FMSN60 / MASM18, 7,5 credits, A (Second Cycle)

General Information

Elective for: F5, F5-fm, I5-fir, Pi4-fm, R5, Master Mathematical Statistics
Language of instruction: The course will be given in English

Contents

The course deals with model building and estimation in non-linear dynamic stochastic models for financial systems. The models can have continuous or discrete time and the model building concerns determining the model structure as well as estimating possible parameters. Common model classes are, e.g., GARCH models with discrete time or models based on stochastic differential equations in continuous time. The course participants will also meet statistical methods, such as Maximum-likelihood and (generalised) moment methods for parameter estimation, kernel estimation techniques, non-linear filters for filtering and prediction, and particle filter methods.

The course also discusses prediction, optimization, and risk evaluation for systems based on such descriptions.

Examination details

LTH:

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Written report and oral presentation of a larger project and compulsory computer exercises.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Parts
Code: 0117. Name: Project Work.
Credits: 4,5. Grading scale: TH. Assessment: Written and oral project presentation
Code: 0217. Name: Laboratory Part 1.
Credits: 1,5. Grading scale: UG. Assessment: Computer exercise 1 and 2
Code: 0317. Name: Laboratory Part 2.
Credits: 1,5. Grading scale: UG. Assessment: Computer exercise 3 and 4

NF:

Subcourses in MASM18, Mathematical Statistics: Financial Statistics
Applies from H15
0703 Project, 4,5 hp
Grading scale: Fail, Pass, Pass with distinction
0704 Laboratory Work part 1, 1,5 hp
Grading scale: Fail, Pass
0705 Laboratory Work part 2, 1,5 hp
Grading scale: Fail, Pass

Admission

Admission requirements LTH:

FMSF10 Stationary Stochastic Processes or FMSF15 Markov Processes

Assumed prior knowledge: EXTF45 Financial Management and preferrably also one or several of FMSN45 Time series analysis, TEK180/EXTQ35 Financial Valuation and Risk Management, and FMSN25 Valuation of Derivative Assets.

Entry requirements Science faculty:

For admission to the course knowledge equivalent to the course MASC04, Stationary
Stochastic processes, 7.5 credits is required together with English B. The course
MASM17 Time series analysis, 7.5 credits, is recommended, as well as basic
knowledge in financial economy.

Reading list

Henrik Madsen, Erik Lindström and Jan Nygaard Nielsen: Statistics for Finance. Chapman and Hall/CRC , 2015, ISBN: 9781482228991.

Contact and other information

Director of studies: studierektor@matstat.lu.se
The number of participants is not limited.

The course overlaps following course/s: FMS161, MASM18

Official Course Description