Homework #5 7 th week Math 240 Thursday October 24, 2013
|
|
- Barbra Osborne
- 5 years ago
- Views:
Transcription
1 . Let a, b > be integers and g : = gcd(a, b) its greatest common divisor. Show that if a = g q a and b = g q b then q a and q b are relatively rime. Since gcd(κ a, κ b) = κ gcd(a, b) in articular, for κ = g we have g = gcd(a, b) = gcd(g q a, g q b ) = g gcd(q a, q b ) gcd(q a, q b ) = that is, q a and q b are relatively rime. 2. Show that for any air of non negative integers a and b a b = gcd(a, b) lcm(a, b). Suose first that a and b are relatively rime and let m be any multile of both a and b. Then, for some integers q a and q b, m = a q a = b q b and so, a b q b. Since a and b are relatively rime it follows that a q b, i.e., q b = κ a for some integer κ which imlies that m = a b κ and hence a b m. This means that a b being a multile of a and b, is is a divisor of any its common multiles. Therefore, by the very definition of the least common multile, it follows that a b = lcm(a, b). Finally, if a and b were not relatively rime, writing a = g q a and b = g q b as in exercise, since q a and q b are relatively rime we have for we just have roved q a q b = lcm(q a, q b ) a b = (g q a )(g q b ) a b = g 2 lcm(q a, q b ) a b = g lcm(g q a, g q b ) a b = g lcm(a, b) a b = gcd(a, b) lcm(a, b) since as in exercise, g = gcd(a, b).
2 3. Find gcd(000, 625) (a) using the Euclidean Algorithm and (b) by factorization. (a) Successive divisions give the remainders 000 = = = = This means that the last non zero reminder is 25 and hence gcd(000, 625) = 25. (b) Since the rime factorizations of 000 and 625 are and 000 = = 5 4 we find that gcd(000, 625) = = 5 3 = (a) If is rime, show that the largest ower of dividing n! is or log n j= j = n n n n σ (n) where σ (n) denotes the sum of the base digits of n. (b) 000! has a lot of final zero digits. Use (a) to find how many are there. 2
3 (a) There are # { κ / κ, and κ n } = # { / κ κ n } = multiles of which are n. In the same way, for j =, 2,... there are # { κ / κ, and κ j n } { / = # κ κ n } j = j multiles of j which are n. Therefore, the largest ower of that divides n! is n n n Note that this sum ends u as soon as j > n, i.e., when j > log n. Alternatively, if n = a m m a m m a a 0 is the base exansion of n then, for any j =, 2,..., m, we have n j = a m m j a m m j a j a j a j a j a 0 j, but since 0 a i, a j a j a ( 0 () j j ) j ) ( j = () = j < we see that and hence j = a m m j a m m j a j a j m j= j = a m m a m m 2 a 2 a a m m 2 a m m 3 a 3 a 2. a m a m a m 3
4 = a a 2 ( ) a 3 ( 2 ) a m ( m ) = a () a 2 ( 2 ) a 3 ( 3 ) a m ( m ) ( a a 2 2 a 3 3 a m m) (a a 2 a 3 a m ) = = n σ (n). (b) If s (n) denotes either of the quantities aearing in art (a), the rime decomosition of n! is n! = n rime s(n). Since the number of zeros at the end of n! coincides with the largest ower of 0 = 2 5 dividing n! and s 5 (n) < s 2 (n) we see that the total of such zeros is s 5 (n). In articular, when n = s 5 (000) = = = and 000! ends with 249 zeros. 5. (a) Given two non negative relatively rime integers a an b, show that if x 0, y 0 is a articular solution of the Diohantine equation ax by = m then, any other solution is of the form { x = x0 bκ for some integer κ. y = y 0 aκ (b) Use (a) to describe the solution set for the general linear Diohantine equation ax by = m when a and b are arbitrary non negative integers. (a) If x 0, y 0 satisfies ax 0 by 0 = m and x, y is any other solution of this equation, i.e., ax by = m, by subtracting a(x x 0 ) = b(y y 0 ). This imlies that b a(x x 0 ) and hence b (x x 0 ) because a and b are relatively rime. This means that for some integer κ, x = x 0 bκ. Also, from the above relation it follows that b(y y 0 ) = abκ and so y = y 0 aκ. 4
