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FINS3616 International Business Finance
创建日期：2024-06-12 16:34:57
所属分类：金融Finance
标签： FINS3616
International Business Finance

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FINS3616

International Business Finance
Note: These notes are property of the author (Mohamad Mourad). They are for the exclusive use of students enrolled in the iLab component of
FINS3616 International Business Finance for Term 1,2024. Reproduction, distribution and re-use of these notes outside the scope of the course, in
any way, shape or form is strictly prohibited. The author and UNSW bear no responsibility for any loss, injury or claims made by any party, entity or
individual, however defined, if these notes are used in exchange rate forecasts for private or commercial purposes.
All students in the Business School have been
provided with a FACTSET Account.
ASAP.
IMPORTANT NOTE
Note: These notes are property of the author (Mohamad Mourad). They are for the exclusive use of students enrolled in the iLab component of
FINS3616 International Business Finance for Term 1,2024. Reproduction, distribution and re-use of these notes outside the scope of the course, in
any way, shape or form is strictly prohibited. The author and UNSW bear no responsibility for any loss, injury or claims made by any party, entity or
individual, however defined, if these notes are used in exchange rate forecasts for private or commercial purposes.
FINS3616 – iLab Task Overview
You are building a regression model to estimate the future USD/AUD exchange
rate.
You expect changes in future exchange rates depend on:
1. the countries’ real GDP growth rates,
2. the differences in inflation,
3. long-term interest rates between the countries.
Students are expected to complete this exercise and take notes as they
would during a tutorial.
Note: These notes are property of the author (Mohamad Mourad). They are for the exclusive use of students enrolled in the iLab component of
FINS3616 International Business Finance for Term 1,2024. Reproduction, distribution and re-use of these notes outside the scope of the course, in
any way, shape or form is strictly prohibited. The author and UNSW bear no responsibility for any loss, injury or claims made by any party, entity or
individual, however defined, if these notes are used in exchange rate forecasts for private or commercial purposes.
Steps – Downloading Data and Setting up File
1. Obtain quarterly data from 2001Q1 to 2023Q3 on:
- USD/AUD spot exchange rate (FactSet identifier: AUDUSD)
- Economic growth 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 CPI
- Long-term interest rates for both countries
2. Calculate the following:
- The change in exchange rates over (i) 1 quarter, (ii) 1 year, and (iii) 3 years. These should be
forward looking, i.e. the quarterly change for September 2023 is:
- 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, defined as the US rate less the Australian rate, and
then dividing this value by 100.
- The long-term interest rate differential as a decimal, defined as the US rate less the Australian
rate, and then dividing this value by 100.
Note: These notes are property of the author (Mohamad Mourad). They are for the exclusive use of students enrolled in the iLab component of
FINS3616 International Business Finance for Term 1,2024. Reproduction, distribution and re-use of these notes outside the scope of the course, in
any way, shape or form is strictly prohibited. The author and UNSW bear no responsibility for any loss, injury or claims made by any party, entity or
individual, however defined, if these notes are used in exchange rate forecasts for private or commercial purposes.
Steps – Estimating the Model and Forecasting
3. Estimate separate regression models for each change in exchange rate as
functions of:
- both countries economic growth rates,
- the long-term interest rate differential, and
- the inflation rate differential.
4. Using your regression models, forecast the future change in exchange rates
using the most recently available quarterly economic data.
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