Mohamad MOURAD – Term 3, 2024 UNSW Sydney
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FINS3616 – International Business Finance
Term 3, 2024, UNSW Sydney
iLab Assignment
DUE: Friday 15 November 2024, 5pm (Sydney, Australia time)
Weighting
This assessment is worth 20% of your final grade for FINS3616 – International Business
Finance. Next to each question is the allocation of marks. There are a total of 50 marks for
this assignment.
Assignment Learning Objectives
The purpose behind this assignment is to get students to:
1. apply and assess the relevance of the International Parity Conditions and Purchasing
Power Parity (PPP) Theory in a practical setting,
2. think outside the textbook and homework questions framework,
3. conduct their own research,
4. using actual data and statistical methods (regression and regression analysis),
5. explore and visualize macroeconomic data and improve their familiarity with statistical
tools in Microsoft Excel.
This assignment is designed to give students an insight into how economists and analysts in
industry approach the topic of exchange rate modelling.
This assignment is individual work and must be submitted as individual work only.
IT IS RECOMMENDED THAT STUDENTS WORK ON THIS ASSIGNMENT FREQUENTLY.
CRAMMING AT THE LAST MOMENT IS A BAD STRATEGY.
Mohamad MOURAD – Term 3, 2024 UNSW Sydney
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FINS3616 – iLab Assignment
The LIC will randomly assign each student one of five countries in the list below:
1. South Africa (ZAR)
2. South Korea (KRW)
3. Switzerland (CHF)
4. Thailand (THB)
5. United Kingdom (GBP)
Once assigned a country, the student will analyse the exchange rate 푒
ℎ/푓
comprising that
country’s currency in relation to that of the United States (USD). The USD is the base
currency irrespective of which currency you have been allocated. Thus, if you are
assigned South Africa, then you need to complete the iLab assignment on the ZAR/USD
exchange rate. The ZAR/USD exchange rate is interpreted as the number of ZAR per USD.
Download the Excel file uploaded on Moodle to see which country you have been allocated.
Section 1 – Qualitative Analysis.
You are constructing a regression model to forecast an estimate of the exchange rate. You
expect changes in future exchange rates depend on a set of key macroeconomic variables:
− the countries’ real GDP growth rates
− the inflation rate differential
− long-term interest rate differential
Answer the following questions below. The limit for each question is 150 words.
1.1 – What are the exchange rate systems in both countries? Are there any differences
between the two countries’ foreign exchange systems over the sample period? (1 mark)
1.2 – Comment on the reputation of each country’s central bank and its degree of
independence. (2 marks)
1.3 – Using the most recently available data, what are the sovereign credit ratings for the two
countries you have been assigned? What might be driving these differences? What issues
could this create from a MNC’s perspective? (3 marks)
1.4 – What is your assessment of the degree of political risk within both countries? Are there
any recent examples of political risk? What are possible methods for hedging against such
risk? (3 marks)
Section 2 – Downloading the Data and Setting up the Excel File.
2.1 – Using FACTSET, obtain quarterly data from 2001Q1 to 2024Q2 on:
- The exchange rate 푒
ℎ/푓
you have been randomly assigned.
- Economic growth rates for both countries, defined as the year-on-year % change in
real GDP.
- Inflation rates for both countries, defined as the year-on-year % change in the CPI.
- Long-term interest rates for both countries.
Mohamad MOURAD – Term 3, 2024 UNSW Sydney
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2.2 – Using the data you collected from FACTSET, calculate the following:
- The change in exchange rates over (i) 1 quarter, (ii) 1 year, and (iii) 3 years. These
must be forward looking. Calculating a forward-looking change in the exchange rate
is best illustrated by an example. Thus, for example, the one-quarter change in the
exchange rate, 푒
ℎ/푓
, for December 2022 is:
푒
ℎ/푓,푡=푀푎푟푐ℎ 2023
푒
ℎ/푓,푡=퐷푒푐 2022
−1
- Economic growth rates for both countries as a decimal. This is done by dividing the
FACTSET value by 100.
