exams in business, law, and mathematics, students often face considerable challenges in preparing for and performing well in these exams. The challenges differ by discipline,
reflecting the unique demands significantly in format. Common types of business exams and Writing Skills: Business exams
Advanced Financial
Accounting
An IFRS® Standards Approach, 4e
Pearl Tan, Chu Yeong Lim and Ee Wen Kuah
Solutions Manual
Chapter 1
Risk Reporting
Copyright © 2019 by McGraw-Hill Education (Asia)
, Advanced Financial Accounting (Tan, Lim & Kuah)
Chapter 1 solutions
CHAPTER 1
CONCEPT QUESTIONS
Concept Question 1.1
This is an open-ended question and is specific to the financial institution selected by
the student.
Concept Question 1.2
1. Historical simulation is more appropriate than the delta-normal method under
the following conditions:
(i) Future market conditions are an extension of the past as historical
simulation is based on historical data.
(ii) The distribution of returns is non-normal.
(iii) The distribution has fat tails. The existence of fat tails pose a
problem for parameter-based models since VAR is focused on the
left tail of the distribution. A fat would mean that the normal
distribution underestimate the proportion of outliers and in turn the
true value at risk.
(iv) When the portfolio includes nonlinear instruments such as options
and mortgages. Options have asymmetric returns and these are not
captured by the delta-normal method. On the other hand, historical
simulation allows for nonlinearities.
exams in business, law, and mathematics, students often face considerable challenges in preparing for and performing well in these exams. The challenges differ by discipline, reflecting the unique
demands area, these exams can vary significantly in format. Common types of business exams and Writing Skills: Business exams
2. Based on a 99% confidence level and assuming 250 daily observations, the firm
would expect to incur losses greater than the VAR estimate for 2.5 days.
3. The firm might carry out stress testing using a worst-case scenario analysis
approach. The approach involves the following steps:
(i) Choose an appropriate short-term period to measure the worst case,
for example, a week.
(ii) Simulate a large number of times (thousands) various possible
behaviour of the portfolio in the selected period.
(iii) For each simulation create a distribution of worst outcomes by
incorporating the worst value return for each simulation into a new
distribution.
(iv) After running all the simulations a distribution of worst case
scenarios is created. The mean value of this distribution may be used
as the worst case scenario.
, Concept Question 1.3
Some of the insights are obtained from the article “Value at Risk” by T J Linsmeier and
N D Pearson (Financial Analysts Journal, Mar/Apr 2000, 56,2). However, other
readings relating to VaR will also be relevant.
1. Advantages of VaR as discussed in the article
o The advantage of VaR is that it is a single quantitative and succinct
measure of market risk for a portfolio. It summarizes the impact of
complex risks in a single measure. It is a concise measure of risk.
o It is a statistical measure and the risk of measurement error can be
quantified, unlike descriptive data or opinion-based measures.
o VaR is used to aggregate different risks in the same portfolio. It is a
comprehensive measure of market risks.
o The concept of VaR is not complex and can be understood by different
audiences including senior management, regulators and investors.
Limitations of VaR:
o It is a measure of loss arising from “normal” market movements. It does not
capture extreme market conditions (e.g. events that fall within 5 to 10
standard deviations from mean conditions – a recent example is the credit
crisis of 2007). exams in business, law, and mathematics, students often face considerable challenges in preparing for and performing
well in these exams. The challenges differ by discipline, reflecting the unique demands exams are often a mix of theoretical knowledge and practical
application. Depending on the subject area, these exams can vary significantly in format. Common types of business exams and Writing Skills:
Business exams
o The historical simulation is restricted by historical trends in market prices
and does not capture new and abnormal situations well.
o Assumed distributions (e.g. the delta-normal and Monte Carlo simulation)
may not reflect real distributions of market factors.
o The reliability of the VaR measure depends on the sample size (the larger
the data set, the better the results), the horizon period (a short holding period,
e.g. daily to generate a large sample size), assumptions concerning standard
deviations and/or correlations.
o Additional tests, such as stress testing are needed to determine losses outside
of the normal range.
o Source of risks are not evident from the summary measure. Loss of
information results from the highly compressed measure.
