Advanced Modelling

Bond University

Course Description

  • Course Name

    Advanced Modelling

  • Host University

    Bond University

  • Location

    Gold Coast, Australia

  • Area of Study

    Finance

  • Language Level

    Taught In English

  • Prerequisites

    Students must have successfully completed ACSC12-200 Mathematical Statistics or equivalent prior to undertaking ACSC13-302

  • Course Level Recommendations

    Upper

    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • Credit Points

    10
  • Recommended U.S. Semester Credits
    3 - 4
  • Recommended U.S. Quarter Units
    4.5 - 6
  • Overview

    Introduction

    This subject covers both stochastic and survival modelling. Stochastic processes are very useful in actuarial science and finance. Stochastic processes are used to model the dynamic behaviour of the random variables over time. They are typically collections of random variables indexed by time, such as the close of day exchange rate, which is a discrete stochastic process. There are also continuous-time stochastic processes that involve continuously observing variables, for example the height of water in the Brisbane river. This subject covers simple discrete Markov chains, continuous-time stochastic processes with a focus on Poisson processes, Brownian motion and other related Gaussian processes. Survival models have proved to be very useful in actuarial science. This subject also discusses the theory, estimation and application of survival models. The life table is introduced, followed by survival models with a focus on the key parametric models. Estimation methods for lifetime distributions are discussed. Statistical models and maximum likelihood estimation of multistate processes are considered along with techniques such as the binomial model of mortality and exposed to risk. Methods for smoothing and testing crude mortality data are also studied.
     
     
    Learning Objectives
    1.Expertise in the basic theory and the long run behaviour of simple discrete-time stochastic processes. An understanding of the properties of important continuous-time stochastic process with particular emphasis on Poisson processes.  An understanding of other Markov pure jump processes, Brownian motion including important applications and other relevant Gaussian processes.
    2. Facility in the theory and application of survival models.  Facility in the application of multi state models including those with single and multiple decrements, competence in deriving transfer probabilities and transition intensities and an ability to derive maximum likelihood estimates in these contexts. Facility in estimating lifetime distributions, age based transition intensities and in testing estimates against the standard and graduated life tables. Define and analyse basic compound interest problems.

Course Disclaimer

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.