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Mathematical Methods in Finance

General data

Course ID: 2400-QFU1MMF
Erasmus code / ISCED: 14.3 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0311) Economics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title: Mathematical Methods in Finance
Name in Polish: Mathematical Methods in Finance
Organizational unit: Faculty of Economic Sciences
Course groups: English-language course offering of the Faculty of Economics
Obligatory courses for Quantitative Finance, 1st year
ECTS credit allocation (and other scores): 6.00 Basic information on ECTS credits allocation principles:
  • the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS;
  • the student’s weekly hourly workload is 45 h;
  • 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes;
  • weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS;
  • work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.

view allocation of credits
Language: English
Type of course:

obligatory courses

Short description:

The purpose of this course is to help students develop advanced skills for formulating and analyzing mathematical models in the economics and finance. Rigorous mathematical analysis of theoretical models can lead to a better understanding of economic problems.

Full description:

The course is dedicated to advanced undergraduate students of economics.

1. Non-linear programming:

constrained optimization; equality constrains and the Lagrange problem; the constraint qualification; Lagrange multipliers; Kuhn-Tucker multipliers.

2. Differential equations:

Constant coefficient linear differential equation (ODE) systems, fundamental matrix; qualitative solution: phase portrait diagrams; nonlinear systems; fixed points; linearization of dynamic system in the plane.

3. Difference equations:

review of difference equations; linear difference equations; non-linear difference equations and phase diagram; first order difference equations systems.

4. Optimal control:

maximum principle; transversality conditions; transversality conditions in infinite horizon problem; second variations and sufficient conditions.

5. Dynamic programming:

dynamic programming problems; the principle of optimality; the value function; Bellman equation; Euler equations.

6. Stochastic differential equations and partial differential equations:

probability spaces; random variables and stochastic processes; Brownian motion; construction of the Ito integral; the Ito integral; properties of the Ito integral; 1-dimensional Ito processes; 1-dimensional Ito formula; the martingale representation theorem; stochastic differential equations - examples and some solution methods.

Bibliography:

Mandatory literature:

K. Sydsater, P. Hammond, A. Seierstad, A. Strom, Futher mathematics for economic analysis, Prentice Hall, 2005

Supplementary literature:

1. A. Chiang, Elements of dynamic optimization, McGraw-Hill 1992

2. A. Chiang, Fundamental methods of mathematical economics, McGraw-Hill 1967

3. Z. Brzeźniak, T. Zastawiak, Basic stochastic processes., Springer 2003

Learning outcomes:

A student should be able to:

- solve constrained optimization problems,

- solve simple differential and difference equations,

- analyze nonlinear differential and difference equations and systems of equations,

- solve and analyze optimal control problems,

- calculate Ito integrals,

- use the above techniques in economic modeling and finance.

Assessment methods and assessment criteria:

To complete the course, the student has to complete the assignments, pass the midterm exam and pass the final exam. The passing threshold is 50%.

During the midterm and final exam student will have to solve by hand five problems.

Additionally, there will be home assignments. A student will be asked to solve some problems from economics and finance in each homework.

There will be no oral exams.

The final grade will be determined as follows:

Midterm Exam - 30%, Final Exam - 50%, Assignments - 20%.

Classes in period "Winter semester 2023/24" (past)

Time span: 2023-10-01 - 2024-01-28
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 30 hours more information
Lecture, 30 hours more information
Coordinators: Elżbieta Babula
Group instructors: Elżbieta Babula
Students list: (inaccessible to you)
Examination: Course - Examination
Classes - Grading
Lecture - Examination

Classes in period "Winter semester 2024/25" (future)

Time span: 2024-10-01 - 2025-01-26
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 30 hours more information
Lecture, 30 hours more information
Coordinators: Elżbieta Babula
Group instructors: Elżbieta Babula
Students list: (inaccessible to you)
Examination: Course - Examination
Classes - Grading
Lecture - Examination
Course descriptions are protected by copyright.
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