5 (b) Let x 0, y 0 be a solution of the general equation ax by = m. We know that if g : = gcd(a, b) then, g m so if, as in exercise, we write a = gq a and b = gq b, any solution x, y to the equation will satisfy a a x q b y = m g Z. Since q a and q b are relatively rime (exercise ), from art (a) { x = x0 κq b for some integer κ. y = y 0 κq a 6. Solve } x mod 3 x 2 mod 5 From the first equation x = 3κ and from the second x = 2 5l form some integers κ and l. This means that for x to be a solution of the given system, κ and l must satisfy 3κ = 2 5l 3κ = 5l. Since 3 and 5 are relatively rime and κ 0 = 2, l 0 = is a articular solution to this last equation, we see that its solutions are describe (exercise 5) by { κ = 2 5υ l = 3υ where υ Z is an arbitrary integer. Thus, returning to the exression for x in terms if κ (or l) we find that the general solution to the given system of congruences is x = 7 5υ with υ Z an arbitrary integer. In other words (recall the Chinese reminder theorem), } x mod 3 x 7 mod 5. x 2 mod 5 5
MATH 116: Material Covered in Class and Quiz/Exam Information
MATH 116: Material Covered in Class and Quiz/Exam Information August 23 rd. Syllabus. Divisibility and linear combinations. Example 1: Proof of Theorem 2.4 parts (a), (c), and (g). Example 2: Exercise
More informationOn the smallest abundant number not divisible by the first k primes
On the smallest abundant number not divisible by the first k rimes Douglas E. Iannucci Abstract We say a ositive integer n is abundant if σ(n) > 2n, where σ(n) denotes the sum of the ositive divisors of
More informationWorksheet A ALGEBRA PMT
Worksheet A 1 Find the quotient obtained in dividing a (x 3 + 2x 2 x 2) by (x + 1) b (x 3 + 2x 2 9x + 2) by (x 2) c (20 + x + 3x 2 + x 3 ) by (x + 4) d (2x 3 x 2 4x + 3) by (x 1) e (6x 3 19x 2 73x + 90)
More informationSupplemental Material: Buyer-Optimal Learning and Monopoly Pricing
Sulemental Material: Buyer-Otimal Learning and Monooly Pricing Anne-Katrin Roesler and Balázs Szentes February 3, 207 The goal of this note is to characterize buyer-otimal outcomes with minimal learning
More informationChapter 4 Partial Fractions
Chapter 4 8 Partial Fraction Chapter 4 Partial Fractions 4. Introduction: A fraction is a symbol indicating the division of integers. For example,, are fractions and are called Common 9 Fraction. The dividend
More informationStudy Guide and Review - Chapter 2
Divide using long division. 31. (x 3 + 8x 2 5) (x 2) So, (x 3 + 8x 2 5) (x 2) = x 2 + 10x + 20 +. 33. (2x 5 + 5x 4 5x 3 + x 2 18x + 10) (2x 1) So, (2x 5 + 5x 4 5x 3 + x 2 18x + 10) (2x 1) = x 4 + 3x 3
More informationAlgebra and Number Theory Exercise Set
Algebra and Number Theory Exercise Set Kamil Niedzia lomski 1 Algebra 1.1 Complex Numbers Exercise 1. Find real and imaginary part of complex numbers (1) 1 i 2+i (2) (3 + 7i)( 3 + i) (3) ( 3+i)( 1+i 3)
More informationTWO-PERIODIC TERNARY RECURRENCES AND THEIR BINET-FORMULA 1. INTRODUCTION
TWO-PERIODIC TERNARY RECURRENCES AND THEIR BINET-FORMULA M. ALP, N. IRMAK and L. SZALAY Abstract. The properties of k-periodic binary recurrences have been discussed by several authors. In this paper,
More informationCentral Limit Theorem (cont d) 7/28/2006
Central Limit Theorem (cont d) 7/28/2006 Central Limit Theorem for Binomial Distributions Theorem. For the binomial distribution b(n, p, j) we have lim npq b(n, p, np + x npq ) = φ(x), n where φ(x) is
More informationLECTURE NOTES ON MICROECONOMICS
LECTURE NOTES ON MCROECONOMCS ANALYZNG MARKETS WTH BASC CALCULUS William M. Boal Part : Consumers and demand Chater 5: Demand Section 5.: ndividual demand functions Determinants of choice. As noted in
More informationELEMENTS OF MONTE CARLO SIMULATION
APPENDIX B ELEMENTS OF MONTE CARLO SIMULATION B. GENERAL CONCEPT The basic idea of Monte Carlo simulation is to create a series of experimental samples using a random number sequence. According to the
More informationMidterm Exam: Tuesday 28 March in class Sample exam problems ( Homework 5 ) available tomorrow at the latest
Plan Martingales 1. Basic Definitions 2. Examles 3. Overview of Results Reading: G&S Section 12.1-12.4 Next Time: More Martingales Midterm Exam: Tuesday 28 March in class Samle exam roblems ( Homework
More informationIntegrating rational functions (Sect. 8.4)
Integrating rational functions (Sect. 8.4) Integrating rational functions, p m(x) q n (x). Polynomial division: p m(x) The method of partial fractions. p (x) (x r )(x r 2 ) p (n )(x). (Repeated roots).
