CAC 510 FINANCIAL ACCOUNTING
Assignment 7 Questions
Case: The 10 Beach Hut by Dana Gillett and Julie Harvey, Richard Ivey School of Business
1. What was Mandy Arlington’s business?
2. What was Mandy Arlington’s brand name?
3. Explain what “sole proprietorship” is.
4. Would you say the idea of sole proprietorship was in line with the vision of the protagonist? Advise Mandy on this issue.
5. Losses were incurred in the first few years. a. Comment about this.
b. After how many years was a profit made?
c. How do you explain the fact that the business made losses for all the years you have indicated and yet was able to survive?
6. In exhibit 2, there is an item “drawings”. Explain its meaning in regard to (1) sole proprietorship and (2) Company
7. Using Exhibit 3;
(a) Explain what is meant by “prepaids.”
(b) Compute the working capital of the business for 2003 and 2004. Explain what your figures mean.
THE 10 BEACH HUT
Upon graduation, a young business school student, Mandy Arlington, decided to follow her dream of becoming a clothing designer. After much thought, she decided to design her own line of beachwear to be sold in beach towns across the province of Ontario in Canada. Arlington would design the clothing and have it produced by a local manufacturer. After researching suppliers, manufacturers, vendors and office locations, Arlington’s clothing line, The 10 Beach Hut, was launched as a sole proprietorship in January of 2001, in time for the upcoming spring season. Operations started slowly and losses were incurred in the first few years; however, by 2004, sales resulted in a profit as demand grew for the 10 beach Hut wear. Selected financial statements for 2003 and 2004 are shown in Exhibits 1, 2 and 3.
Exhibit 1
STATEMENT OF EARNINGS
For the year ending December 31, 2004
Net Sales $ 296,475
Cost of goods sold 221,109
Gross profit 75,366
Operating expenses
Selling and administration $ 48,384
Amortization 6,106
Interest 14,115
68,605
Net income $ 6,761
Additional note regarding 2004 operations:
The owner made an additional $5,580 capital in October 2004 (see Exhibit 2).
Exhibit 2
STATEMENT OF CAPITAL
For the year ending December 31, 2004
Beginning Capital (2003) $ 45,627
Net income 6,761
Capital investment 5,580
57,968
Less: drawings 3,283
Ending capital (2004) $ 54,685
Exhibit 3
BALANCE SHEETS
For the years ending December 31, 2003 and 2004
ASSETS 2004 2003
Current assets:
Cash $ 3,939 $ 1,970
Accounts receivable 73,856 60,726
Inventory 65,322 58,100
Prepaids 1,313 1,641
Total current assets $144,430 $122,437
Fixed assets¹:
Land 16,084 16,084
Building & fixtures $ 79,764 $ 72,543
Less: accum.amortization 20,548 59,216 14,442 58,101
Total net fixed assets 75,300 74,185
Total assets $ 219,730 $ 196,622
LIABILITIES & OWNER’S EQUITY
Current liabilities:
Bank indebtedness $ 32,760 $ 23,962
Accounts payable 40,375 31,840
Total current liabilities 73,135 55,802
Long-term debt 91,910 95,193
Total Liabilities 91,910 95,193
Owner’s equity:
Owner, capital 54,685 45,627
Total liabilities and owner’s equity $ 219,730 $ 196,622
¹ Several fixed assets worth $7,221 were purchased throughout the year, however, no fixed assets were sold during the year.
In: Accounting
The Terminator
Trans Ocean Shipping (“Trans Ocean”) provides domestic and international transportation and logistics services to customers. The company contracts shipping vessels, trucks, and aircraft to provide regional, long-haul, and international shipments of customer goods. Trans Ocean has entered into the following contracts:
In March 2019, Trans Ocean entered into a revenue contract with a customer, Asia Manufacturing (“Asia”), in which Trans Ocean would be the exclusive shipper of Asia’s products between Shanghai and Los Angeles. Trans Ocean’s contract with Asia is effective on July 1, 2019. Before signing the contract with Asia, Trans Ocean did not operate the Shanghai Los Angeles route, and to satisfy the contract with Asia, in April 2019, Trans Ocean leases a cargo ship from Heavy Vessel Manufacturing (“Heavy”), which commences on July 1, 2019.