- The inflation rate differential as a decimal (ensure that you divide the FACTSET
value by 100), which for simplicity, we define as the term currency rate (ℎ) less the
base currency rate (푓).
- The long-term interest rate differential as a decimal (ensure that you divide the
FACTSET value by 100), which for simplicity, we define as the term currency rate
(ℎ) less the base currency rate (푓).
Section 3 – Data Exploration and Visualisation
Using the data you collected from FACTSET, answer the following questions (limit for each
question is 100 words):
3.1 – What is the average exchange rate over your sample period? (1 mark)
3.2 – What is the average year-on-year percent change in real GDP for each country
assigned over the entire sample period? (1 mark)
3.3 – What is the average inflation rate for each country assigned over the entire sample
period? (1 mark)
3.4 – What is the average long-term interest rate for each country assigned over the entire
sample period? (1 mark)
Analysts use charts and graphs they normally paste from a spreadsheet into a presentation
to analyse and communicate insights in their everyday work. Data can be better understood
and more compelling for colleagues and clients by presenting them in a visual context in a
simple and logical manner.
3.5 – Plot the quarterly exchange rate over your sample period in a line chart. Do not use the
default graph from FACTSET. You need to use the functions in Excel to complete this
section and ensure it is labelled and easy to comprehend. (1 mark)
Identify a period of significant increase or decrease in the exchange rate. What factors might
have contributed to such changes? (2 marks)
Mohamad MOURAD – Term 3, 2024 UNSW Sydney
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3.6 – Compare the differences in GDP growth rates over the sample period for both
countries in a chart of your choice and provide comments on any large differences over the
period. (2 marks)
3.7 – Plot the inflation rate and long-term interest rate for the term currency country over the
sample in a chart. Repeat this for the base currency country. What does each graph show
regarding the relation between these two rates? Is it consistent with the Fisher Effect? (3
marks)
Section 4 – Regression Modelling
4.1 – Consider the following econometric structural model of the change in the exchange rate:
Δ푒
ℎ/푓,푡
=훽
0
+훽
1
Δ퐺퐷푃
ℎ,푡
+훽
2
Δ퐺퐷푃
푓,푡
+훽
3
퐼푛푓푅퐷
푡
+훽
4
퐼푛푡푅퐷
푡
+휖
푡
where
Δ푒
ℎ/푓,푡
is the percentage change in the exchange rate over period 푡.
Δ퐺퐷푃
푡
is the annual percentage growth rate in real GDP over period 푡.
퐼푛푓푅퐷
푡
is the inflation rate differential for period 푡.
퐼푛푡푅퐷
푡
is the interest rate differential for period 푡.
휖
푡
is the error term for period 푡.
Using linear regression, obtain the coefficient estimates for each of the 3-time horizons. You
need to report for each time-horizon, ALL coefficient estimates, p-values, Adjusted R-squares,
F-statistics (and p-value) in one table, so the grader is able to see your results in your written
submission (rather than the Excel file). (4 marks)
4.2 – Analyse the statistical significance of the coefficient estimates at the 5% level. You are
to provide a summary/high-level analysis of the key results. Word limit: 150 words. (3 marks)
4.3 – Consider both the p-value from the F-test (at the 5% level of significance) and the
adjusted R-squared as the forecast horizon increases from 1 quarter to 3 years. Provide some
commentary and discuss whether such results (across the 3 models) are consistent with PPP
theory. Word limit: 150 words. (4 marks)
4.4 – Which macroeconomic variables from the model you have estimated are considered
economically important for modelling changes in the exchange rate? Are you surprised by
these results? Are they consistent with PPP theory? Word limit: 150 words. (5 marks)
4.5 – One potential issue the analyst faces when using multiple linear regression analysis is
the multicollinearity of the independent variables. Verify whether or not multicollinearity exists
among the independent variables. This is done by examining the correlation between each of
the independent variables. Think of this as a correlation matrix (must be included in your
document) which can be easily performed in Excel using the “Data Analysis” tool pack. If the
independent variables are highly correlated, then the analyst is unable to isolate the effect of
each independent variable on the dependent variable. Thus, analysis essentially becomes
