Major: All Engineering Majors. Authors: Autar Kaw, Jai Paul

Size: px
Start display at page:

Download "Major: All Engineering Majors. Authors: Autar Kaw, Jai Paul"

Transcription

1 Secant Method Major: All Engneerng Majors Authors: Autar Kaw, Ja Paul Transormng Numercal Methods Educaton or STEM Undergraduates /0/00

2 Secant Method

3 Secant Method Dervaton () ( ) ( - ) θ + + [ ( )], Fgure Geometrcal llustraton o the Newton-Raphson method. X Newton s Method ( ) + - ( ) ( + ) ( ) ( ( ( )( ) ) ( () Appromate the dervatve () Substtutng Equaton () nto Equaton () gves the Secant method ) )

4 Secant Method Dervaton The secant method can also be derved rom geometry: () ( ) ( - ) C E D A + - B X The Geometrc Smlar Trangles AB DC AE DE can be wrtten as ( ) ( ) + + On rearrangng, the secant method s gven as Fgure Geometrcal representaton o the Secant method. + ( ( )( ) ( ) ) 4

5 Algorthm or Secant Method 5

6 6 Step 00 - a + + Calculate the net estmate o the root rom two ntal guesses Fnd the absolute relatve appromate error ) ( ) ( ) )( ( +

7 Step Fnd the absolute relatve appromate error s greater than the prespeced relatve error tolerance. I so, go back to step, else stop the algorthm. Also check the number o teratons has eceeded the mamum number o teratons. 7

8 Eample You are workng or DOWN THE TOILET COMPANY that makes loats or ABC commodes. The loatng ball has a specc gravty o 0.6 and has a radus o 5.5 cm. You are asked to nd the depth to whch the ball s submerged when loatng n water. 8 Fgure Floatng Ball Problem.

9 Eample Cont. 9 The equaton that gves the depth to whch the ball s submerged under water s gven by ( ) 4 Use the Secant method o ndng roots o equatons to nd the depth to whch the ball s submerged under water. Conduct three teratons to estmate the root o the above equaton. Fnd the absolute relatve appromate error and the number o sgncant dgts at least correct at the end o each teraton.

10 To ad n the understandng o how ths method works to nd the root o an equaton, the graph o () s shown to the rght, where Soluton ( ) Eample Cont. Fgure 4 Graph o the uncton (). 0

11 Eample Cont. Let us assume the ntal guesses o the root o as 0.0 and ( ) 0 0 Iteraton The estmate o the root s ( 0 )( 0 ) ( 0 ) ( ) ( ( 0.05) )( ) ( 0.05) ( ) ( ( ).99 0 )

12 Eample Cont. The absolute relatve appromate error Iteraton s a % 00 a at the end o The number o sgncant dgts at least correct s 0, as you need an absolute relatve appromate error o 5% or less or one sgncant dgts to be correct n your result.

13 Eample Cont. Fgure 5 Graph o results o Iteraton.

14 Eample Cont. Iteraton The estmate o the root s ( )( 0 ) ( ) ( ) 0 4 ( ( ) )( ) ( ) ( ) ( ( ).99 0 )

15 Eample Cont. The absolute relatve appromate error Iteraton s a % 00 a at the end o The number o sgncant dgts at least correct s, as you need an absolute relatve appromate error o 5% or less. 5

16 Eample Cont. Fgure 6 Graph o results o Iteraton. 6

17 Eample Cont. Iteraton The estmate o the root s ( )( ) ( ) ( ) 4 ( ( 0.064) )( ) ( 0.064) ( ) ( ( ).99 0 )

18 Eample Cont. The absolute relatve appromate error Iteraton s a % 00 a at the end o The number o sgncant dgts at least correct s 5, as you need an absolute relatve appromate error o 0.5% or less. 8

19 Iteraton # Fgure 7 Graph o results o Iteraton. 9

20 Advantages Converges ast, t converges Requres two guesses that do not need to bracket the root 0

21 Drawbacks ( ) ( ) ( ) () prev. guess new guess, guess, guess Dvson by zero ( ) Sn( ) 0 0

22 Drawbacks (contnued) ( ) ( ) ( ) secant( ) ( ) , 0, ',, () ', (rst guess) 0, (prevous guess) Secant lne, (new guess) Root Jumpng ( ) Sn 0 0