Because the shipping route is new, on July 1, 2019, (1) Trans Ocean has no other customers to deliver goods on the Shanghai-Los Angeles route and (2) because of operational costs, Trans Ocean does not have alternative uses for the leased cargo ship.
Trans Ocean adopted ASC 842, Leases, on January 1, 2019.
The following are relevant facts about Trans Ocean’s revenue contract with Asia, and Trans Ocean’s lease with Heavy.
Trans Ocean’s Revenue Contract With Asia
• The revenue contract’s stated term with Asia is for one year.
• Asia can renew the contract annually for up to four additional years. Therefore, the revenue contract can extend to five full years.
• Asia pays a significant up-front nonrefundable fee for the initial one-year term; the same amount is due at the beginning of every renewal period.
• Asia can cancel at any time without incurring a penalty outside of forfeiting any up-front nonrefundable fees already paid or owed at the beginning of the initial contract term and any and each renewed period.
• Although the contract is new, Trans Ocean and Asia have entered into similar arrangements with similar terms and historically, Asia has renewed for one or more years.
• Trans Ocean appropriately concludes that (1) the revenue contract meets the scope of, and criteria in, ASC 606, Revenue From Contracts With Customers, and (2) the contract term for its revenue contract with Asia is one year.
Trans Ocean’s Lease With Heavy
• The contract between Trans Ocean and Heavy contains a lease under ASC 842.
• Rental payments are at market and fixed each year.
• To mitigate risks, Trans Ocean negotiated the lease period and renewal options to mirror those of Trans Ocean’s revenue contract with Asia. As a result, the fixed, noncancelable term of the lease is one year, and Trans Ocean can renew annually for four additional years (i.e., up to five full years).
Trans Ocean believes that since Asia can terminate the revenue contract after one year (even though Asia may need to ship products for longer than a year and has historically renewed under other similarly structured contracts), it is uncertain whether Asia will renew the revenue contract. Because of this uncertainty, Trans Ocean believes that the renewal options related to the lease are not reasonably certain at the commencement date of the lease.
As a result, Trans Ocean concludes that the lease term for its lease contract with Heavy is also one year.
1. Under US GAAP, do you agree with Trans Ocean’s conclusion that the lease term for the cargo vessel is one year because the revenue contract is for one year?
2. According to US GAAP, what factors should Trans Ocean consider in supporting its conclusion related to the lease term?
Additional Facts:
On December 1, 2019, Trans Ocean entered into a shipping contract with Eastern Manufacturing Company (“Eastern”) to ship Eastern’s products between Shanghai and Los Angeles. The contract with Eastern commences on January 1, 2020, and on the basis of Trans Ocean’s evaluation of its enforceable rights and obligations in the contract with Eastern, Trans Ocean concludes that term of the revenue contract with Eastern is for a period of two years. Further, Trans Ocean concludes that (1) because of its contract with Asia and Eastern, it would not be operationally feasible to deploy the leased cargo vessel on other routes; (2) the cargo vessel will have sufficient capacity to service both Asia and Eastern; and (3) the leased asset is needed for Trans Ocean to perform under its revenue contract with Eastern (because of economic reasons that would not allow Trans Ocean to use another vessel).
