Study-Unit Description

Study-Unit Description


CODE INS5031

 
TITLE Practical Stochastic Asset Liability Modelling

 
UM LEVEL 05 - Postgraduate Modular Diploma or Degree Course

 
MQF LEVEL 7

 
ECTS CREDITS 5

 
DEPARTMENT Insurance and Risk Management

 
DESCRIPTION The study-unit will start with a review of the main relevant univariate and multivariate statistical distributions. This will include their main characteristics, and how to fit data to them. We will also review the main measures of location, spread, skew and kurtosis, and their importance in financial modeling. Different measures of association (correlation) will then be covered, including the criteria for assessing them. This will lead to the discussion of copulas, including the rationale for their use, their characteristics, and how to fit them.

The next stage of the study-unit will be a description of key types of models, including return-driven models (such as the multivariate normal model) and econometric or cascade models. We will then move to look in more detail at time series models such as ARIMA and GARCH models, before looking at some specific interest rate models.

Next, we will look at the liability side of modeling, and how to deal with mortality and longevity risks. This will include models of longevity trend risk, but also level and binomial risk.

We will then look at measures of risk such as volatility, value at risk and conditional value at risk, before moving on to optimisation and efficient frontiers, and how to compare different investment strategies. This will take into account utility and prospect theory.

Whilst teaching the theoretical aspects described above, practical implications using Excel and R will also be demonstrated.

Study-Unit Aims:

The aim of this study-unit is to equip students with the skills they need to build an asset liability model from first principles, and thus to provide them with the expertise needed to work in the financial modeling teams of banks, insurance companies and asset managers.

Learning Outcomes:

1. Knowledge & Understanding:
By the end of the study-unit the student will be able to:

i) Describe the characteristics and uses of selected univariate and multivariate statistical distributions, and copulas;
ii) Describe and calculate measures of location, spread, skew, kurtosis and association;
iii) Calculate the parameters for selected distributions and copulas;
iv) Describe the structure of selected asset models and longevity models;
v) Produce stochastic simulations with particular statistical characteristics;
vi) Calculate selected risk measures based on stochastic simulations.

2. Skills:
By the end of the study-unit the student will be able to:

i) Design models to be used to describe asset prices and liability cash flows;
ii) Determine the parameters for such models given an appropriate data set;
iii) Calculate a series of simulated results from the model;
iv) Compare the portfolios arising from the model;
v) Propose appropriate selection criteria for portfolio choice;
vi) Select the most appropriate portfolio or portfolios given the proposed criteria.

Main Text/s and any supplementary readings:

Main Texts:

- Sweeting, P.J. (2017) Financial Enterprise Risk Management, 2nd Edition (Cambridge University Press).

 
STUDY-UNIT TYPE Lecture

 
METHOD OF ASSESSMENT
Assessment Component/s Assessment Due Sept. Asst Session Weighting
Assignment SEM2 Yes 50%
Examination SEM2 Yes 50%

 
LECTURER/S

 

 
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years.

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