23 Addtonal Resources For all resources on ths topc such as dgtal audovsual lectures, prmers, tetbook chapters, multple-choce tests, worksheets n MATLAB, MATHEMATICA, MathCad and MAPLE, blogs, related physcal problems, please vst thod.html

24 THE END

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

SIMPLE FIXED-POINT ITERATION

SIMPLE 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 information

The Islamic University of Gaza Faculty of Engineering Civil Engineering Department Numerical Analysis ECIV 3306 Chapter 6 Open Methods

The Islamic University of Gaza Faculty of Engineering Civil Engineering Department Numerical Analysis ECIV 3306 Chapter 6 Open Methods The Islamc Unerst o Gaza Faclt o Engneerng Cl Engneerng Department Nmercal Analss ECIV 3306 Chapter 6 Open Methods Open Methods Bracketng methods are based on assmng an nteral o the ncton whch brackets

More information

TCOM501 Networking: Theory & Fundamentals Final Examination Professor Yannis A. Korilis April 26, 2002

TCOM501 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 information

Numerical Analysis Math 370 Spring 2009 MWF 11:30am - 12:25pm Fowler 110 c 2009 Ron Buckmire

Numerical Analysis Math 370 Spring 2009 MWF 11:30am - 12:25pm Fowler 110 c 2009 Ron Buckmire Numerical Analysis Math 37 Spring 9 MWF 11:3am - 1:pm Fowler 11 c 9 Ron Buckmire http://faculty.oxy.edu/ron/math/37/9/ Worksheet 9 SUMMARY Other Root-finding Methods (False Position, Newton s and Secant)

More information

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

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

More information

Homework 9: due Monday, 27 October, 2008

Homework 9: due Monday, 27 October, 2008 PROBLEM ONE Homework 9: due Monday, 7 October, 008. (Exercses from the book, 6 th edton, 6.6, -3.) Determne the number of dstnct orderngs of the letters gven: (a) GUIDE (b) SCHOOL (c) SALESPERSONS. (Exercses

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

Creating a zero coupon curve by bootstrapping with cubic splines.

Creating 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

Supplementary material for Non-conjugate Variational Message Passing for Multinomial and Binary Regression

Supplementary 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 information

Notes on experimental uncertainties and their propagation

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

More information

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

COMPARISON 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 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 information

ME 310 Numerical Methods. Differentiation

ME 310 Numerical Methods. Differentiation M 0 Numercal Metods fferentaton Tese presentatons are prepared by r. Cuneyt Sert Mecancal ngneerng epartment Mddle ast Tecncal Unversty Ankara, Turkey csert@metu.edu.tr Tey can not be used wtout te permsson

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

Numerical Optimisation Applied to Monte Carlo Algorithms for Finance. Phillip Luong

Numerical Optimisation Applied to Monte Carlo Algorithms for Finance. Phillip Luong Numercal Optmsaton Appled to Monte Carlo Algorthms for Fnance Phllp Luong Supervsed by Professor Hans De Sterck, Professor Gregore Loeper, and Dr Ivan Guo Monash Unversty Vacaton Research Scholarshps are

More information

Chapter 3 Student Lecture Notes 3-1

Chapter 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 information

Hewlett Packard 10BII Calculator

Hewlett Packard 10BII Calculator Hewlett Packard 0BII Calculator Keystrokes for the HP 0BII are shown n the tet. However, takng a mnute to revew the Quk Start secton, below, wll be very helpful n gettng started wth your calculator. Note:

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

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

Appendix for Solving Asset Pricing Models when the Price-Dividend Function is Analytic

Appendix 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 information

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

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

More information

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

Data Mining Linear and Logistic Regression

Data Mining Linear and Logistic Regression 07/02/207 Data Mnng Lnear and Logstc Regresson Mchael L of 26 Regresson In statstcal modellng, regresson analyss s a statstcal process for estmatng the relatonshps among varables. Regresson models are

More information

Dept of Mathematics and Statistics King Fahd University of Petroleum & Minerals

Dept of Mathematics and Statistics King Fahd University of Petroleum & Minerals Dept of Mathematcs and Statstcs Kng Fahd Unversty of Petroleum & Mnerals AS201: Fnancal Mathematcs Dr. Mohammad H. Omar Major Exam 2 FORM B Soluton November 27 2012 6.30pm-8.00pm Name ID#: Seral #: Instructons.

