Cloudstreet Ltd is an Australian firm which is publicly-listed on the ASX. The company has a long term target capital structure of 60% Ordinary Equity, 10% Preference Shares, and 30% Debt. All of the shareholders of Cloudstreet are Australian residents for tax purposes. To fund a major expansion Cloudstreet Ltd needs to raise a $120 million in capital from debt and equity markets.

Cloudstreet Ltd’s broker advises that they can sell new corporate bonds to investors for $1030 with a coupon of 6% and a face value of $1,000. Issue costs on this new debt is expected to be 1.5% of face value. The bonds will mature in six (6) years. The firm can also issue new $100 preference shares which will pay a dividend of $8 and have issue costs of 5%. The company also plans to issue new Ordinary Shares at an issue cost of 3%. The ordinary shares of Cloudstreet are currently trading at $7.50 per share and will pay a dividend of $0.40 this year. Ordinary dividends in Cloudstreet are predicted to grow at a constant rate of 4% pa.

a.         (i)         Calculate how much debt Cloudstreet will need to issue to maintain their target capital structure.

            (ii).       What will be the appropriate cost of debt for Cloudstreet?

b.         (i)         Calculate how much Preference Share equity Cloudstreet will need to issue to maintain their target capital structure.

            (ii).       What will be the appropriate cost of Preference shares for Cloudstreet?   

c.         (i)         Calculate how much Ordinary Share equity Cloudstreet will need to issue to maintain their target capital structure.

            (ii).       What will be the appropriate cost of Ordinary Equity shares for Cloudstreet?

d.         Calculate the Weighted Average Cost of Capital for Cloudstreet following the new capital raising.   

e.         Cloudstreet Ltd has a current EBIT of $1.5 million per annum. The CFO approaches the Board and advises them that they have devised a strategy which will lower the company’s cost of capital by a full 1%. How will this change the value of the company? Support your answer using theory and calculations.   

Sardano and Sons is a large, publicly held company that is considering leasing a warehouse. One of the company’s divisions specializes in manufacturing steel, and this particular warehouse is the only facility in the area that suits the firm’s operations. The current price of steel is $751 per ton. If the price of steel falls over the next six months, the company will purchase 700 tons of steel and produce 77,000 steel rods. Each steel rod will cost $42 to manufacture and the company plans to sell the rods for $56 each. It will take only a matter of days to produce and sell the steel rods. If the price of steel rises or remains the same, it will not be profitable to undertake the project, and the company will allow the lease to expire without producing any steel rods. Treasury bills that mature in six months yield a continuously compounded interest rate of 4 percent and the standard deviation of the returns on steel is 45 percent. Use the Black-Scholes model to determine the maximum amount that the company should be willing to pay for the lease.

The function print_mean() that you wrote in the previous lesson calculates an average value and prints it on the screen. Change this function so that instead of printing the average it returns the average.In order to calculate the sum, you won't need to form a loop; call the function column_sum() instead.

# columns are [0]title [1]year [2]rating [3]length(min) [4]genre [5]budget($mil) [6]box_office_gross($mil)
oscar_data = [
["The Shape of Water", 2017, 6.914, 123, ['sci-fi', 'drama'], 19.4, 195.243464],
["Moonlight", 2016, 6.151, 110, ['drama'], 1.5, 65.046687],
["Spotlight", 2015, 7.489, 129, ['drama', 'crime', 'history'], 20.0, 88.346473],
["Birdman", 2014, 7.604, 119, ['drama', 'comedy'], 18.0, 103.215094],
["12 Years a Slave", 2013, 7.71, 133, ['drama', 'biography', 'history'], 20.0, 178.371993],
["Argo", 2012, 7.517, 120, ['thriller', 'drama', 'biography'], 44.5, 232.324128],
["The Artist", 2011, 7.942, 96, ['drama', 'melodrama', 'comedy'], 15.0, 133.432856],
["The King\'s Speech", 2010, 7.977, 118, ['drama', 'biography', 'history'], 15.0, 414.211549],
["The Hurt Locker", 2008, 7.298, 126, ['thriller', 'drama', 'war', 'history'], 15.0, 49.230772],
["Slumdog Millionaire", 2008, 7.724, 120, ['drama', 'melodrama'], 15.0, 377.910544],
["No Country for Old Men", 2007, 7.726, 122, ['thriller', 'drama', 'crime'], 25.0, 171.627166],
["The Departed", 2006, 8.456, 151, ['thriller', 'drama', 'crime'], 90.0, 289.847354],
["Crash", 2004, 7.896, 108, ['thriller', 'drama', 'crime'], 6.5, 98.410061],
["Million Dollar Baby", 2004, 8.075, 132, ['drama', 'sport'], 30.0, 216.763646],
["The Lord of the Rings: Return of the King", 2003, 8.617, 201, ['fantasy', 'drama', 'adventure'], 94.0, 1119.110941],
["Chicago", 2002, 7.669, 113, ['musical', 'comedy', 'crime'], 45.0, 306.776732],
['A Beautiful Mind', 2001, 8.557, 135, ['drama', 'biography', 'melodrama'], 58.0, 313.542341],
["Gladiator", 2000, 8.585, 155, ['action', 'drama', 'adventure'], 103.0, 457.640427],
["American Beauty", 1999, 7.965, 122, ['drama'], 15.0, 356.296601],
["Shakespeare in Love", 1998, 7.452, 123, ['drama', 'melodrama', 'comedy', 'history'], 25.0, 289.317794],
["Titanic", 1997, 8.369, 194, ['drama', 'melodrama'], 200.0, 2185.372302],
["The English Patient", 1996, 7.849, 155, ['drama', 'melodrama', 'war'], 27.0, 231.976425],
["Braveheart", 1995, 8.283, 178, ['drama', 'war', 'biography', 'history'], 72.0, 210.409945],
["Forrest Gump", 1994, 8.915, 142, ['drama', 'melodrama'], 55.0, 677.386686],
["Schindler\'s List", 1993, 8.819, 195, ['drama', 'biography', 'history'], 22.0, 321.265768],
["Unforgiven", 1992, 7.858, 131, ['drama', 'western'], 14.4, 159.157447],
["Silence of the Lambs", 1990, 8.335, 114, ['thriller', 'crime', 'mystery', 'drama', 'horror'], 19.0, 272.742922],
["Dances with Wolves", 1990, 8.112, 181, ['drama', 'adventure', 'western'], 22.0, 424.208848],
["Driving Miss Daisy", 1989, 7.645, 99, ['drama'], 7.5, 145.793296],
["Rain Man", 1988, 8.25, 133, ['drama'], 25.0, 354.825435],
]

