MATH 329 2005 01 1 NOTE TO PRINTER (These nstructons are for the prnter. They should not be duplcated.) Ths examnaton should be prnted on 8 1 2 14 paper, and stapled wth 3 sde staples, so
More informationOPERATIONS 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 informationImproved Marginal Loss Calculations During Hours of Transmission Congestion
Improved Margnal Loss Calculatons Durng Hours of Transmsson Congeston Judth B. Cardell Smth College jcardell@smth.edu Abstract Shortcomngs of the current polcy focus and accepted mplementatons for calculatng
More informationParallel Prefix addition
Marcelo Kryger Sudent ID 015629850 Parallel Prefx addton The parallel prefx adder presented next, performs the addton of two bnary numbers n tme of complexty O(log n) and lnear cost O(n). Lets notce the
More informationElements 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 informationUnderstanding 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 informationRaising Food Prices and Welfare Change: A Simple Calibration. Xiaohua Yu
Rasng Food Prces and Welfare Change: A Smple Calbraton Xaohua Yu Professor of Agrcultural Economcs Courant Research Centre Poverty, Equty and Growth Unversty of Göttngen CRC-PEG, Wlhelm-weber-Str. 2 3773
More informationMeasures 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 informationAn annuity is a series of payments made at equal intervals. There are many practical examples of financial transactions involving annuities, such as
2 Annutes An annuty s a seres of payments made at equal ntervals. There are many practcal examples of fnancal transactons nvolvng annutes, such as a car loan beng repad wth equal monthly nstallments a
More informationII. 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 informationAppendix for Solving Asset Pricing Models when the Price-Dividend Function is Analytic
Appendx for Solvng Asset Prcng Models when the Prce-Dvdend Functon s Analytc Ovdu L. Caln Yu Chen Thomas F. Cosmano and Alex A. Hmonas January 3, 5 Ths appendx provdes proofs of some results stated n our
More informationFall 2016 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out
Economcs 435 Menze D. Cnn Fall 6 Socal Scences 748 Unversty of Wsconsn-Madson. Standard IS-LM Transactons and ortfolo Crowdng Out Transactons crowdng out of nvestment s te reducton n nvestment attrbutable
More informationSurvey of Math: Chapter 22: Consumer Finance Borrowing Page 1
Survey of Math: Chapter 22: Consumer Fnance Borrowng Page 1 APR and EAR Borrowng s savng looked at from a dfferent perspectve. The dea of smple nterest and compound nterest stll apply. A new term s the
More informationSIMPLE FIXED-POINT ITERATION
SIMPLE FIXED-POINT ITERATION The fed-pont teraton method s an open root fndng method. The method starts wth the equaton f ( The equaton s then rearranged so that one s one the left hand sde of the equaton
More informationTCOM501 Networking: Theory & Fundamentals Final Examination Professor Yannis A. Korilis April 26, 2002
TO5 Networng: Theory & undamentals nal xamnaton Professor Yanns. orls prl, Problem [ ponts]: onsder a rng networ wth nodes,,,. In ths networ, a customer that completes servce at node exts the networ wth
More informationFacility Location Problem. Learning objectives. Antti Salonen Farzaneh Ahmadzadeh
Antt Salonen Farzaneh Ahmadzadeh 1 Faclty Locaton Problem The study of faclty locaton problems, also known as locaton analyss, s a branch of operatons research concerned wth the optmal placement of facltes
More informationWages as Anti-Corruption Strategy: A Note
DISCUSSION PAPER November 200 No. 46 Wages as Ant-Corrupton Strategy: A Note by dek SAO Faculty of Economcs, Kyushu-Sangyo Unversty Wages as ant-corrupton strategy: A Note dek Sato Kyushu-Sangyo Unversty
More informationUnderstanding price volatility in electricity markets
Proceedngs of the 33rd Hawa Internatonal Conference on System Scences - 2 Understandng prce volatlty n electrcty markets Fernando L. Alvarado, The Unversty of Wsconsn Rajesh Rajaraman, Chrstensen Assocates
More informationPASS Sample Size Software. :log
PASS Sample Sze Software Chapter 70 Probt Analyss Introducton Probt and lot analyss may be used for comparatve LD 50 studes for testn the effcacy of drus desned to prevent lethalty. Ths proram module presents
More informationChapter 3 Student Lecture Notes 3-1
Chapter 3 Student Lecture otes 3-1 Busness Statstcs: A Decson-Makng Approach 6 th Edton Chapter 3 Descrbng Data Usng umercal Measures 005 Prentce-Hall, Inc. Chap 3-1 Chapter Goals After completng ths chapter,
More informationCyclic Scheduling in a Job shop with Multiple Assembly Firms
Proceedngs of the 0 Internatonal Conference on Industral Engneerng and Operatons Management Kuala Lumpur, Malaysa, January 4, 0 Cyclc Schedulng n a Job shop wth Multple Assembly Frms Tetsuya Kana and Koch
More informationTests 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 informationFast Laplacian Solvers by Sparsification
Spectral Graph Theory Lecture 19 Fast Laplacan Solvers by Sparsfcaton Danel A. Spelman November 9, 2015 Dsclamer These notes are not necessarly an accurate representaton of what happened n class. The notes
More informationSupplementary material for Non-conjugate Variational Message Passing for Multinomial and Binary Regression