More information

Fast Laplacian Solvers by Sparsification

Fast 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 information

COS 511: Theoretical Machine Learning. Lecturer: Rob Schapire Lecture #21 Scribe: Lawrence Diao April 23, 2013

COS 511: Theoretical Machine Learning. Lecturer: Rob Schapire Lecture #21 Scribe: Lawrence Diao April 23, 2013 COS 511: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture #21 Scrbe: Lawrence Dao Aprl 23, 2013 1 On-Lne Log Loss To recap the end of the last lecture, we have the followng on-lne problem wth N

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

Solution of Equations

Solution of Equations Solution of Equations Outline Bisection Method Secant Method Regula Falsi Method Newton s Method Nonlinear Equations This module focuses on finding roots on nonlinear equations of the form f()=0. Due to

More information

EDC Introduction

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

More information

CS227-Scientific Computing. Lecture 6: Nonlinear Equations

CS227-Scientific Computing. Lecture 6: Nonlinear Equations CS227-Scientific Computing Lecture 6: Nonlinear Equations A Financial Problem You invest $100 a month in an interest-bearing account. You make 60 deposits, and one month after the last deposit (5 years

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

EGR 102 Introduction to Engineering Modeling. Lab 09B Recap Regression Analysis & Structured Programming

EGR 102 Introduction to Engineering Modeling. Lab 09B Recap Regression Analysis & Structured Programming EGR 102 Introduction to Engineering Modeling Lab 09B Recap Regression Analysis & Structured Programming EGR 102 - Fall 2018 1 Overview Data Manipulation find() built-in function Regression in MATLAB using

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

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

The Direct Control and Penalty Methods for American Put Options

The Direct Control and Penalty Methods for American Put Options The Drect Control and Penalty Methods for Amercan Put Optons by Ama Peprah Asare A thess presented to the Unversty of Waterloo n fulfllment of the thess requrement for the degree of Master of Mathematcs

More information

Calibration Methods: Regression & Correlation. Calibration Methods: Regression & Correlation

Calibration Methods: Regression & Correlation. Calibration Methods: Regression & Correlation Calbraton Methods: Regresson & Correlaton Calbraton A seres of standards run (n replcate fashon) over a gven concentraton range. Standards Comprsed of analte(s) of nterest n a gven matr composton. Matr

More information

Project Management Project Phases the S curve

Project Management Project Phases the S curve Project lfe cycle and resource usage Phases Project Management Project Phases the S curve Eng. Gorgo Locatell RATE OF RESOURCE ES Conceptual Defnton Realzaton Release TIME Cumulated resource usage and

More information

Appendix - Normally Distributed Admissible Choices are Optimal

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

More information

Production and Supply Chain Management Logistics. Paolo Detti Department of Information Engeneering and Mathematical Sciences University of Siena

Production and Supply Chain Management Logistics. Paolo Detti Department of Information Engeneering and Mathematical Sciences University of Siena Producton and Supply Chan Management Logstcs Paolo Dett Department of Informaton Engeneerng and Mathematcal Scences Unversty of Sena Convergence and complexty of the algorthm Convergence of the algorthm

More information

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

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

More information

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

Parallel Prefix addition

Parallel 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 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

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

A DUAL EXTERIOR POINT SIMPLEX TYPE ALGORITHM FOR THE MINIMUM COST NETWORK FLOW PROBLEM

A DUAL EXTERIOR POINT SIMPLEX TYPE ALGORITHM FOR THE MINIMUM COST NETWORK FLOW PROBLEM Yugoslav Journal of Operatons Research Vol 19 (2009), Number 1, 157-170 DOI:10.2298/YUJOR0901157G A DUAL EXTERIOR POINT SIMPLEX TYPE ALGORITHM FOR THE MINIMUM COST NETWORK FLOW PROBLEM George GERANIS Konstantnos

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

QUADRATIC CONVERGENCE FOR VALUING AMERICAN OPTIONS USING A PENALTY METHOD

QUADRATIC CONVERGENCE FOR VALUING AMERICAN OPTIONS USING A PENALTY METHOD QUADRATIC CONVERGENCE FOR VALUING AMERICAN OPTIONS USING A PENALTY METHOD P.A. FORSYTH AND K.R. VETZAL Abstract. The convergence of a penalty method for solvng the dscrete regularzed Amercan opton valuaton