def column_sum(data, column):
result = 0
for row in data:
result += row[column]
return result

def column_mean(data, column):
# < write code here >
  

mean_score = column_mean(oscar_data, 2)
print('Average rating: {:.2f}'.format(mean_score))

mean_length = column_mean(oscar_data, 3)
print('Average length: {:.2f} min.'.format(mean_length))

mean_budget = column_mean(oscar_data, 5)
print('Average budget: ${:.2f} mil.'.format(mean_budget))

mean_gross = column_mean(oscar_data, 6)
print('Average revenue: ${:.2f} mil.'.format(mean_gross))

# columns are [0]title [1]year [2]rating [3]length(min) [4]genre [5]budget($mil) [6]box_office_gross($mil)
oscar_data = [
["The Shape of Water", 2017, 6.914, 123, ['sci-fi', 'drama'], 19.4, 195.243464],
["Moonlight", 2016, 6.151, 110, ['drama'], 1.5, 65.046687],
["Spotlight", 2015, 7.489, 129, ['drama', 'crime', 'history'], 20.0, 88.346473],
["Birdman", 2014, 7.604, 119, ['drama', 'comedy'], 18.0, 103.215094],
["12 Years a Slave", 2013, 7.71, 133, ['drama', 'biography', 'history'], 20.0, 178.371993],
["Argo", 2012, 7.517, 120, ['thriller', 'drama', 'biography'], 44.5, 232.324128],
["The Artist", 2011, 7.942, 96, ['drama', 'melodrama', 'comedy'], 15.0, 133.432856],
["The King\'s Speech", 2010, 7.977, 118, ['drama', 'biography', 'history'], 15.0, 414.211549],
["The Hurt Locker", 2008, 7.298, 126, ['thriller', 'drama', 'war', 'history'], 15.0, 49.230772],
["Slumdog Millionaire", 2008, 7.724, 120, ['drama', 'melodrama'], 15.0, 377.910544],
["No Country for Old Men", 2007, 7.726, 122, ['thriller', 'drama', 'crime'], 25.0, 171.627166],
["The Departed", 2006, 8.456, 151, ['thriller', 'drama', 'crime'], 90.0, 289.847354],
["Crash", 2004, 7.896, 108, ['thriller', 'drama', 'crime'], 6.5, 98.410061],
["Million Dollar Baby", 2004, 8.075, 132, ['drama', 'sport'], 30.0, 216.763646],
["The Lord of the Rings: Return of the King", 2003, 8.617, 201, ['fantasy', 'drama', 'adventure'], 94.0, 1119.110941],
["Chicago", 2002, 7.669, 113, ['musical', 'comedy', 'crime'], 45.0, 306.776732],
['A Beautiful Mind', 2001, 8.557, 135, ['drama', 'biography', 'melodrama'], 58.0, 313.542341],
["Gladiator", 2000, 8.585, 155, ['action', 'drama', 'adventure'], 103.0, 457.640427],
["American Beauty", 1999, 7.965, 122, ['drama'], 15.0, 356.296601],
["Shakespeare in Love", 1998, 7.452, 123, ['drama', 'melodrama', 'comedy', 'history'], 25.0, 289.317794],
["Titanic", 1997, 8.369, 194, ['drama', 'melodrama'], 200.0, 2185.372302],
["The English Patient", 1996, 7.849, 155, ['drama', 'melodrama', 'war'], 27.0, 231.976425],
["Braveheart", 1995, 8.283, 178, ['drama', 'war', 'biography', 'history'], 72.0, 210.409945],
["Forrest Gump", 1994, 8.915, 142, ['drama', 'melodrama'], 55.0, 677.386686],
["Schindler\'s List", 1993, 8.819, 195, ['drama', 'biography', 'history'], 22.0, 321.265768],
["Unforgiven", 1992, 7.858, 131, ['drama', 'western'], 14.4, 159.157447],
["Silence of the Lambs", 1990, 8.335, 114, ['thriller', 'crime', 'mystery', 'drama', 'horror'], 19.0, 272.742922],
["Dances with Wolves", 1990, 8.112, 181, ['drama', 'adventure', 'western'], 22.0, 424.208848],
["Driving Miss Daisy", 1989, 7.645, 99, ['drama'], 7.5, 145.793296],
["Rain Man", 1988, 8.25, 133, ['drama'], 25.0, 354.825435],
]