More informationPortfolio Choice. := δi j, the basis is orthonormal. Expressed in terms of the natural basis, x = j. x j x j,
Portfolio Choice Let us model portfolio choice formally in Euclidean space. There are n assets, and the portfolio space X = R n. A vector x X is a portfolio. Even though we like to see a vector as coordinate-free,
More informationDividing Polynomials
OpenStax-CNX module: m49348 1 Dividing Polynomials OpenStax OpenStax Precalculus This work is produced by OpenStax-CNX and licensed under the Creative Commons Attribution License 4.0 In this section, you
More informationAlgebra homework 8 Homomorphisms, isomorphisms
MATH-UA.343.005 T.A. Louis Guigo Algebra homework 8 Homomorphisms, isomorphisms For every n 1 we denote by S n the n-th symmetric group. Exercise 1. Consider the following permutations: ( ) ( 1 2 3 4 5
More informationMathematics Notes for Class 12 chapter 1. Relations and Functions
1 P a g e Mathematics Notes for Class 12 chapter 1. Relations and Functions Relation If A and B are two non-empty sets, then a relation R from A to B is a subset of A x B. If R A x B and (a, b) R, then
More informationFall 2017 COT 3100 Final Exam Part A. Last Name:, First Name:
Fall 2017 COT 3100 Final Exam Part A Last Name:, First Name: 1) (8 pts) It takes Bob six days to paint their townhouse, and it takes Carol ten days to paint their townhouse. For the purposes of this problem,
More information6.4 Solving Linear Inequalities by Using Addition and Subtraction
6.4 Solving Linear Inequalities by Using Addition and Subtraction Solving EQUATION vs. INEQUALITY EQUATION INEQUALITY To solve an inequality, we USE THE SAME STRATEGY AS FOR SOLVING AN EQUATION: ISOLATE
More informationMATH 205 HOMEWORK #1 OFFICIAL SOLUTION
MATH 205 HOMEWORK #1 OFFICIAL SOLUTION Problem 2: Show that if there exists a ijective field homomorhism F F the char F = char F. Solutio: Let ϕ be the homomorhism, suose that char F =. Note that ϕ(1 =
More informationOn equation. Boris Bartolomé. January 25 th, Göttingen Universität & Institut de Mathémathiques de Bordeaux
Göttingen Universität & Institut de Mathémathiques de Bordeaux Boris.Bartolome@mathematik.uni-goettingen.de Boris.Bartolome@math.u-bordeaux1.fr January 25 th, 2016 January 25 th, 2016 1 / 19 Overview 1
More informationNotes on the symmetric group
Notes on the symmetric group 1 Computations in the symmetric group Recall that, given a set X, the set S X of all bijections from X to itself (or, more briefly, permutations of X) is group under function
More informationA generalization of Sylvester s and Frobenius problems on numerical semigroups
ACTA ARITHMETICA LXV.4 (1993) A generalization of Sylvester s and Frobenius problems on numerical semigroups by Zdzis law Skupień (Kraków) 1. Introduction. Our aim is to formulate and study a modular change
More informationON THE MEAN VALUE OF THE SCBF FUNCTION
ON THE MEAN VALUE OF THE SCBF FUNCTION Zhang Xiaobeng Deartment of Mathematics, Northwest University Xi an, Shaani, P.R.China Abstract Keywords: The main urose of this aer is using the elementary method
More informationThe Multistep Binomial Model
Lecture 10 The Multistep Binomial Model Reminder: Mid Term Test Friday 9th March - 12pm Examples Sheet 1 4 (not qu 3 or qu 5 on sheet 4) Lectures 1-9 10.1 A Discrete Model for Stock Price Reminder: The
More informationProblem Set 2 - SOLUTIONS
Problem Set - SOLUTONS 1. Consider the following two-player game: L R T 4, 4 1, 1 B, 3, 3 (a) What is the maxmin strategy profile? What is the value of this game? Note, the question could be solved like
More information6-3 Dividing Polynomials
Polynomials can be divided using long division just like you learned with numbers. Divide) 24 6 5 6 24-8 4-0 4 Remainder 24 6 = 5 4 6 Example : Using Long Division to Divide a Polynomial Divide using
More informationMaximum Contiguous Subsequences
Chapter 8 Maximum Contiguous Subsequences In this chapter, we consider a well-know problem and apply the algorithm-design techniques that we have learned thus far to this problem. While applying these
More informationI. The Solow model. Dynamic Macroeconomic Analysis. Universidad Autónoma de Madrid. September 2015
I. The Solow model Dynamic Macroeconomic Analysis Universidad Autónoma de Madrid September 2015 Dynamic Macroeconomic Analysis (UAM) I. The Solow model September 2015 1 / 43 Objectives In this first lecture
More informationUniversity of Toronto Department of Economics ECO 204 Summer 2013 Ajaz Hussain TEST 1 SOLUTIONS GOOD LUCK!
