Financial Optimization, 6 credits

Finansiell optimering, 6 hp

TPPE61

Main field of study

Mathematics Applied Mathematics Industrial Engineering and Management

Course level

Second cycle

Course type

Programme course

Examiner

Jörgen Blomvall

Director of studies or equivalent

Fredrik Persson

Education components

Preliminary scheduled hours: 22 h
Recommended self-study hours: 138 h
ECV = Elective / Compulsory / Voluntary
Course offered for Semester Period Timetable module Language Campus ECV
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Applied Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Applied Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Applied Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Applied Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Applied Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Financial Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla C
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Financial Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla C
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Financial Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla C
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Financial Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla C
6CYYI Applied Physics and Electrical Engineering - International, M Sc in Engineering (Financial Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla C
6CYYY Applied Physics and Electrical Engineering, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYY Applied Physics and Electrical Engineering, M Sc in Engineering (Applied Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CYYY Applied Physics and Electrical Engineering, M Sc in Engineering (Financial Mathematics) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla C
6CIEI Industrial Engineering and Management - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering (Master Profile Finance) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering (Master Profile Finance) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering (Master Profile Finance) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering (Master Profile Finance) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIEI Industrial Engineering and Management - International, M Sc in Engineering (Master Profile Finance) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIII Industrial Engineering and Management, M Sc in Engineering 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6CIII Industrial Engineering and Management, M Sc in Engineering (Master Profile Finance) 9 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6MMAT Mathematics, Master's programme 3 (Autumn 2017) 2 2 Swedish Linköping, Valla E
6MMAT Mathematics, Master's programme (Modelling and Optimization in Economics) 3 (Autumn 2017) 2 2 Swedish Linköping, Valla E

Main field of study

Mathematics, Applied Mathematics, Industrial Engineering and Management

Course level

Second cycle

Advancement level

A1X

Course offered for

  • Industrial Engineering and Management - International, M Sc in Engineering
  • Industrial Engineering and Management, M Sc in Engineering
  • Applied Physics and Electrical Engineering, M Sc in Engineering
  • Mathematics, Master's programme
  • Applied Physics and Electrical Engineering - International, M Sc in Engineering

Entry requirements

Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.

Prerequisites

Introduction to Operations Researchand Mathematical Statistics, first course (or corresponding courses on other programs). The courses Financial Markets and Instruments, Financial Valuation Methodology , and Portfolio Management are desirable, but not necessary.

Intended learning outcomes

To gain insight of how financial decision problems can be solved with an optimization methodology. To give experience of how financial decision problems can be solved with optimization methods. After the course, the student shall:

  • explain stochastic programming models
  • be able to plan, design and implement financial optimization models (Asset Liability Management models) and evaluate these
  • explain Mean-Variance model
  • explain Value at Risk, Conditional Value at Risk and Hedging from an optimization perspective

Course content

Stochastic optimization. Mean-Variance model, Conditional Value at Risk and Hedging. Maximal smoothness of interest rate curves.

Teaching and working methods

The course consists of one or two projects, which are solved in a group. The course is not in the timetable. Lectures and guidance support the projects. The contents of the lectures are governed by the project's need. At the seminars the projects are presented and discussed.

Examination

PRA1Project6 creditsU, 3, 4, 5
Individually written report.

Grades

Four-grade scale, LiU, U, 3, 4, 5

Department

Institutionen för ekonomisk och industriell utveckling

Director of Studies or equivalent

Fredrik Persson

Examiner

Jörgen Blomvall

Course website and other links

http://www.iei.liu.se/prodek/blomvall/

Education components

Preliminary scheduled hours: 22 h
Recommended self-study hours: 138 h

Course literature

Kompletterande material.
Code Name Scope Grading scale
PRA1 Project 6 credits U, 3, 4, 5
Individually written report.

Regulations (apply to LiU in its entirety)

The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.

LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva. 

Kompletterande material.

Note: The course matrix might contain more information in Swedish.

I = Introduce, U = Teach, A = Utilize
I U A Modules Comment
1. DISCIPLINARY KNOWLEDGE AND REASONING
1.1 Knowledge of underlying mathematics and science (G1X level)
X
PRA1

                            
1.2 Fundamental engineering knowledge (G1X level)
X

                            
1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level)
X
X
PRA1

                            
1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level)

                            
1.5 Insight into current research and development work

                            
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES
2.1 Analytical reasoning and problem solving
X
X
X
PRA1

                            
2.2 Experimentation, investigation, and knowledge discovery

                            
2.3 System thinking
X
X
X
PRA1

                            
2.4 Attitudes, thought, and learning
X
PRA1

                            
2.5 Ethics, equity, and other responsibilities

                            
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION
3.1 Teamwork
X

                            
3.2 Communications
X
PRA1

                            
3.3 Communication in foreign languages

                            
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT
4.1 External, societal, and environmental context

                            
4.2 Enterprise and business context

                            
4.3 Conceiving, system engineering and management
X
X
PRA1

                            
4.4 Designing
X
X
PRA1

                            
4.5 Implementing
X
X
PRA1

                            
4.6 Operating

                            
5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS
5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development

                            
5.2 Economic conditions for knowledge development

                            
5.3 Identification of needs, structuring and planning of research or development projects
X
PRA1

                            
5.4 Execution of research or development projects
X
PRA1

                            
5.5 Presentation and evaluation of research or development projects
X
PRA1

                            

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