3. Under US GAAP, should Trans Ocean reassess the lease term of the cargo vessel? If so, why?
4. Please answer questions 1 and 3 under IFRS/IAS.
In: Accounting
1. It has been suggested that global warming may increase the frequency of hurricanes. The table given below shows the number of major Atlantic hurricanes recorded annually before and after 1990.
| before 1995 | after 1995 | |||
| year | # of storms | year | # of storms | |
| 1976 | 2 | 1996 | 6 | |
| 1977 | 1 | 1997 | 1 | |
| 1978 | 2 | 1998 | 3 | |
| 1979 | 2 | 1999 | 5 | |
| 1980 | 2 | 2000 | 3 | |
| 1981 | 3 | 2001 | 4 | |
| 1982 | 1 | 2002 | 2 | |
| 1983 | 1 | 2003 | 3 | |
| 1984 | 1 | 2004 | 6 | |
| 1985 | 3 | 2005 | 7 | |
| 1986 | 0 | 2006 | 2 | |
| 1987 | 1 | 2007 | 2 | |
| 1988 | 3 | 2008 | 5 | |
| 1989 | 2 | 2009 | 2 | |
| 1990 | 1 | 2010 | 5 | |
| 1991 | 2 | 2011 | 4 | |
| 1992 | 1 | 2012 | 2 | |
| 1993 | 1 | 2013 | 0 | |
| 1994 | 0 | 2014 | 2 | |
| 1995 | 5 | 2015 | 2 | |
Does this data is sufficient enough to claim that the number of annual hurricanes increased since 1995? Do the test at 8% significance level. To do the test, answer the following: a. Write down the null and alternative hypotheses. b. Get the excel output and answer the following: i. Fill the cell with the p-value of the test with green color ii. Fill the cell with the test statistic of the test with yellow color
In: Statistics and Probability
| You have observed the following returns over time: | Assume the risk-free rate is 3.55% and the market risk premium is 4.60%. | ||||||||||||
| Year | Stock A | Stock B | Market | INPUT DATA | rRF | 3.55% | Market Risk Premium | 4.60% | |||||
| 1997 | 14.000% | 15.000% | 13.143% | a. What are the betas of Stocks A and B? | |||||||||
| 1998 | 11.000% | 9.000% | 11.029% | bA | bB | ||||||||
| 1999 | -2.500% | 5.000% | 4.109% | ||||||||||
| 2000 | 14.000% | 7.500% | 5.097% | b. What are the required rates of return for Stocks A and B? | |||||||||
| 2001 | 20.000% | 13.500% | 19.926% | rA | rB | ||||||||
| 2002 | 21.500% | 14.000% | 24.869% | ||||||||||
| 2003 | 22.400% | 13.500% | 21.903% | c. What is the required rate of return for a portfolio consisting of 40% A and 60% B? | |||||||||
| 2004 | 19.900% | 14.400% | 15.972% | INPUT DATA | wA | 40.00% | rp | ||||||
| 2005 | 21.100% | 16.700% | 13.006% | ||||||||||
| 2006 | 24.000% | 18.800% | 18.937% | d. Stock A is trading at a price consistent with the security market line. If your analysis suggests that Stock A will provide a return above the SML, does your analysis suggest that Stock A is undervalued or overvalued? Explain. | |||||||||
| 2007 | 26.300% | 19.700% | 16.960% | ||||||||||
| 2008 | 25.500% | 21.100% | 17.949% | ||||||||||
| 2009 | 22.100% | 23.400% | 19.926% | ||||||||||
| 2010 | 13.500% | 11.500% | 18.937% | ||||||||||
| 2011 | 6.400% | 8.800% | 10.040% | ||||||||||
| 2012 | -1.100% | 4.200% | -1.823% | ||||||||||
| 2013 | -4.000% | 5.600% | -1.328% | ||||||||||
| 2014 | 6.500% | 6.800% | 5.097% | ||||||||||
| 2015 | 7.400% | 8.700% | 10.040% | ||||||||||
| 2016 | 9.900% | 9.900% | 13.006% | ||||||||||
In: Finance
The questions in this exercise are based on Netflix, Inc. To answer the questions you will need to download Netilix’s Form 10-K for the year ended December 31, 2005 at www.sec.gov/edgar!searchedgar/companysearch.html. Once at this website, input CIK code 1065280 and hit enter. In the gray box on the right-hand side of your computer screen define the scope of your search by inputting 10-K and then pressing enter. Select the 10-K with a filing date of March 16, 2006. You do not need to print this document to answer the questions.