University of Toronto Department of Economics ECO 204 Summer 2013 Ajaz Hussain TEST 1 SOLUTIONS TIME: 1 HOUR AND 50 MINUTES DO NOT HAVE A CELL PHONE ON YOUR DESK OR ON YOUR PERSON. ONLY AID ALLOWED: A
More informationLecture 14: Basic Fixpoint Theorems (cont.)
Lecture 14: Basic Fixpoint Theorems (cont) Predicate Transformers Monotonicity and Continuity Existence of Fixpoints Computing Fixpoints Fixpoint Characterization of CTL Operators 1 2 E M Clarke and E
More informationHomework 10 Solution Section 4.2, 4.3.
MATH 00 Homewor Homewor 0 Solution Section.,.3. Please read your writing again before moving to the next roblem. Do not abbreviate your answer. Write everything in full sentences. Write your answer neatly.
More informationC (1,1) (1,2) (2,1) (2,2)
TWO COIN MORRA This game is layed by two layers, R and C. Each layer hides either one or two silver dollars in his/her hand. Simultaneously, each layer guesses how many coins the other layer is holding.
More informationPORTFOLIO OPTIMIZATION AND EXPECTED SHORTFALL MINIMIZATION FROM HISTORICAL DATA
PORTFOLIO OPTIMIZATION AND EXPECTED SHORTFALL MINIMIZATION FROM HISTORICAL DATA We begin by describing the problem at hand which motivates our results. Suppose that we have n financial instruments at hand,
More informationδ j 1 (S j S j 1 ) (2.3) j=1
Chapter The Binomial Model Let S be some tradable asset with prices and let S k = St k ), k = 0, 1,,....1) H = HS 0, S 1,..., S N 1, S N ).) be some option payoff with start date t 0 and end date or maturity
More information4: SINGLE-PERIOD MARKET MODELS
4: SINGLE-PERIOD MARKET MODELS Marek Rutkowski School of Mathematics and Statistics University of Sydney Semester 2, 2016 M. Rutkowski (USydney) Slides 4: Single-Period Market Models 1 / 87 General Single-Period
More informationRealizability of n-vertex Graphs with Prescribed Vertex Connectivity, Edge Connectivity, Minimum Degree, and Maximum Degree
Realizability of n-vertex Graphs with Prescribed Vertex Connectivity, Edge Connectivity, Minimum Degree, and Maximum Degree Lewis Sears IV Washington and Lee University 1 Introduction The study of graph
More informationON THE U p OPERATOR IN CHARACTERISTIC p
ON THE U OPERATOR IN CHARACTERISTIC BRYDEN CAIS Abstract. For a erfect field κ of characteristic > 0, a ositive ingeger N not divisible by, and an arbitrary subgrou Γ of GL 2(Z/NZ), we rove (with mild
More informationSkills Practice Skills Practice for Lesson 10.1
Skills Practice Skills Practice for Lesson 10.1 Name Date Water Balloons Polynomials and Polynomial Functions Vocabulary Match each key term to its corresponding definition. 1. A polynomial written with
More informationBrownian Motion, the Gaussian Lévy Process
Brownian Motion, the Gaussian Lévy Process Deconstructing Brownian Motion: My construction of Brownian motion is based on an idea of Lévy s; and in order to exlain Lévy s idea, I will begin with the following
More informationarxiv: v1 [math.nt] 17 May 2013
ON THE U OPERATOR IN CHARACTERISTIC BRYDEN CAIS arxiv:1305.4188v1 [math.nt] 17 May 2013 Abstract. For a erfect field κ of characteristic > 0, a ositive ingeger N not divisible by, and an arbitrary subgrou
More informationPricing Kernel. v,x = p,y = p,ax, so p is a stochastic discount factor. One refers to p as the pricing kernel.
