Description
The focus of this subject is stochastic processes that are typically used to model the dynamic behaviour of random variables indexed by time. The close-of-day exchange rate is an example of a discrete-time stochastic process. There are also continuous-time stochastic processes that involve continuously observing variables, such as the water level within significant rivers. This subject covers discrete Markov chains, continuous-time stochastic processes and some simple time-series models. It also covers applications to insurance, reinsurance and insurance policy excesses, amongst others.
Subject details
Type | Undergraduate |
Code | ACSC13-306 |
EFTSL | 0.125 |
Faculty | Bond Business School |
Semesters offered |
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Credit | 10 |
Study areas |
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Subject fees |
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Learning outcomes
1. Determine the type of a stochastic process and whether it possesses certain well-known properties.
2. Define, estimate and analyse Markov chains, including their long-run behaviour.
3. Define, estimate and analyse Markov jump processes, both time-homogeneous and time-inhomogeneous.
4. Define, estimate and analyse compound stochastic processes including their applications to insurance, reinsurance and policy excess.
5. Estimate and analyse some basic time-series models, including ARIMA and exponential smoothing models.
6. Use statistical software commonly used by practitioners to model stochastic processes.
Enrolment requirements
Requisites: ? | Pre-requisites: ?Co-requisites: ?There are no co-requisites. |
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Restrictions: ? | Anti-requisites: ? |
Subject outlines
Subject dates
Standard Offering | |
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Enrolment opens | 15/11/2020 |
Semester start | 18/01/2021 |
Subject start | 18/01/2021 |
Cancellation 1? | 01/02/2021 |
Cancellation 2? | 08/02/2021 |
Last enrolment | 31/01/2021 |
Withdraw – Financial? | 13/02/2021 |
Withdraw – Academic? | 06/03/2021 |
Teaching census? | 12/02/2021 |