ST213 Half Unit
Introduction to Pricing, Hedging and Optimization
This information is for the 2020/21 session.
Teacher responsible
Prof Konstantinos Kardaras COL 6.07
Availability
This course is compulsory on the BSc in Financial Mathematics and Statistics. This course is available as an outside option to students on other programmes where regulations permit. This course is available with permission to General Course students.
Pre-requisites
MA203 Real Analysis. Must be taken with ST202 Probability, Distribution Theory and Inference.
Course content
This course introduces the concepts of valuation, hedging and portfolio selection in a discrete-time environment. Towards the end, it introduces continuous-time markets in a heuristic fashion. It covers the following topics:
• The binomial model; pricing and replication.
• Trinomial model and incompleteness, arbitrage-free price intervals.
• General discrete-time models and the fundamental theorems.
• Portfolio optimization and hedging.
• Martingale theory in discrete time.
• Multi-period models and backwards induction methods.
• Passage to continuous time Black & Scholes model.
Teaching
This course will be delivered through a combination of classes and lectures totalling a minimum of 30 hours across Lent Term. This year, some or all of this teaching may be delivered through a combination of virtual classes and flipped-lectures delivered as short online videos. This course includes a reading week in Week 6 of Lent Term.
Formative coursework
Students will be expected to produce 9 problem sets in the LT.
Certain problem sets will be returned with feedback.
Indicative reading
Lecture notes will be provided.
Assessment
Exam (80%, duration: 2 hours, reading time: 15 minutes) in the summer exam period.
Coursework (20%).
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Key facts
Department: Statistics
Total students 2019/20: 37
Average class size 2019/20: 37
Capped 2019/20: No
Value: Half Unit
Personal development skills
- Self-management
- Problem solving
- Communication
- Application of numeracy skills
- Specialist skills