Payoff Space The set of possible payoffs is the range R(A). This payoff space is a subspace of the state space and is a Euclidean space in its own right. 1 Pricing Kernel By the law of one price, two portfolios
More informationFundamental Theorems of Asset Pricing. 3.1 Arbitrage and risk neutral probability measures
Lecture 3 Fundamental Theorems of Asset Pricing 3.1 Arbitrage and risk neutral probability measures Several important concepts were illustrated in the example in Lecture 2: arbitrage; risk neutral probability
More informationChapter 2 Supply, Demand, and Markets SOLUTIONS TO EXERCISES
Firms, rices & Markets Timothy Van Zandt August 0 Chapter Supply, Demand, and Markets SOLUTIONS TO EXERCISES Exercise.. Suppose a market for commercial water purification systems has buyers with the following
More informationCOMPUTER SCIENCE 20, SPRING 2014 Homework Problems Recursive Definitions, Structural Induction, States and Invariants
COMPUTER SCIENCE 20, SPRING 2014 Homework Problems Recursive Definitions, Structural Induction, States and Invariants Due Wednesday March 12, 2014. CS 20 students should bring a hard copy to class. CSCI
More informationUnit 8 Notes: Solving Quadratics by Factoring Alg 1
Unit 8 Notes: Solving Quadratics by Factoring Alg 1 Name Period Day Date Assignment (Due the next class meeting) Tuesday Wednesday Thursday Friday Monday Tuesday Wednesday Thursday Friday Monday Tuesday
More informationTutorial 6. Sampling Distribution. ENGG2450A Tutors. 27 February The Chinese University of Hong Kong 1/6
Tutorial 6 Sampling Distribution ENGG2450A Tutors The Chinese University of Hong Kong 27 February 2017 1/6 Random Sample and Sampling Distribution 2/6 Random sample Consider a random variable X with distribution
More information7. Infinite Games. II 1
7. Infinite Games. In this Chapter, we treat infinite two-person, zero-sum games. These are games (X, Y, A), in which at least one of the strategy sets, X and Y, is an infinite set. The famous example
More informationT.I.H.E. IT 233 Statistics and Probability: Sem. 1: 2013 ESTIMATION
In Inferential Statistic, ESTIMATION (i) (ii) is called the True Population Mean and is called the True Population Proportion. You must also remember that are not the only population parameters. There
More informationChapter 14 : Statistical Inference 1. Note : Here the 4-th and 5-th editions of the text have different chapters, but the material is the same.
