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日期：2023-04-12 10:14

Mohamad MOURAD – Term 1, 2023 UNSW Sydney

FINS5516 – International Corporate Finance

Term 1, 2023, UNSW Sydney

Data Exercise Assignment

DUE: Sunday 16 April 2023, 11:59pm (Sydney, Australia time)

Weighting

This assessment is worth 15% of your final grade for FINS5516 – International Corporate

Finance. Next to each question is the allocation of marks. There are a total of 30 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. 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 1, 2023 UNSW Sydney

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FINS5516 – Data Exercise Assignment

The LIC will randomly assign each student one of five countries in the list below:

1. Denmark (DKK)

2. Italy (EUR)

3. Mexico (MXN)

4. New Zealand (NZD)

5. South Korea (KRW)

Once assigned a country, the student will analyse the exchange rate ?/ 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, for example, if a

student is assigned Denmark, then they are required to complete the data exercise

assignment on the DKK/USD exchange rate.

Download the Excel file uploaded on Moodle to see which country you have been allocated.

Section 0 – General Overview of the Data Exercise Assignment.

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:

1. the countries’ real GDP growth rates

2. the inflation rate differential

3. long-term interest rate differential

Section 1 – Downloading the Data and Setting up the Excel File.

1.1 – Using FactSet, obtain quarterly data from 2001Q1 to 2022Q3 on:

- The exchange rate ?/ 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.

1.2 – 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, /, for March 2021 is:

- Economic growth rates for both countries as a decimal. This is done by dividing the

FactSet value by 100.

Mohamad MOURAD – Term 1, 2023 UNSW Sydney

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- The inflation rate differential as a decimal (ensure that you divide the FactSet value

by 100), which for simplicity, we define as the rate of the term currency country less

the rate of the base currency country.

- 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 rate of the term currency

country less the rate of the base currency country.

Section 2 – Regression Modelling

2.1 – Consider the following econometric structural model of the change in the exchange rate:

is the percentage change in the exchange rate over period .

Δ is the annual percentage growth rate in real GDP over period .

is the inflation rate differential for period .

is the interest rate differential for period .

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)

2.2 – 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)

2.3 – Consider both the p-value associated with the F-statistic (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)

2.4 – 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)

2.5 – 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 3 – Forecasting

3.1 – Using the latest values of the key macroeconomic variables forecast the estimated

change in the exchange rate:

(1)

Mohamad MOURAD – Term 1, 2023 UNSW Sydney

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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 mark)

3.2 – 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) Mohamad MOURAD – Term 1, 2023 UNSW Sydney

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Additional Information

Note 1: Grammar, Spelling, Punctuation and Style.

1. Five marks out of the 30 marks will be allocated to grammar, spelling, 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 greater than 15% 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: Data Exercise Assignment Submissions and Responses.

1. Students will only be permitted to submit their data exercise 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 data exercise 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.

5. If a student submits their data exercise assignment via the incorrect Turnitin

submission link, then 1 mark 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 1 mark being deducted. If your

submission is not submitted in PDF format, 1 mark 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, 7 days) after the specified due date will result in

a grade of 0.

The LIC 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.