Enterprise Risk Management 2 - WEEK 1
Tim Higgins

S2, 2015

Tim Higgins

Enterprise Risk Management 2 - WEEK 1

Learning Objectives
Upon successful completion of the requirements for this course, students will be able to:
1 Describe the properties and limitations of common risk measures. 2 Describe how models can be used in the ERM decision-making process.
3 Demonstrate an understanding of different quantitative techniques for modelling and measuring risk including:
Risk aggregation methods
Statistical distributions
Copulas
Time series techniques
Extreme value theory
4

5

Recommend appropriate models for risk assessment based on quantitative and qualitative analysis.
Assess different types of risk within an organisation including: market risk, credit risk, operational and other risks.
Tim Higgins

Enterprise Risk Management 2 - WEEK 1

Course Schedule
Week
1
2
3
4
5
6
7
8
9
10
11
12
13

Syllabus
Introduction
to the Course
Risk Measurement
Risk Modelling - Part 1
A review of statistical distributions
Financial time series - Part 1
Financial time series - Part 2
Copulas - Part 1
Copulas - Part 2
Model fitting techniques
Extreme value theory
Risk
Modelling
Part
2
Analysing Market Risk - Part 1
Analysing Market Risk - Part 2
Analysing Credit Risk - Part 1
Analysing Credit Risk - Part 2
Analysing Operational Risk and Other
Risks
Revision
Tim Higgins

Reading
ActEd Ch.10
ActEd
ActEd
ActEd
ActEd

Ch.11
Ch.12
Ch.13
Ch.13 and 14

ActEd
ActEd
ActEd
ActEd

Ch.14
Ch.15
Ch.16
Ch.17

ActEd Ch.18 and 19
ActEd Ch.19
ActEd Ch.20 and 21

Enterprise Risk Management 2 - WEEK 1

Course Assessment

Assessment piece
Mid-Semester Exam
Assignment
Final Exam

Value
20%
20%
60%

Due date
Week 8
Week 12
TBA

All assessment is compulsory and non-redeemable.

Tim Higgins

Enterprise Risk Management 2 - WEEK 1

Risk Measurement

Tim Higgins

Enterprise Risk Management 2 - WEEK 1

Week 1: Objectives and readings
Describe the properties and limitations of common risk measures, including Value at Risk (VaR)
Tail Value at Risk (TVaR)
Probability of ruin
Expected shortfal
Describe how to choose a suitable time horizon and risk discount rate Readings:
ActEd ST9: Chapter 10
Sweeting: Ch1, section 1.6
Sweeting: Ch13, section 13.6
Sweeting: Ch15, section 15.4
Tim Higgins

Enterprise Risk Management 2 - WEEK 1

Properties of Risk Measures

A risk measure is an operation that assigns a value to a risk
Coherence:
Monotonicity

If L1 ≤ L2 then F (L1 ) ≤ F (L2 )

Sub-additivity

F (L1 + L2 ) ≤ F (L1 ) + F (L2 )

Positive homogeneity

F (kL) = kF (L)

Translation invariance

F (L + k) = F (L) + k

Convexity:

F (λLx + (1 − λ)Ly ) ≤ λF (Lx ) + (1 − λ)F (Ly )

Tim Higgins

Enterprise Risk Management 2 - WEEK 1

Deterministic approaches

Notional approach (e.g., risk weightings)
Factor sensitivity approach
Scenario sensitivity approach

Tim Higgins

Enterprise Risk Management 2 - WEEK 1

Deterministic approaches: Notional approach example
Apply multiples to assets or liabilities to allow for uncertainty in their values.
Example:
APRA General Insurance solvency and capital adequacy standards
Insurance risk charge
Net insurance liabilities calculated to be sufficient with 75% probability. What about the other 25%?
Risk charge applied to outstanding claim and premium liability estimates Risk charge is a percentage that depends on class of liability
(based on uncertainty)
Link to GPS 115
Tim Higgins

Enterprise Risk Management 2 - WEEK 1

Deterministic approaches: Factor sensitivity approach
Calculate impact on assets and liabilities of a change to a single underlying risk factor.
Example:
APRA General Insurance solvency and capital adequacy standards
Asset risk charge
Old solvency standards (prior to 2013) used a notional approach (investment capital factors). Problems: overly simplistic; doesn’t address asset/liability mismatch
New solvency standards use a factor sensitivity approach
Link to GPS 114
Factor approach can be criticised because risk factors are only