2. This question tests the understanding of the information required by the three
methodologies. The three methodologies are historical simulation, Delta-
Normal and Monte Carlo Simulation.
reflecting the unique demands significantly in format. Common types of business exams and Writing Skills: Business exams
Advanced Financial
Accounting
An IFRS® Standards Approach, 4e
Pearl Tan, Chu Yeong Lim and Ee Wen Kuah
Solutions Manual
Chapter 1
Risk Reporting
Copyright © 2019 by McGraw-Hill Education (Asia)
, Advanced Financial Accounting (Tan, Lim & Kuah)
Chapter 1 solutions
CHAPTER 1
CONCEPT QUESTIONS
Concept Question 1.1
This is an open-ended question and is specific to the financial institution selected by
the student.
Concept Question 1.2
1. Historical simulation is more appropriate than the delta-normal method under
the following conditions:
(i) Future market conditions are an extension of the past as historical
simulation is based on historical data.
(ii) The distribution of returns is non-normal.
(iii) The distribution has fat tails. The existence of fat tails pose a
problem for parameter-based models since VAR is focused on the
left tail of the distribution. A fat would mean that the normal
distribution underestimate the proportion of outliers and in turn the
true value at risk.
(iv) When the portfolio includes nonlinear instruments such as options
and mortgages. Options have asymmetric returns and these are not
captured by the delta-normal method. On the other hand, historical
simulation allows for nonlinearities.
exams in business, law, and mathematics, students often face considerable challenges in preparing for and performing well in these exams. The challenges differ by discipline, reflecting the unique
demands area, these exams can vary significantly in format. Common types of business exams and Writing Skills: Business exams
2. Based on a 99% confidence level and assuming 250 daily observations, the firm
would expect to incur losses greater than the VAR estimate for 2.5 days.
3. The firm might carry out stress testing using a worst-case scenario analysis
approach. The approach involves the following steps:
(i) Choose an appropriate short-term period to measure the worst case,
for example, a week.
(ii) Simulate a large number of times (thousands) various possible
behaviour of the portfolio in the selected period.
(iii) For each simulation create a distribution of worst outcomes by
incorporating the worst value return for each simulation into a new
distribution.
(iv) After running all the simulations a distribution of worst case
scenarios is created. The mean value of this distribution may be used
as the worst case scenario.
, Concept Question 1.3
Some of the insights are obtained from the article “Value at Risk” by T J Linsmeier and
N D Pearson (Financial Analysts Journal, Mar/Apr 2000, 56,2). However, other
readings relating to VaR will also be relevant.
1. Advantages of VaR as discussed in the article
o The advantage of VaR is that it is a single quantitative and succinct
measure of market risk for a portfolio. It summarizes the impact of
complex risks in a single measure. It is a concise measure of risk.
o It is a statistical measure and the risk of measurement error can be
quantified, unlike descriptive data or opinion-based measures.
o VaR is used to aggregate different risks in the same portfolio. It is a
comprehensive measure of market risks.
o The concept of VaR is not complex and can be understood by different
audiences including senior management, regulators and investors.
Limitations of VaR:
o It is a measure of loss arising from “normal” market movements. It does not
capture extreme market conditions (e.g. events that fall within 5 to 10
standard deviations from mean conditions – a recent example is the credit
crisis of 2007). exams in business, law, and mathematics, students often face considerable challenges in preparing for and performing
well in these exams. The challenges differ by discipline, reflecting the unique demands exams are often a mix of theoretical knowledge and practical
application. Depending on the subject area, these exams can vary significantly in format. Common types of business exams and Writing Skills:
Business exams
o The historical simulation is restricted by historical trends in market prices
and does not capture new and abnormal situations well.
o Assumed distributions (e.g. the delta-normal and Monte Carlo simulation)
may not reflect real distributions of market factors.
o The reliability of the VaR measure depends on the sample size (the larger
the data set, the better the results), the horizon period (a short holding period,
e.g. daily to generate a large sample size), assumptions concerning standard
deviations and/or correlations.
o Additional tests, such as stress testing are needed to determine losses outside
of the normal range.
o Source of risks are not evident from the summary measure. Loss of
information results from the highly compressed measure.
2. This question tests the understanding of the information required by the three
methodologies. The three methodologies are historical simulation, Delta-
Normal and Monte Carlo Simulation.