Chapter 14 : Statistical Inference 1 Chapter 14 : Introduction to Statistical Inference Note : Here the 4-th and 5-th editions of the text have different chapters, but the material is the same. Data x
More information2D penalized spline (continuous-by-continuous interaction)
2D penalized spline (continuous-by-continuous interaction) Two examples (RWC, Section 13.1): Number of scallops caught off Long Island Counts are made at specific coordinates. Incidence of AIDS in Italian
More informationLesson 11. Ma February 8 th, 2017
Lesson 11 Ma 15800 February 8 th, 2017 This lesson focuses on applications of quadratics.the nice thing about quadratic expressions is that it is very easy to find their maximum or minimum values, namely
More informationNUMERICAL MATHEMATICS & COMPUTING, 7 Ed. 4.3 Estimating Derivatives and Richardson Extrapolation
NUMERICAL MATHEMATICS & COMPUTING, 7 Ed. 4.3 Estimating Derivatives and Richardson Extrapolation Ward Cheney/David Kincaid c UT Austin Engage Learning: Thomson-Brooks/Cole www.engage.com www.ma.utexas.edu/cna/nmc7
More informationECLT 5930/SEEM 5740: Engineering Economics Second Term
ECLT 5930/SEEM 5740: Engineering Economics 2015 16 Second Term Master of Science in ECLT & SEEM Instructors: Dr. Anthony Man Cho So Department of Systems Engineering & Engineering Management The Chinese
More informationIntroduction to Greedy Algorithms: Huffman Codes
Introduction to Greedy Algorithms: Huffman Codes Yufei Tao ITEE University of Queensland In computer science, one interesting method to design algorithms is to go greedy, namely, keep doing the thing that
More informationNCERT Solutions for Class 11 Maths Chapter 8: Binomial Theorem
NCERT Solutions for Class 11 Maths Chapter 8: Binomial Theorem Exercise 8.1 : Solutions of Questions on Page Number : 166 Question 1: Expand the expression (1-2x) 5 By using Binomial Theorem, the expression
More informationMultiproduct Pricing Made Simple
Multiproduct Pricing Made Simple Mark Armstrong John Vickers Oxford University September 2016 Armstrong & Vickers () Multiproduct Pricing September 2016 1 / 21 Overview Multiproduct pricing important for:
More informationPartial Fractions. A rational function is a fraction in which both the numerator and denominator are polynomials. For example, f ( x) = 4, g( x) =
Partial Fractions A rational function is a fraction in which both the numerator and denominator are polynomials. For example, f ( x) = 4, g( x) = 3 x 2 x + 5, and h( x) = x + 26 x 2 are rational functions.
More information8.1 Estimation of the Mean and Proportion
8.1 Estimation of the Mean and Proportion Statistical inference enables us to make judgments about a population on the basis of sample information. The mean, standard deviation, and proportions of a population
More information1. Factors: Write the pairs of factors for each of the following numbers:
Attached is a packet containing items necessary for you to have mastered to do well in Algebra I Resource Room. Practicing math skills is especially important over the long summer break, so this summer
More informationa*(variable) 2 + b*(variable) + c
CH. 8. Factoring polynomials of the form: a*(variable) + b*(variable) + c Factor: 6x + 11x + 4 STEP 1: Is there a GCF of all terms? NO STEP : How many terms are there? Is it of degree? YES * Is it in the
More informationOn Toponogov s Theorem
On Toponogov s Theorem Viktor Schroeder 1 Trigonometry of constant curvature spaces Let κ R be given. Let M κ be the twodimensional simply connected standard space of constant curvature κ. Thus M κ is
More information5.1 Gauss Remarkable Theorem
5.1 Gauss Remarkable Theorem Recall that, for a surface M, its Gauss curvature is defined by K = κ 1 κ 2 where κ 1, κ 2 are the principal curvatures of M. The principal curvatures are the eigenvalues of
More informationTrinomial Tree. Set up a trinomial approximation to the geometric Brownian motion ds/s = r dt + σ dw. a
Trinomial Tree Set up a trinomial approximation to the geometric Brownian motion ds/s = r dt + σ dw. a The three stock prices at time t are S, Su, and Sd, where ud = 1. Impose the matching of mean and
More informationVocabulary & Concept Review
Vocabulary & Concept Review MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) The are 0, 1, 2, 3,... A) factor B) digits C) whole numbers D) place
More informationCHAPTER 3. Compound Interest
CHAPTER 3 Compound Interest Recall What can you say to the amount of interest earned in simple interest? Do you know? An interest can also earn an interest? Compound Interest Whenever a simple interest
More informationWriting Exponential Equations Day 2
Writing Exponential Equations Day 2 MGSE9 12.A.CED.1 Create equations and inequalities in one variable and use them to solve problems. Include equations arising from linear, quadratic, simple rational,
More informationMixed Strategies. Samuel Alizon and Daniel Cownden February 4, 2009
Mixed Strategies Samuel Alizon and Daniel Cownden February 4, 009 1 What are Mixed Strategies In the previous sections we have looked at games where players face uncertainty, and concluded that they choose
More informationSlide 1 / 128. Polynomials
Slide 1 / 128 Polynomials Slide 2 / 128 Table of Contents Factors and GCF Factoring out GCF's Factoring Trinomials x 2 + bx + c Factoring Using Special Patterns Factoring Trinomials ax 2 + bx + c Factoring
More informationMA 162: Finite Mathematics - Chapter 1
MA 162: Finite Mathematics - Chapter 1 Fall 2014 Ray Kremer University of Kentucky Linear Equations Linear equations are usually represented in one of three ways: 1 Slope-intercept form: y = mx + b 2 Point-Slope
More informationMath 101, Basic Algebra Author: Debra Griffin
Math 101, Basic Algebra Author: Debra Griffin Name Chapter 5 Factoring 5.1 Greatest Common Factor 2 GCF, factoring GCF, factoring common binomial factor 5.2 Factor by Grouping 5 5.3 Factoring Trinomials
More informationChapter 17 Appendix A
Chapter 17 Appendix A The Interest Parity Condition We can derive all the results in the text with a concept that is widely used in international finance. The interest parity condition shows the relationship
More informationReview Exercise Set 13. Find the slope and the equation of the line in the following graph. If the slope is undefined, then indicate it as such.