pointless. Word limit: 100 words. (3 marks)
Section 5 – Forecasting
(1)
Mohamad MOURAD – Term 3, 2024 UNSW Sydney
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5.1 – Using the latest values of the key macroeconomic variables forecast the estimated
change in the exchange rate:
a) 1-quarter ahead,
b) 1-year ahead
c) 3-years’ ahead
Report the magnitude of the forecasts for each regression model in no more than two
sentences. Provide brief commentary (no more than one sentence) as to whether the currency
you have been assigned is forecast to depreciate or appreciate against the USD over each
forecast horizon. (3 marks)
5.2 – Do you think that the structural model (Equation 1) is a useful model for modelling
changes in the exchange rate? What are some of its limitations? Irrespective of your answer,
what other independent variable would you include in Equation 1? Provide at least one
economic reason for that variable’s inclusion. You should also provide commentary indicating
what relationship this variable has with the change in the exchange rate (that is, the dependent
variable). Word limit: 150 words. (3 marks)
Additional Information
Note 1: Grammar, Spelling, Punctuation and Style.
1. Four marks out of the 50 marks will be allocated to grammar, spelling, and overall
professionality of the responses and ensuring that all data and calculations in the Excel
file are expressed to 3 decimal places. You need to ensure that your work is polished
and contains NO errors. Remember you are presenting your work. When you are
working professionally, the market expects high quality output.
2. If you use sources in your answers, ensure that you formally cite them. The style of
referencing is for you to decide.
3. Plagiarism is not tolerated. Your answers must be written by you and only you. Turnitin
has a similarity indicator that reports a percentage similarity score. Submissions with
similarity scores should not be high if they are written in your own words.
Turnitin includes the cover sheet and your references list in its calculation of its similarity score.
However, the grader will be able to filter this out and see the percentage similarity score based
only on the student’s written responses.
Note 2: iLab Assignment Submissions and Responses.
1. Students will only be permitted to submit their iLab assignment ONCE in Turnitin.
There are NO multiple submission options permitted. What is submitted first will be
graded.
2. There is NO grace period for any submissions.
3. Lengthy responses to questions will result in only the first 150 words of each part (or
whatever the word limit is for that section) being graded.
4. If a student submits their iLab assignment on an exchange rate other than the
exchange rate they were assigned, then they have not followed instructions. The
maximum grade a student will then obtain is 60% for this assessment.
Mohamad MOURAD – Term 3, 2024 UNSW Sydney
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5. If a student submits their iLab assignment via the incorrect Turnitin submission link,
then 2 marks will be deducted.
6. You must type your answers and submit as a PDF document via Turnitin. Ensure that
the cover sheet is attached with your submission. See Moodle for cover sheet. A
submission without the cover sheet will result in 2 marks being deducted. If your
submission is not submitted in PDF format, 2 marks will be deducted.
7. Submit your Excel file with the calculations. Failure to submit the Excel file will result
in a deduction of 5 marks.
8. The School of Banking and Finance’s policy stipulates late submissions will attract a
5% penalty per day following the assignment due date (weekend days included). A
submission made one week (that is, 5 days) after the specified due date will result in
a grade of 0.
9. AI Policy for iLab Assignment: The iLab assignment is designed for students to put in
the time and effort to learn about the country they’ve been assigned, and also the use
of regression to interpret results. As such, the use of AI in any way shape or form is
not permitted for this assignment. Teaching staff will inspect all iLab Assignment
submissions and those deemed as having used AI will result in the student being
reported to the UNSW Integrity Committee.
The LIC or iLab Instructor reserves the right to add to this list in light of changing conditions.
Any changes made will be communicated with students as an announcement via the Moodle
webpage.
