Finance Discipline Group

UTS Business School

FINANCIAL METRICS FOR DECISION MAKING â€“ SUMMER 2020

ASSIGNMENT

General Instructions and Information

Â§ This assignment accounts for 40% of studentsâ€™ final grade for 25624 Financial Metrics

for Decision Making.

Â§ The assignment is to be undertaken individually.

Â§ The assignment is due on Friday the 5th of February 2021 (Week 11) by 5pm.

Â§ The assignment must be submitted via UTSOnline. Youâ€™ll need to provide a written

report and an Excel spreadsheet:

â€¢ The written report must be self-contained and formatted as a PDF file.

â€¢ Excel files will also be examined and will constitute 20% of the value of the

assignment. The Excel file should include all calculations.

Â§ The scope of this assignment is limited to [5] pages not including appendices and cover

sheet. Use standard fonts (think Calibri, Times New Roman, Arial) and standard font

sizes. There is no specific word count.

Â§ You are encouraged to use figures and tables when reporting your results.

Â§ The file names, for both the report and the Excel spreadsheet, will take the form:

â€œName â€“ Student numberâ€. For example, if your name is Jane Doe and your student

number is 12345, then your file name will be â€œJane Doe – 12345â€. Please donâ€™t write

the words â€œnameâ€, â€œstudent numberâ€ or anything else in the file name.

Â§ All assignment-related questions should be posted to the Discussion Board on

UTSOnline.

Marking

Â§ This assessment will be graded on the quality of both, the written report and the

quantitative analysis in Excel.

Â§ Marks will be awarded 70% for content and analysis, and 30% for effectiveness of

communication and presentation.

Â§ Late submissions will be allocated a mark of zero with no exceptions unless via special

consideration filing.

Files

In the Assignment folder on UTSOnline, youâ€™ll find the following files:

Â§ Cover Sheet: is the cover sheet youâ€™ll need to fill in, sign, and submit along with your

written report.

Â§ Data: this Excel spreadsheet contains the following worksheets:

â€¢ Cover: youâ€™ll need provide your student details here.

â€¢ Part 1 to Part 4: these worksheets contain the data (when applicable) for each

part and should be used to perform all relevant data analysis required.

Instructions

Part 1 â€“ Hypothesis Testing [10 marks]

The national average annual salary for a campus manager is $89,000 a year. A state official

took a sample of 25 campus managers in the state of New South Wales (NSW) to learn about

salaries in the state and see if they differed from the national average.

The data for this question is provided in the worksheet named â€˜Part 1â€™.

a. [5 marks] Formulate the null and alternative hypotheses that can be used to

determine whether the annual salary mean of a campus manager in NSW differs from

the national mean of $89,000.

b. [5 marks] What is the p-value for your hypothesis test in part (a)? At a 5% significance

level, can your null hypothesis be rejected? What is your conclusion?

Part 2 â€“ Modelling [40 marks]

Background Information

Your boss, a real estate business manager, has approached you for financial advice. She is

interested in either purchasing or leasing a new car for her personal use. Aware of your

financial expertise, she has asked you to develop a Spreadsheet Model that allows her to

decide whether to buy or lease the vehicle.

The retail price of the car she is interested in is $50,000.

Buy Scenario

In the Buy Scenario, your boss would like to purchase the car by making an initial down

payment of $15,000 dollars and finance the difference with a conventional car loan to be

repaid monthly for 3-years at a 5% interest rate. The following table summarises the relevant

information for the Buy Scenario.

Buy Scenario

Car Price $ 50,000.00

Down Payment $ 15,000.00

Interest Rate 5%

Term 3 years

Lease Scenario

In the Lease Scenario, there is no initial down payment. Instead, your boss would like to use

a Finance Lease to rent the car for 3 years. At the end of this 3-year period, she plans to

purchase the car from the lease financier (lessor) by paying a residual value of $25,000. In

this scenario, to rent the car, your boss would have to pay a monthly rent of $850 for 3 years.

The following table summarises the relevant information for the Lease Scenario.

