Mathematics I

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This is the homepage of my course Mathematics I for the Master Program in Quantitative Finance.

Last update: 28.9.2009

Contents

[edit] Handouts

There is a preliminary version of handouts ready for download:

[edit] References

The contents of the course are covered by the following references:

SH1: K. Sydsaeter and P. Hammond (2008): Essential Mathematics for Economic Analysis. Prentice Hall, Third Edition. ISBN 978-0-273-71324-1.

SH2: K. Sydsaeter, P. Hammond, A. Seierstad and A. Stroem (2005): Further Mathematics for Economic Analysis. Prentice Hall, First edition. ISBN 0-273-65576-0.

LL: S. Lipschutz and M. L. Lipson (2009): Linear Algebra. Schaum's Outline Series. Mc Graw Hill, Fourth Edition. ISBN 978-0-07-154352-1.

[edit] Prerequisites

The following topics are not taught in the course but are assumed to be known.

[edit] Basic Business Mathematics

The following notions are subject of every basic course in business mathematics. In particular, they are part of the introductory mathematics course at the WU.

  • Introductory Algebra (SH1, chapter 1)
  • Introductory Equations (SH1, chapter 2)
  • Functions of One Variable (SH1, chapter 4)
  • Differentiation (SH1, chapter 6, sections 7.1-7.4, 7.7)
  • Single-Variable Optimization (SH1, chapter 8)
  • Integration (SH1, sections 9.1-9.6)
  • Interest Rates (SH1, sections 10.1-10.5)
  • Functions of Many Variables (SH1, sections 11.1-11.7, 12.1-12.3)
  • Multivariable Optimization (SH1, sections 13.1-13.4)
  • Constrained Optimization (SH1, sections 14.1-14.4)
  • Matrix and Vector Algebra (SH1, chapter 15, sections 16.1 and 16.9)

[edit] Undergraduate Business Mathematics

The following notions are standard content of undergraduate business mathematics. In particular, they can be obtained from elective courses of undergraduate studies at the WU.

  • Introduction to mathematical foundations (SH1, chapter 3)
  • Properties to functions (SH1, chapter 5)
  • Advanced differentiation (SH1, sections 7.6-7.12)
  • Advanced integration (SH1, section 9.7)
  • Trigonometric functions and complex numbers (SH2, Appendix B)
  • Sets, completeness and convergence (SH2, Appendix A)

[edit] Course Outline

The course is devoted to Advanced Mathematics for Business and Finance. All notions from Basic Mathematics and Undergraduate Mathematics are supposed to be well-known and familiar.

  • Part 1: Linear Algebra
    • Class 1: Vector Spaces and linear mappings
    • Class 2: Inner products, orthogonality and diagonalization
    • Class 3: Orthogonal projections and multiple regression
    • Class 4: Convexity and separation
  • Midterm Test
  • Part 2: Analysis
    • Class 5: Multivariable differentiation
    • Class 6: Multiple integration and first order differential equations
    • Class 7: Differential equations
  • Endterm Test


[edit] Course Details

[edit] Vector Spaces and linear mappings

definition of a vector space - linear combinations - spanning sets - subspaces - linear spans, row space, column space - linear dependence and linear independence - basis and dimension - rank of a matrix - coordinates

linear mappings - kernel and image - singular and nonsingular linear mappings, isomorphisms - matrix representation - change of basis

References: LL chapters 4,5,6.

[edit] Inner products, orthogonality and diagonalization

inner product - norm - Cauchy Schwarz inequality - orthogonality - orthogonal sets and bases - orthogonal projection - Gram Schmidt orthogonalization process - orthogonal matrix

quadratic functions - positive definite matrix - diagonalization, eigenvalues and eigenvectors

[edit] Orthogonal projections and multiple regression

minimal distance problem - least squares principle - forcing linear restrictions - uniqueness - orthogonality criterion - normal equations - linear orthogonal projection - generalized inverse

descriptive multiple regression - Cholesky decomposition - inverse matrix representation - residual variance - partial correlations

[edit] Convexity and separation

open and closed sets - continuous functions - maximum theorems

convex sets - separating hyperplane theorem - nullation lemma - Farkas lemma - strong separating hyperplane theorem - no arbitrage theorem - application to finance

Frobenius theorem - application to productive economies

References: SH2 chapter 13

[edit] Multivariable differentation

gradients and directional derivatives - convex and concave functions - Taylor's formula - inverse function theorem - implicit function theorem

partial elasticities - homogeneous functions - Euler's theorem - chain rule - implicit differentiation along a level curve - elasticity of substitution

References: SH1 section 11.8, chapter 12, SH2 chapter 2

[edit] Multiple integration and first order differential equations

multiple integrals - section theorem - Fubini's theorem - transformation theorem

separable equations - first order linear equations

References: SH2 chapter 4, SH1 sections 9.8 and 9.9

[edit] Differential equations

second order linear differential equations

linear systems of equations in the plane

partial differential equations

References: SH2 chapters 5-7 buy essays online

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