ETC5351 - Modelling in finance and insurance - 2019

Mathematical definition of options and other financial derivatives; probability models; mathematical models of random processes; applications; numerical methods; Monte Carlo methods.

The learning goals associated with this unit are to:

1. develop an understanding of the modern approach to evaluation of uncertain future payoffs
2. develop an understanding of the concepts of arbitrage and fair games and their relevance to finance and insurance
3. develop an understanding of the concepts of conditional expectation and martingales and their relation to pricing of financial derivatives
4. develop an understanding of the random processes such as Random Walk, Brownian Motion and Diffusions and be able to apply them for modelling real life processes and risk models
5. obtain skills to use Ito's formula
6. develop the skills to price options by using the Binomial and Black-Scholes models
7. ability to simulate the price process and obtain prices by simulation
8. ability to formulate discrete time Risk Model in Insurance and use it for control of probabilities of ruin.

Within semester assessment: 40% + Examination: 60%

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.

See also Unit timetable information