Lease Scenario

Car Price $ 50,000.00

Residual Value $ 25,000.00

Monthly Rent $850

Term 3 years

Note: A Finance Lease is a common way people can use a car without actually buying it. Under

a Finance Lease, the car belongs to the financier (lessor) who rents it out to the borrower

(lessee) in exchange for monthly instalments. At the end of the lease term, the lessee has the

option to claim ownership of the car by paying a residual value.

a. [5 marks] Lay out the decision-making problem, the alternatives, and the overall

criteria you would use to evaluate the different alternatives.

b. [5 marks] Carefully establish all the inputs and assumptions you would include in the

Spreadsheet Model for each scenario. If you include inputs/variables other than the

ones provided (e.g. interest rate on savings), justify your choices based on data from

the Australian market.

c. [10 marks] Based on your answers to a) and b), build a Spreadsheet Model which helps

your boss decide whether to buy or lease the vehicle. Make your spreadsheet selfexplanatory.

d. [5 marks] Perform What-If analysis for at least one of your inputs (e.g. down payment).

That is, show what would happen to your modelâ€™s output at, at least, three different

values of the chosen input. In your spreadsheet, highlight the section you would

present to your boss to help her with her decision-making problem.

e. [5 marks] Of all the inputs included in your model, which one do you think is the most

important in determining whether buying or leasing is the best option for your boss?

Provide an explanation.

f. [5 marks] Describe the modelâ€™s limitations and/or aspects that could be improved.

What other factors havenâ€™t been considered?

g. [5 marks] Are there any cognitive biases you would suggest your boss to be aware of

when finally making her decision?

Part 3 â€“ Simple Linear Regression [20 marks]

The Toyota Hilux is the top selling car in Australia. The price of a previously owned Hilux

depends on many factors, including the number kilometres (kms) travelled. To investigate the

relationship between a carâ€™s kms and its sales price, data was collected on a sample of 20

used Hilux in Sydney.

The data for this question is provided in the worksheet named â€˜Part 3â€™.

a. [2 marks] Create a scatter plot for this data with kms as the independent variable.

What does the scatter plot indicate about the relationship between price and kms?

b. [5 marks] Estimate a simple linear regression model with price as the dependent

variable and kms as the independent variable. What is the estimated regression model

(equation)?

c. [5 marks] Test whether each of the regression parameters (intercept and coefficient)

is equal to zero at a 5% significance level. Interpret the coefficients of the estimated

regression parameters and discuss whether these interpretations are reasonable.

d. [4 marks] Using the model estimated in part (b), calculate the predicted price for each

of the cars in the sample. Based on the difference between the true and predicted

prices, identify the two cars that were the biggest bargains.

e. [4 marks] Suppose that you are considering purchasing a previously owned Hilux that

has been driven 100,000 kms. Use the model estimated in part (b) to predict the price

for this car. Is this the price you would offer the seller?

Part 4 â€“ Multiple Linear Regression [30 marks]

A financial institution has a large dataset of information provided by its customers when

they apply for a credit card. This customer information includes the following variables:

â€¢ Annual household income (in thousands of dollars)

â€¢ Household size (number of people)

â€¢ Number of years of post-high school education

â€¢ Number of hours per week watching television

â€¢ Age

â€¢ Gender

In addition, the financial institution has records of the credit card charges accrued by each

customer over the past year.

The data for this question is provided in the worksheet named â€˜Part 4â€™.

a. [5 marks] Plot histograms to contrast the distribution of annual credit card charges for

1) People with zero years of post-high school education vs. People with at least 1 year

of post-high school education, and 2) Female vs. Male. Describe the overall shape of

each histogram and comment on any observable differences.

b. [10 marks] Estimate a multiple linear regression model in which the dependent

variable is the credit card charges accrued by each customer in the data over the past

year, and the independent variables are all the variables the financial institution

collected when the customer first applied for a credit card (e.g. annual household

income). What is the estimated regression model (equation)?

a. Hint: For Gender, create a dummy variable that takes 1 if the customer is

female and 0 if male.

c. [15 marks] Interpret each of the regression coefficients and comment on both their

economic and statistical significance. For each significant regressor (at a 5%

significance level) provide a potential explanation for its statistical relationship with

the dependent variable.

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