Review Exercise Set 13 Exercise 1: Find the slope and the equation of the line in the following graph. If the slope is undefined, then indicate it as such. Exercise 2: Write a linear function that can
More informationOption Pricing. Chapter Discrete Time
Chapter 7 Option Pricing 7.1 Discrete Time In the next section we will discuss the Black Scholes formula. To prepare for that, we will consider the much simpler problem of pricing options when there are
More informationCompulsory Assignment
An Introduction to Mathematical Finance UiO-STK-MAT300 Autumn 2018 Professor: S. Ortiz-Latorre Compulsory Assignment Instructions: You may write your answers either by hand or on a computer for instance
More informationENDOWMENTS OF GOODS. [See Lecture Notes] Copyright 2005 by South-Western, a division of Thomson Learning. All rights reserved.
ENDOWMENTS OF GOODS [See Lecture Notes] Coyright 005 by South-Western a division of Thomson Learning. All rights reserved. Endowments as Income So far assume agent endowed with income m. Where does income
More informationLecture 10: The knapsack problem
Optimization Methods in Finance (EPFL, Fall 2010) Lecture 10: The knapsack problem 24.11.2010 Lecturer: Prof. Friedrich Eisenbrand Scribe: Anu Harjula The knapsack problem The Knapsack problem is a problem
More informationMAT103: Fundamentals of Mathematics I Final Exam Review Packet
MAT103: Fundamentals of Mathematics I Final Exam Review Packet A. Using the information below, write the appropriate numerical value in each region of the Venn diagram provided and answer the questions
More informationOn the Optimality of a Family of Binary Trees Techical Report TR
On the Optimality of a Family of Binary Trees Techical Report TR-011101-1 Dana Vrajitoru and William Knight Indiana University South Bend Department of Computer and Information Sciences Abstract In this
More informationInterior-Point Algorithm for CLP II. yyye
Conic Linear Optimization and Appl. Lecture Note #10 1 Interior-Point Algorithm for CLP II Yinyu Ye Department of Management Science and Engineering Stanford University Stanford, CA 94305, U.S.A. http://www.stanford.edu/
More informationLecture 2: The Simple Story of 2-SAT
0510-7410: Topics in Algorithms - Random Satisfiability March 04, 2014 Lecture 2: The Simple Story of 2-SAT Lecturer: Benny Applebaum Scribe(s): Mor Baruch 1 Lecture Outline In this talk we will show that
More informationEDULABZ INTERNATIONAL NUMBERS AND REAL NUMBERS
5 NUMBERS AND REAL NUMBERS. Find the largest 4-digit number which is exactly divisible by 459. Ans.The largest 4-digit natural number = 9999 We divide 9999 by 459 and find the remainder 459 9999 98 89
More informationBuyer-Optimal Learning and Monopoly Pricing
Buyer-Otimal Learning and Monooly Pricing Anne-Katrin Roesler and Balázs Szentes January 2, 217 Abstract This aer analyzes a bilateral trade model where the buyer s valuation for the object is uncertain
More informationScenario Generation and Sampling Methods
Scenario Generation and Sampling Methods Güzin Bayraksan Tito Homem-de-Mello SVAN 2016 IMPA May 9th, 2016 Bayraksan (OSU) & Homem-de-Mello (UAI) Scenario Generation and Sampling SVAN IMPA May 9 1 / 30
More informationChapter 6 Analyzing Accumulated Change: Integrals in Action
Chapter 6 Analyzing Accumulated Change: Integrals in Action 6. Streams in Business and Biology You will find Excel very helpful when dealing with streams that are accumulated over finite intervals. Finding
More informationApplication of an Interval Backward Finite Difference Method for Solving the One-Dimensional Heat Conduction Problem
Application of an Interval Backward Finite Difference Method for Solving the One-Dimensional Heat Conduction Problem Malgorzata A. Jankowska 1, Andrzej Marciniak 2 and Tomasz Hoffmann 2 1 Poznan University
More informationCurves on a Surface. (Com S 477/577 Notes) Yan-Bin Jia. Oct 24, 2017
Curves on a Surface (Com S 477/577 Notes) Yan-Bin Jia Oct 24, 2017 1 Normal and Geodesic Curvatures One way to examine how much a surface bends is to look at the curvature of curves on the surface. Let
More informationPosterior Inference. , where should we start? Consider the following computational procedure: 1. draw samples. 2. convert. 3. compute properties
Posterior Inference Example. Consider a binomial model where we have a posterior distribution for the probability term, θ. Suppose we want to make inferences about the log-odds γ = log ( θ 1 θ), where
More informationVersion A. Problem 1. Let X be the continuous random variable defined by the following pdf: 1 x/2 when 0 x 2, f(x) = 0 otherwise.
