GRA 6561 Advanced Computational Methods
GRA 6561 Advanced Computational Methods
This course covers advanced computational methods and their applications in finance and economics. These methods can be used for derivative pricing, asset pricing, macroeconomic simulation, and other pertinent applications in the industry, finance/economics academia, and central banks.
After taking the course, students should know:
- General numerical methods in economics and finance, such as nonlinear equation solving, optimization, approximation, finite difference, projection, and dynamic programming.
- Specialized numerical methods in derivatives pricing, such as lattice/tree methods, Monte Carlo methods, and PDE methods.
After taking the course, students should be able to:
- Apply advanced computational methods in finance and economics.
- Do programming in Matlab or similar programming languages.
- Understanding of quantitative models and ability to implement quantitative methods.
- General numerical methods
- Lattice/Tree method
- Monte Carlo method
- PDE approach in option pricing
- Dynamic programming
- Ethics and sustainability in quantitative finance
The course will be organized as a mixture of lectures, presenting the theory and methods, in-class examples and hands-on implementations of the various methods and tools.
Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class.
This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course starts.
At resit, all exam components must, as a main rule, be retaken during next scheduled course.
Honour Code
Academic honesty and trust are important to all of us as individuals, and represent values that are encouraged and promoted by the honour code system. This is a most significant university tradition. Students are responsible for familiarizing themselves with the ideals of the honour code system, to which the faculty are also deeply committed.
Any violation of the honour code will be dealt with in accordance with BI’s procedures for cheating. These issues are a serious matter to everyone associated with the programs at BI and are at the heart of the honour code and academic integrity. If you have any questions about your responsibilities under the honour code, please ask.
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
| Assessments |
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Exam category: Submission Form of assessment: Written submission Weight: 30 Grouping: Group (2 - 3) Duration: 1 Week(s) Comment: One week-long assignment Exam code: GRA65611 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
Exam category: Submission Form of assessment: Written submission Weight: 70 Grouping: Individual Duration: 6 Hour(s) Comment: take-home exam Exam code: GRA65611 Grading scale: Point scale leading to ECTS letter grade Resit: All components must, as a main rule, be retaken during next scheduled course |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.