Required:
In: Accounting
An economist with a major bank wants to learn, quantitatively, how much spending on luxury goods and services can be explained based on consumers’ perception about the current state of the economy and what do they expect in the near future (6 months ahead). Consumers, of all income and wealth classes, were surveyed. Every year, 1500 consumers were interviewed. The bank having all of the data from the 1500 consumers interviewed every year, computed the average level of consumer confidence (an index ranging from 0 to 100, 100 being absolutely optimistic) and computed the average dollar amount spent on luxuries annually. Below is the data shown for the last 24 years.
Date X Y (in thousands of dollars)
1994 79.1 55.6
1995 79 54.8
1996 80.2 55.4
1997 80.5 55.9
1998 81.2 56.4
1999 80.8 57.3
2000 81.2 57
2001 80.7 57.5
2002 80.3 56.9
2003 79.4 55.8
2004 78.6 56.1
2005 78.3 55.7
2006 78.3 55.7
2007 77.8 55
2008 77.7 54.4
2009 77.6 54
2010 77.6 56
2011 78.5 56.7
2012 78.3 56.3
2013 78.5 57.2
2014 78.9 57.8
2015 79.8 58.7
2016 80.4 59.3
2017 80.7 59.9
Question:
In: Statistics and Probability
The data below is the total spending (in millions of dollars) on drugs and other non-durable products for your assigned state (or DC). You need to convert this data to spending per capita in constant 2019 dollars.
Go to the FRED database at https://fred.stlouisfed.org/
Search for the PCEPI. Change the frequency to annual. Using that price index (this is a national index; there isn't a PCE index for each state), convert the following to 2019Q3 dollars.
Again using the FRED database, find the population for your state. The symbol is usually the two letter abbreviation for the state and POP. New York, for example, would be NYPOP.
Using this information, covert the spending below into spending per capita, in 2019Q3 dollars. Keep in mind that the values below are in millions of dollars and you want your answers in dollars.
Enter your results for every even-numbered year in the answer
| Your assigned state: |
Alaska
| Year | Total spending on drugs and other non-durable products (millions of dollars) |
| 1991 | 142 |
| 1992 | 149 |
| 1993 | 153 |
| 1994 | 162 |
| 1995 | 156 |
| 1996 | 179 |
| 1997 | 209 |
| 1998 | 229 |
| 1999 | 262 |
| 2000 | 290 |
| 2001 | 317 |
| 2002 | 358 |
| 2003 | 411 |
| 2004 | 425 |
| 2005 | 455 |
| 2006 | 499 |
| 2007 | 531 |
| 2008 | 524 |
| 2009 | 503 |
| 2010 | 485 |
| 2011 | 480 |
| 2012 | 468 |
| 2013 | 430 |
| 2014 | 471 |
In: Economics
Despite the growth in digital entertainment, the nation’s 400 amusement parks have managed to hold on to visitors. A manager collects data on the number of visitors (in millions) to amusement parks in the United States. A portion of the data is shown in the accompanying table.
B-1) Estimate a linear trend model and an exponential trend model for the sample. (Round your answers to 2 decimal places.)
| Variable | Linear Trend | Exponential Trend | |
|---|---|---|---|
| Intercept | ? | ? | |
| T | ? | ? | |
| Standard Error | ? | ? |
B-2 Calculate the MSE for both trends. (Do not round estimates or intermediate calculations. Round final answers to 2 decimal places.)
| Linear Trend | Exponential Trend | |
|---|---|---|
| MSE | ? | ? |
b-3. By comparing MSE, which of the above methods perform better? Exponential or Linear?
