Continuous Time Finance 2: (FinKont2)

Course content

See "Knowledge" below. Note that the "selected topics" part (weeks 4-9) varies from year to year.

Education

MSc Programme in Mathematics-Economics

MSc Programme in Actuarial Mathematics

Learning outcome

Knowledge:

  • Dynamic hedging, model risk and "the fundamental theorem of derivative trading"
  • Dividends and foreign exchange models
  • Arbitrage-free term structure models; the Heath-Jarrow-Morton formalism;  1-dim. affine models; Vasicek and Cox-Ingersoll-Ross; LIBOR market models
  • Pricing of interest rate derivatives (caps, swaptions)
  • Selected topics such as advanced models for option pricing (stochastic volatility, jumps) or multi-dimensional affine term structure models.

 

Skills:

  • Design, conduct and analyze simulation-based hedge experiments
  • Derive no-arbitrage conditions models with dividends, multiple currencies, stochastic interest rates, or a non-traded underlying asset.  
  • Use change-of-numeraire techniques to price  interest rate options

These are the skills acquired in first, part of the course (3 weeks). The second part the course (whose topics will vary slightly from year to year depending on lecturer and student interests)  will hone these skills further as well as teach some other ones (e.g. how an how not to read an academic paper).

 

Competencies:

  1. Confidence in using continuous-time finance models to analyze problems and models that go (well) beyond the basic “call-option in Black/Scholes”-case. The confidence is obtained by working through (fairly) specific specific examples (see also 2. below) rather than “abstract nonsense”.
  2. Producing “sensible numbers” from the continuous-time models; the numbers may arise from implementation of specific numerical algorithms, from well-designed experiments, or from empirical analysis.
  3. Ability to read original research papers in finance journals, both broad academic journals such as Journal of Finance, technical journals such as Mathematical Finance, or applied quantitative journals such as Journal of Derivatives.

6 hours of lectures and 2 hours of tutorials per week for 9 weeks

Continuous-time Finance (FinKont) and Mathematical Finance.

Academic qualifications equivalent to a BSc degree is recommended.

Written
Individual
Continuous feedback during the course of the semester
Feedback by final exam (In addition to the grade)
ECTS
7,5 ECTS
Type of assessment
Continuous assessment
Type of assessment details
The evaluation is based on 3 mandatory hand-in exercises, which all have equal weight.
Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
One internal examiner
Re-exam

20 minute oral exam with several internal examiners. No preparation time and no aids.

Criteria for exam assessment

The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 54
  • Preparation
  • 134
  • Theory exercises
  • 18
  • English
  • 206

Kursusinformation

Language
English
Course number
NMAK15010U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Duration

1 block

Placement
Block 3
Schedulegroup
A
Capacity
No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Studyboard
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Rolf Poulsen   (4-7774716b457266796d33707a336970)
rolf@math.ku.dk, office 04.4.11
Saved on the 14-02-2024

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