Supplementary materal for Non-conjugate Varatonal Message Passng for Multnomal and Bnary Regresson October 9, 011 1 Alternatve dervaton We wll focus on a partcular factor f a and varable x, wth the am
More informationAppendix - 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 informationProblem 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 informationMoney, 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 informationInstituto de Engenharia de Sistemas e Computadores de Coimbra Institute of Systems Engineering and Computers INESC - Coimbra
Insttuto de Engenhara de Sstemas e Computadores de Combra Insttute of Systems Engneerng and Computers INESC - Combra Joana Das Can we really gnore tme n Smple Plant Locaton Problems? No. 7 2015 ISSN: 1645-2631
More information4. 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 informationMode 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 informationCS 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 informationAnalysis 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 informationTradable Emissions Permits in the Presence of Trade Distortions
85 Tradable Emssons Permts n the Presence of Trade Dstortons Shnya Kawahara Abstract Ths paper nvestgates how trade lberalzaton affects domestc emssons tradng scheme n a poltcal economy framework. Developng
More informationAn Approach to Quantify the Loss Reduction due to Distributed Generation
nternatonal Journal of Computer Applcatons (0975 8887) Volume 5 No.17, August 01 An Approach to Quantfy the Loss Reducton due to Dstrbuted eneraton S B Karajg Department of Electrcal Engneerng S.D.M. College
More information2) 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 informationS yi a bx i cx yi a bx i cx 2 i =0. yi a bx i cx 2 i xi =0. yi a bx i cx 2 i x
LEAST-SQUARES FIT (Chapter 8) Ft the best straght lne (parabola, etc.) to a gven set of ponts. Ths wll be done by mnmzng the sum of squares of the vertcal dstances (called resduals) from the ponts to the
More informationECONOMETRICS - 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 informationMultifactor 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 informationFinal 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 informationISE High Income Index Methodology
ISE Hgh Income Index Methodology Index Descrpton The ISE Hgh Income Index s desgned to track the returns and ncome of the top 30 U.S lsted Closed-End Funds. Index Calculaton The ISE Hgh Income Index s
More informationUNIVERSITY 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 informationarxiv: v1 [q-fin.pm] 13 Feb 2018
WHAT IS THE SHARPE RATIO, AND HOW CAN EVERYONE GET IT WRONG? arxv:1802.04413v1 [q-fn.pm] 13 Feb 2018 IGOR RIVIN Abstract. The Sharpe rato s the most wdely used rsk metrc n the quanttatve fnance communty
More informationiii) 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 informationSpring 2018 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out
Economcs 44 Menze D. Cnn Sprng 8 Socal Scences 748 Unversty of Wsconsn-Madson. Standard IS-LM Transactons and Portfolo Crowdng Out Transactons crowdng out of nvestment s te reducton n nvestment attrbutable
More informationA New Uniform-based Resource Constrained Total Project Float Measure (U-RCTPF) Roni Levi. Research & Engineering, Haifa, Israel
Management Studes, August 2014, Vol. 2, No. 8, 533-540 do: 10.17265/2328-2185/2014.08.005 D DAVID PUBLISHING A New Unform-based Resource Constraned Total Project Float Measure (U-RCTPF) Ron Lev Research
More informationOptimising a general repair kit problem with a service constraint
Optmsng a general repar kt problem wth a servce constrant Marco Bjvank 1, Ger Koole Department of Mathematcs, VU Unversty Amsterdam, De Boelelaan 1081a, 1081 HV Amsterdam, The Netherlands Irs F.A. Vs Department
More informationSpring 2010 Social Sciences 7418 University of Wisconsin-Madison. The Financial and Economic Crisis Interpreted in a CC-LM Model
Publc Affars 854 Menze D. Chnn Sprng 2010 Socal Scences 7418 Unversty of Wsconsn-Madson The Fnancal and Economc Crss Interpreted n a CC-LM Model 1. Background: Typcal Fnancal Crss Source: Mshkn 2. Theory:
More informationDistortions in Two Sector Dynamic Models with Incomplete Specialization *
Dstortons n Two Sector Dynamc Models wth Incomplete Specalzaton * Erc W. Bond a# and Robert A. Drskll a a Vanderblt Unversty Abstract We extend the Jones (1971 analyss of the effects of dstortons n statc
More informationMacroeconomic 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 informationLecture 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 informationMacroeconomic 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 informationCh 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 information4: 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 informationLECTURE 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 informationWho Wins a Trade War? Mark Melatos, Pascalis Raimondos-Møller and Matthew Gibson. August 31, 2007
Who Wns a Trade War? Mark Melatos, Pascals Ramondos-Møller and Matthew Gbson August 31, 2007 Abstract. A trade war provdes an economc ratonale for the exstence of barrers to trade. The man result n ths
More informationTHIRD 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 informationCreating a zero coupon curve by bootstrapping with cubic splines.
