TPPE61 · 6 credits · Advanced level (A1F) · Matematik, Tillämpad matematik, Industriell ekonomi
Financial Optimization
Active · next start HT 2026
100%
passed the latest regular sitting
MUN1 · 16 Jan 2026 · 49 students
99%
passed the regular sittings, all sittings over the last 5 years
MUN1 · 181 students
4%
Harder than 4% of courses at advanced level
Compared with 285 courses at the same level, ordinary exams over the last three academic years. 90 students.
Part of 6 programmes
- Master of Science in Industrial Engineering and Management - International
- Master of Science in Industrial Engineering and Management
- Master of Science in Engineering Mathematics
- Master of Science in Applied Physics and Electrical Engineering - International
- Master of Science in Applied Physics and Electrical Engineering
- Master's Programme in Mathematics
Other module
MUN1 Oral test
- 5
- 4
- 3
- U
Main rounds
99% passed · 181 students
- 100%49
- 98%41
- 100%40
- 100%51
Later rounds
No sittings with at least 5 students.
- Get 4 or 5: 26% (181 students)
Show small sittings (2)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
Other modules
Partial exams, hand-ins and labs. They are not part of the figures at the top.
Hand-in or lab
PRA2 Project
- G
- U
Main rounds
99% passed · 181 students
- 100%49
- 98%41
- 100%40
- 100%51
Later rounds
No sittings with at least 5 students.
Show small sittings (2)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%1
- 100%1
Hand-in or lab
PRA1 Project
- 5
- 4
- 3
- U
Main rounds
94% passed · 32 students
- 94%32
Later rounds
No sittings with at least 5 students.
- Get 4 or 5: 22% (32 students)
Show small sittings (1)
Sittings with fewer than 5 students, often credit transfers or special sittings. They are not part of any figure on this page.
- 100%2
About the course
Aim
After finishing the course, the student should understand and apply financial optimization models within stochastic programming, maximum likelihood estimation and inverse problems.
Content
Stochastic optimization. Mean-Variance model, Conditional Value at Risk and Hedging. Maximal smoothness of interest rate curves.
- Examiner
- Jörgen Blomvall
- Scheduled hours
- 22 h
- Main field of study
- Matematik, Tillämpad matematik, Industriell ekonomi