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ACSC71-306: Stochastic Processes

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

TypePostgraduate
CodeACSC71-306
EFTSL0.125
FacultyBond Business School
Semesters offered
  • January 2021 [Standard Offering]
  • September 2021 [Standard Offering]
  • January 2022 [Standard Offering]
  • September 2022 [Standard Offering]
Credit10
Study areas
  • Actuarial Science
Subject fees
  • Commencing in May 2021: $5,710

Learning outcomes

1. Explain in detail 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, analyse and compare compound stochastic processes including their applications to insurance, reinsurance and policy excess.
5. Estimate, analyse and compare 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.

Assumed knowledge:

Assumed knowledge is the minimum level of knowledge of a subject area that students are assumed to have acquired through previous study. It is the responsibility of students to ensure they meet the assumed knowledge expectations of the subject. Students who do not possess this prior knowledge are strongly recommended against enrolling and do so at their own risk. No concessions will be made for students’ lack of prior knowledge.

Possess demonstratable knowledge in mathematical statistics and probability theory to the level of a unit such as ACSC71-200 Mathematical Statistics.

Restrictions: ?

Anti-requisites: ?

Subject outlines

Subject dates

Standard Offering
Enrolment opens15/11/2020
Semester start18/01/2021
Subject start18/01/2021
Cancellation 1?01/02/2021
Cancellation 2?08/02/2021
Last enrolment31/01/2021
Withdraw – Financial?13/02/2021
Withdraw – Academic?06/03/2021
Teaching census?12/02/2021