MMA 708 Analytcal Fnance II Creatng a zero coupon curve by bootstrappng wth cubc splnes. erg Gryshkevych Professor: Jan R. M. Röman 0.2.200 Dvson of Appled Mathematcs chool of Educaton, Culture and Communcaton
More information/ 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 informationDecomposition of Value-Added in Gross Exports: Unresolved Issues and Possible Solutions
Decomposton of Value-Added n ross Exports: Unresolved Issues and Possble Solutons Sébasten Mroudot 1 and Mng Ye 2, OECD December 2017 Abstract: To better understand trade n the context of global value
More informationOptimal 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 informationDecomposition of Value-Added in Gross Exports:Unresolved Issues and Possible Solutions
MPRA Munch Personal RePEc Archve Decomposton of Value-Added n ross Exports:Unresolved Issues and Possble Solutons Sébasten Mroudot and Mng Ye 12 December 2017 Onlne at https://mpra.ub.un-muenchen.de/86346/
More information3/3/2014. 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 informationFinancial 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 informationCOMPARISON OF THE ANALYTICAL AND NUMERICAL SOLUTION OF A ONE-DIMENSIONAL NON-STATIONARY COOLING PROBLEM. László Könözsy 1, Mátyás Benke 2
COMPARISON OF THE ANALYTICAL AND NUMERICAL SOLUTION OF A ONE-DIMENSIONAL NON-STATIONARY COOLING PROBLEM László Könözsy 1, Mátyás Benke Ph.D. Student 1, Unversty Student Unversty of Mskolc, Department of
More informationTaxation 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 informationCapability Analysis. Chapter 255. Introduction. Capability Analysis
Chapter 55 Introducton Ths procedure summarzes the performance of a process based on user-specfed specfcaton lmts. The observed performance as well as the performance relatve to the Normal dstrbuton are
More informationAn 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 informationSolution 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 informationNote on Cubic Spline Valuation Methodology
Note on Cubc Splne Valuaton Methodology Regd. Offce: The Internatonal, 2 nd Floor THE CUBIC SPLINE METHODOLOGY A model for yeld curve takes traded yelds for avalable tenors as nput and generates the curve
More informationA 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 informationPrinciples 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 informationA FRAMEWORK FOR PRIORITY CONTACT OF NON RESPONDENTS
A FRAMEWORK FOR PRIORITY CONTACT OF NON RESPONDENTS Rchard McKenze, Australan Bureau of Statstcs. 12p36 Exchange Plaza, GPO Box K881, Perth, WA 6001. rchard.mckenze@abs.gov.au ABSTRACT Busnesses whch have
More informationOCR 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 informationTopics on the Border of Economics and Computation November 6, Lecture 2
Topcs on the Border of Economcs and Computaton November 6, 2005 Lecturer: Noam Nsan Lecture 2 Scrbe: Arel Procacca 1 Introducton Last week we dscussed the bascs of zero-sum games n strategc form. We characterzed
More informationOn the Moments of the Traces of Unitary and Orthogonal Random Matrices
Proceedngs of Insttute of Mathematcs of NAS of Ukrane 2004 Vol. 50 Part 3 1207 1213 On the Moments of the Traces of Untary and Orthogonal Random Matrces Vladmr VASILCHU B. Verkn Insttute for Low Temperature
More informationMicroeconomics: BSc Year One Extending Choice Theory
mcroeconomcs notes from http://www.economc-truth.co.uk by Tm Mller Mcroeconomcs: BSc Year One Extendng Choce Theory Consumers, obvously, mostly have a choce of more than two goods; and to fnd the favourable
More informationNew 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 informationMeasuring Comparative Advantage: A Ricardian Approach
Measurng Comparatve Advantage: A Rcardan Approach Johannes Moenus Unversty of Redlands Prelmnary, please do not cte comments hghly apprecated 06/12/2006 ABSTRACT In ths paper, we derve and compare several
More informationProceedings of the 2nd International Conference On Systems Engineering and Modeling (ICSEM-13)
Proceedngs of the 2nd Internatonal Conference On Systems Engneerng and Modelng (ICSEM-13) Research on the Proft Dstrbuton of Logstcs Company Strategc Allance Based on Shapley Value Huang Youfang 1, a,
More informationEquilibrium 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 informationJean-Paul Murara, Västeras, 26-April Mälardalen University, Sweden. Pricing EO under 2-dim. B S PDE by. using the Crank-Nicolson Method
Prcng EO under Mälardalen Unversty, Sweden Västeras, 26-Aprl-2017 1 / 15 Outlne 1 2 3 2 / 15 Optons - contracts that gve to the holder the rght but not the oblgaton to buy/sell an asset sometmes n the
More information