def column_sum(data, column):
result = 0
for row in data:
result += row[column]
return result

def column_mean(data, column):
total = column_sum(oscar_data, 6)
mean = total / len(data)
return mean

# < write code here >
  

mean_score = column_mean(oscar_data, 2)
print('Average rating: {:.2f}'.format(mean_score))

mean_length = column_mean(oscar_data, 3)
print('Average length: {:.2f} min.'.format(mean_length))

mean_budget = column_mean(oscar_data, 5)
print('Average budget: ${:.2f} mil.'.format(mean_budget))

mean_gross = column_mean(oscar_data, 6)
print('Average revenue: ${:.2f} mil.'.format(mean_gross))

Which, if any, of the following are exclusive rights enjoyed by authors of visual works of art? Select all applicable answers.

a. right to publicly display

b. right to publicly perform

c. right to reproduce

d. right of attribution

e. right of first sale

f. right to prevent mutilation

A manager must decide how many machines of a certain type to purchase.

Each machine can process 101 customers per day.

One machine will result in a fixed cost of $2,038 per day, while two machines will result in a fixed cost of $3,836 per day.

Variable cost will be $22 per customer and revenue will be $49 per customer.

Determine the break-even point in units for TWO machines.

*Round your answers to 3 decimal places in your calculation if necessary.

Hypothesis Testing and Confidence Intervals

The Reliable Housewares store manager wants to learn more about the purchasing behavior of its

"credit" customers. In fact, he is speculating about four specific cases shown below (a) through (d) and

wants you to help him test their accuracy.

b. The true population proportion of credit customers who live in an urban area exceeds 55%

i. Using the dataset provided in Files perform the hypothesis test for each of the above speculations (a) through (d) in order to see if there is an statistical evidence to support the manager’s belief. In each case,

oUse the

Seven Elements of a Test of Hypothesis, in Section 7.1 of your textbook (on or about Page 361) or the Six Steps of Hypothesis Testing I have identified in the addendum.

oUse α=2%for all your analyses,

oExplain your conclusion in simple terms,

oIndicate which hypothesis is the“claim”,

o Compute the p-value,

o Interpret your results,

ii.Follow your work in (i) with computing a 98% confidence interval for each of the variables

described in (a) though (d). Interpret these intervals.

iii.

Write an executive summary for the Reliable Housewares store manager about your analysis,

distilling down the results in a way that would be understandable to someone who does not

know statistics. Clear explanations and interpretations are critical.

Use engine size to predict the car’s width. Answer the questions.

I) For each additional 3.0 liter in engine size how much the car’s width will change? (11.11 points)

• a. It will increase by 2.42 units.
• b. It will increase by 7.27 units.
• c. It will increase by 68.2 units.
• d. It will increase by 63.3 units.
• e. Not applicable.

II) After performing the regression analysis you are asked to pick one number that would best answer the question: Are these two variables, engine size and car width, related or not? What is this number and why? (11.11 points)

• a. The number is the slope and it clearly indicates the relation: For each additional liter in engine size the car’s width increases.
• b. This number is R-square and since it is not close to 1 we cannot claim that these two variables are related.
• c. The number is the P-value, which in this case is very low indicating a strong probability that the two variables are related.
• d. None of these.

III) Given a car that has engine size of 2.0 liters use regression analysis and all available information in there, in order to predict this car’s width. What is your interval prediction?   (11.11 points)

• a. [66.36, 70.09]
• b. ± 1.8
• c. 68.2
• d. 63.3
• e. Not applicable