More information

Topics on the Border of Economics and Computation November 6, Lecture 2

Topics 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 information

UNIVERSITY OF VICTORIA Midterm June 6, 2018 Solutions

UNIVERSITY OF VICTORIA Midterm June 6, 2018 Solutions UIVERSITY OF VICTORIA Mdterm June 6, 08 Solutons Econ 45 Summer A0 08 age AME: STUDET UMBER: V00 Course ame & o. Descrptve Statstcs and robablty Economcs 45 Secton(s) A0 CR: 3067 Instructor: Betty Johnson

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

An annuity is a series of payments made at equal intervals. There are many practical examples of financial transactions involving annuities, such as

An 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 information

Appendix Algebra of the ISLM Model

Appendix Algebra of the ISLM Model Chapter 23: Monetary an Fscal Polcy n the ISLM Moel Appenx Algebra o the ISLM Moel The use o algebra to analyze the ISLM moel allows us to exten the multpler analyss n Chapter 22 an to obtan many o the

More information

Computational Finance

Computational Finance Department of Mathematcs at Unversty of Calforna, San Dego Computatonal Fnance Dfferental Equaton Technques [Lectures 8-10] Mchael Holst February 27, 2017 Contents 1 Modelng Fnancal Optons wth the Black-Scholes

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

YORK UNIVERSITY Faculty of Science Department of Mathematics and Statistics MATH A Test #2 November 03, 2014

YORK UNIVERSITY Faculty of Science Department of Mathematics and Statistics MATH A Test #2 November 03, 2014 Famly Name prnt): YORK UNIVERSITY Faculty of Scence Department of Mathematcs and Statstcs MATH 2280.00 A Test #2 November 0, 2014 Solutons Gven Name: Student No: Sgnature: INSTRUCTIONS: 1. Please wrte

More information

S 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

S 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 information

Fall 2017 Social Sciences 7418 University of Wisconsin-Madison Problem Set 3 Answers

Fall 2017 Social Sciences 7418 University of Wisconsin-Madison Problem Set 3 Answers ublc Affars 854 enze D. Chnn Fall 07 Socal Scences 748 Unversty of Wsconsn-adson roblem Set 3 Answers Due n Lecture on Wednesday, November st. " Box n" your answers to the algebrac questons.. Fscal polcy

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

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

Elements of Economic Analysis II Lecture VI: Industry Supply

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

More information

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

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

More information

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

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

More information

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

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

Capability Analysis. Chapter 255. Introduction. Capability Analysis

Capability 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 information

The Hiring Problem. Informationsteknologi. Institutionen för informationsteknologi

The Hiring Problem. Informationsteknologi. Institutionen för informationsteknologi The Hrng Problem An agency gves you a lst of n persons You ntervew them one-by-one After each ntervew, you must mmedately decde f ths canddate should be hred You can change your mnd f a better one comes

More information

Jean-Paul Murara, Västeras, 26-April Mälardalen University, Sweden. Pricing EO under 2-dim. B S PDE by. using the Crank-Nicolson Method

Jean-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

Week 02, Lecture 03 Detailed Listing and Derivation of Accounting Equations

Week 02, Lecture 03 Detailed Listing and Derivation of Accounting Equations Wee 02, Lecture 03 Detaled Lstng and Dervaton of Accountng Equatons In the GTAP Data Base all the equlbrum condtons hold. The pre-smulaton data base also represents the ntal or pre-smulaton equlbrum. The

More information

Optimising a general repair kit problem with a service constraint

Optimising 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 information

Survey of Math: Chapter 22: Consumer Finance Borrowing Page 1

Survey 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 information

Explaining Movements of the Labor Share in the Korean Economy: Factor Substitution, Markups and Bargaining Power

Explaining Movements of the Labor Share in the Korean Economy: Factor Substitution, Markups and Bargaining Power Explanng Movements of the abor Share n the Korean Economy: Factor Substtuton, Markups and Barganng ower Bae-Geun, Km January 2, 26 Appendx A. Dervaton of the dervatve of et us start from eq. (). For notatonal