c-1. Using the model of best fit, make a forecast for visitors to amusement parks in 2008. (Do not round estimates or intermediate calculations. Round your answer to 1 decimal place.)
| Y Hat or Y^ | ? | Million Visitors |
c-2. Using the model of best fit, make a forecast for visitors to amusement parks in 2009. (Do not round estimates or intermediate calculations. Round your answer to 1 decimal place.)
| Y Hat or Y^ | ? | Million Views |
| Year | Visitors |
| 2000 | 354 |
| 2001 | 338 |
| 2002 | 336 |
| 2003 | 310 |
| 2004 | 358 |
| 2005 | 375 |
| 2006 | 317 |
| 2007 | 305 |
In: Statistics and Probability
Use the procedure outlined in Section 11.6.2 on p.262 of textbook and the annual percentage default rate for all rated companies in Table 11.6 on p.259,
a. Estimate the probability of default (PD) and default correlation (ρ) for the period 1970-1993, and for the period 1994-2016 separately.
b. Plot the probability distribution of default rate (similar to Figure 11.6 on p.263) for the time period 1970-1993 and 1994-2016 together on the same graph.
| 970 | 2.631 |
| 1971 | 0.286 |
| 1972 | 0.453 |
| 1973 | 0.456 |
| 1974 | 0.275 |
| 1975 | 0.361 |
| 1976 | 0.176 |
| 1977 | 0.354 |
| 1978 | 0.354 |
| 1979 | 0.088 |
| 1980 | 0.344 |
| 1981 | 0.162 |
| 1982 | 1.04 |
| 1983 | 0.9 |
| 1984 | 0.869 |
| 1985 | 0.952 |
| 1986 | 1.83 |
| 1987 | 1.423 |
| 1988 | 1.393 |
| 1989 | 2.226 |
| 1990 | 3.572 |
| 1991 | 2.803 |
| 1992 | 1.337 |
| 1993 | 0.899 |
| 1994 | 0.651 |
| 1995 | 0.899 |
| 1996 | 0.506 |
| 1997 | 0.616 |
| 1998 | 1.137 |
| 1999 | 2.123 |
| 2000 | 2.455 |
| 2001 | 3.679 |
| 2002 | 2.924 |
| 2003 | 1.828 |
| 2004 | 0.834 |
| 2005 | 0.647 |
| 2006 | 0.593 |
| 2007 | 0.349 |
| 2008 | 2.507 |
| 2009 | 4.996 |
| 2010 | 1.232 |
| 2011 | 0.906 |
| 2012 | 1.23 |
| 2013 | 1.232 |
| 2014 | 0.939 |
| 2015 | 1.732 |
| 2016 | 2.149 |
Textbook Risk Management and Financial Institutions, 5th Edition
In: Finance
The number of hours worked per year per adult in a state is normally distributed with a standard deviation of 37. A sample of 115 adults is selected at random, and the number of hours worked per year per adult is given below. Use Excel to calculate the 98% confidence interval for the mean hours worked per year for adults in this state. Round your answers to two decimal places and use ascending order.
Number of hours
2250
1987
2029
2018
1938
2197
2099
2228
2245
1913
1903
2298
2231
2200
1902
2161
2211
2124
2082
2257
2087
2123
1929
1948
2124
2013
1973
2000
2030
1932
1993
2014
2118
1900
2195
2222
2035
2088
2010
1962
2166
1918
2070
2277
2114
1975
2045
2050
1921
2103
1954
2017
2235
1993
2156
1984
2057
2200
2133
2144
2145
2219
2222
2210
2143
2163
2168
2246
2186
1907
2072
2142
2187
2036
2207
2270
2262
2159
1914
1926
2261
2006
1948
2028
2256
2182
1955
1969
1941
1924
2176
2256
2051
2111
2221
2222
2190
2068
1942
2024
2258
2201
2085
2061
2004
2260
2136
2244
1989
1941
2297
2159
2260
2093
2293
In: Statistics and Probability