Math 224 Q Exam 3A Fall 217 Tues Dec 12 Version A Problem 1. Let X be the continuous random variable defined by the following pdf: { 1 x/2 when x 2, f(x) otherwise. (a) Compute the mean µ E[X]. E[X] x
More informationMATH3075/3975 FINANCIAL MATHEMATICS TUTORIAL PROBLEMS
MATH307/37 FINANCIAL MATHEMATICS TUTORIAL PROBLEMS School of Mathematics and Statistics Semester, 04 Tutorial problems should be used to test your mathematical skills and understanding of the lecture material.
More informationThe Fundamental Properties of Natural Numbers
FORMALIZED MATHEMATICS Number 1, January 1990 Université Catholique de Louvain The Fundamental Properties of Natural Numbers Grzegorz Bancerek 1 Warsaw University Bia lystok Summary. Some fundamental properties
More informationTHEORETICAL ASPECTS OF THREE-ASSET PORTFOLIO MANAGEMENT
THEORETICAL ASPECTS OF THREE-ASSET PORTFOLIO MANAGEMENT Michal ŠOLTÉS ABSTRACT: The aer deals with three-asset ortfolio It focuses on ordinary investor for whom the Marowitz s theory of selection of otimal
More informationHedging Credit Derivatives in Intensity Based Models
Hedging Credit Derivatives in Intensity Based Models PETER CARR Head of Quantitative Financial Research, Bloomberg LP, New York Director of the Masters Program in Math Finance, Courant Institute, NYU Stanford
More informationHints on Some of the Exercises
Hints on Some of the Exercises of the book R. Seydel: Tools for Computational Finance. Springer, 00/004/006/009/01. Preparatory Remarks: Some of the hints suggest ideas that may simplify solving the exercises
More informationChapter 7 One-Dimensional Search Methods
Chapter 7 One-Dimensional Search Methods An Introduction to Optimization Spring, 2014 1 Wei-Ta Chu Golden Section Search! Determine the minimizer of a function over a closed interval, say. The only assumption
More informationTEACHING NOTE 98-04: EXCHANGE OPTION PRICING
TEACHING NOTE 98-04: EXCHANGE OPTION PRICING Version date: June 3, 017 C:\CLASSES\TEACHING NOTES\TN98-04.WPD The exchange option, first developed by Margrabe (1978), has proven to be an extremely powerful
More informationSome Bounds for the Singular Values of Matrices
Applied Mathematical Sciences, Vol., 007, no. 49, 443-449 Some Bounds for the Singular Values of Matrices Ramazan Turkmen and Haci Civciv Department of Mathematics, Faculty of Art and Science Selcuk University,
More informationLecture 23: April 10
CS271 Randomness & Computation Spring 2018 Instructor: Alistair Sinclair Lecture 23: April 10 Disclaimer: These notes have not been subjected to the usual scrutiny accorded to formal publications. They
More information1 Answers to the Sept 08 macro prelim - Long Questions
Answers to the Sept 08 macro prelim - Long Questions. Suppose that a representative consumer receives an endowment of a non-storable consumption good. The endowment evolves exogenously according to ln
More informationChapter 4: Section 4-2 Annuities
Chapter 4: Section 4-2 Annuities D. S. Malik Creighton University, Omaha, NE D. S. Malik Creighton University, Omaha, NE () Chapter 4: Section 4-2 Annuities 1 / 24 Annuities Suppose that we deposit $1000
More information