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

Lecture 33: Rutherford s Formula, and Rocket Motion

Lecture 33: Rutherford s Formula, and Rocket Motion Lecture 33: Rutherrd s Frula, and Rcket Mtn Fr gravty and the electrc rce, S we have: U( r) Nte that we can deterne r n by ndng the dstance at whch the ttal energy equals the eectve ptental Ths ntegral

More information

Dr. A. Sudhakaraiah* V. Rama Latha E.Gnana Deepika

Dr. A. Sudhakaraiah* V. Rama Latha E.Gnana Deepika Internatonal Journal Of Scentfc & Engneerng Research, Volume, Issue 6, June-0 ISSN - Splt Domnatng Set of an Interval Graph Usng an Algorthm. Dr. A. Sudhakaraah* V. Rama Latha E.Gnana Deepka Abstract :

More information

Numerical Convergence Properties of Option Pricing PDEs with Uncertain Volatility

Numerical Convergence Properties of Option Pricing PDEs with Uncertain Volatility Numercal Convergence Propertes of Opton Prcng PDEs wth Uncertan Volatlty D. M. Pooley, P. A. Forsyth, and K. R. Vetzal Unversty of Waterloo Waterloo, Ontaro Canada NL 3G1 October 6, 001 Abstract The prcng

More information

FROM THE ANSWER SERIES

FROM THE ANSWER SERIES FINNCIL MTHS QUESTIONS & NSWERS 1 FROM THE NSWER SERIES publshed by : The nswer 210 Man Road CLREMONT 7708 Cape Town tel: (021) 671 0837 fa: (021) 671 256 e-mal: nfo@theanswerseres.co.za www.theanswerseres.co.za

More information

Static (or Simultaneous- Move) Games of Complete Information

Static (or Simultaneous- Move) Games of Complete Information Statc (or Smultaneous- Move) Games of Complete Informaton Nash Equlbrum Best Response Functon F. Valognes - Game Theory - Chp 3 Outlne of Statc Games of Complete Informaton Introducton to games Normal-form

More information

Maximum Likelihood Estimation of Isotonic Normal Means with Unknown Variances*

Maximum Likelihood Estimation of Isotonic Normal Means with Unknown Variances* Journal of Multvarate Analyss 64, 183195 (1998) Artcle No. MV971717 Maxmum Lelhood Estmaton of Isotonc Normal Means wth Unnown Varances* Nng-Zhong Sh and Hua Jang Northeast Normal Unversty, Changchun,Chna

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

Mathematical Thinking Exam 1 09 October 2017

Mathematical Thinking Exam 1 09 October 2017 Mathematcal Thnkng Exam 1 09 October 2017 Name: Instructons: Be sure to read each problem s drectons. Wrte clearly durng the exam and fully erase or mark out anythng you do not want graded. You may use

More information

PhysicsAndMathsTutor.com

PhysicsAndMathsTutor.com PhscsAndMathsTutor.com phscsandmathstutor.com June 2005 6. A scentst found that the tme taken, M mnutes, to carr out an eperment can be modelled b a normal random varable wth mean 155 mnutes and standard

More information

Finite Volume Schemes for Solving Nonlinear Partial Differential Equations in Financial Mathematics

Finite Volume Schemes for Solving Nonlinear Partial Differential Equations in Financial Mathematics Fnte Volume Schemes for Solvng Nonlnear Partal Dfferental Equatons n Fnancal Mathematcs Pavol Kútk and Karol Mkula Abstract In order to estmate a far value of fnancal dervatves, varous generalzatons of

More information

Alternatives to Shewhart Charts

Alternatives to Shewhart Charts Alternatves to Shewhart Charts CUSUM & EWMA S Wongsa Overvew Revstng Shewhart Control Charts Cumulatve Sum (CUSUM) Control Chart Eponentally Weghted Movng Average (EWMA) Control Chart 2 Revstng Shewhart

More information

Computation of the Compensating Variation within a Random Utility Model Using GAUSS Software

Computation of the Compensating Variation within a Random Utility Model Using GAUSS Software Modern Economy, 211, 2, 383-389 do:1.4236/me.211.2341 Publshed Onlne July 211 (http://www.scrp.org/journal/me) Computaton of the Compensatng Varaton wthn a Random Utlty Model Usng GAUSS Software Abstract

More information

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

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

More information

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

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

More information

Journal of Computational and Applied Mathematics

Journal of Computational and Applied Mathematics Journal of Computatonal and Appled Mathematcs 236 (212) 3111 3122 Contents lsts avalable at ScVerse ScenceDrect Journal of Computatonal and Appled Mathematcs journal homepage: www.elsever.com/locate/cam

More information

PRICING OF AVERAGE STRIKE ASIAN CALL OPTION USING NUMERICAL PDE METHODS. IIT Guwahati Guwahati, , Assam, INDIA

PRICING OF AVERAGE STRIKE ASIAN CALL OPTION USING NUMERICAL PDE METHODS. IIT Guwahati Guwahati, , Assam, INDIA Internatonal Journal of Pure and Appled Mathematcs Volume 76 No. 5 2012, 709-725 ISSN: 1311-8080 (prnted verson) url: http://www.jpam.eu PA jpam.eu PRICING OF AVERAGE STRIKE ASIAN CALL OPTION USING NUMERICAL

More information

901 Notes: 11.doc Department of Economics Clemson University

901 Notes: 11.doc Department of Economics Clemson University 901 Notes: 11.doc Department of Economcs Clemson nversty Consumer's Surplus 1 The dea of consumer's surplus s to attempt to measure n money terms the value of consumpton of a good from the nformaton contaned

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

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

This method uses not only values of a function f(x), but also values of its derivative f'(x). If you don't know the derivative, you can't use it.

This method uses not only values of a function f(x), but also values of its derivative f'(x). If you don't know the derivative, you can't use it. Finding Roots by "Open" Methods The differences between "open" and "closed" methods The differences between "open" and "closed" methods are closed open ----------------- --------------------- uses a bounded

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

A REAL OPTIONS DESIGN FOR PRODUCT OUTSOURCING. Mehmet Aktan

A REAL OPTIONS DESIGN FOR PRODUCT OUTSOURCING. Mehmet Aktan Proceedngs of the 2001 Wnter Smulaton Conference B. A. Peters, J. S. Smth, D. J. Mederos, and M. W. Rohrer, eds. A REAL OPTIONS DESIGN FOR PRODUCT OUTSOURCING Harret Black Nembhard Leyuan Sh Department

More information

Tuition Fee Loan application notes

Tuition Fee Loan application notes Tuton Fee Loan applcaton notes for new part-tme EU students 2017/18 About these notes These notes should be read along wth your Tuton Fee Loan applcaton form. The notes are splt nto three parts: Part 1

More information

NEW APPROACH TO THEORY OF SIGMA-DELTA ANALOG-TO-DIGITAL CONVERTERS. Valeriy I. Didenko, Aleksander V. Ivanov, Aleksey V.

NEW APPROACH TO THEORY OF SIGMA-DELTA ANALOG-TO-DIGITAL CONVERTERS. Valeriy I. Didenko, Aleksander V. Ivanov, Aleksey V. NEW APPROACH TO THEORY OF IGMA-DELTA ANALOG-TO-DIGITAL CONVERTER Valery I. Ddenko, Aleksander V. Ivanov, Aleksey V. Teplovodsky Department o Inormaton and Measurng Technques Moscow Power Engneerng Insttute

More information

Still Simpler Way of Introducing Interior-Point method for Linear Programming

Still Simpler Way of Introducing Interior-Point method for Linear Programming Stll Smpler Way of Introducng Interor-Pont method for Lnear Programmng Sanjeev Saxena Dept. of Computer Scence and Engneerng, Indan Insttute of Technology, Kanpur, INDIA-08 06 October 9, 05 Abstract Lnear

More information

Probability Distributions. Statistics and Quantitative Analysis U4320. Probability Distributions(cont.) Probability

Probability Distributions. Statistics and Quantitative Analysis U4320. Probability Distributions(cont.) Probability Statstcs and Quanttatve Analss U430 Dstrbutons A. Dstrbutons: How do smple probablt tables relate to dstrbutons?. What s the of gettng a head? ( con toss) Prob. Segment 4: Dstrbutons, Unvarate & Bvarate

More information

Microeconomics: BSc Year One Extending Choice Theory

Microeconomics: 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 information