The Neal Company wants to estimate next year's return on equity (ROE) under different financial leverage ratios. Neal's total capital is $14 million, it currently uses only common equity, it has no future plans to use preferred stock in its capital structure, and its federal-plus-state tax rate is 40%. The CFO has estimated next year's EBIT for three possible states of the world: $5.8 million with a 0.2 probability, $3.4 million with a 0.5 probability, and $0.6 million with a 0.3 probability. Calculate Neal's expected ROE, standard deviation, and coefficient of variation for each of the following debt-to-capital ratios. Do not round intermediate calculations. Round your answers to two decimal places at the end of the calculations.
Debt/Capital ratio is 0.
| RÔE = | % |
| σ = | % |
| CV = |
Debt/Capital ratio is 10%, interest rate is 9%.
| RÔE = | % |
| σ = | % |
| CV = |
Debt/Capital ratio is 50%, interest rate is 11%.
| RÔE = | % |
| σ = | % |
| CV = |
Debt/Capital ratio is 60%, interest rate is 14%.
| RÔE = | % |
| σ = | % |
| CV = |
In: Finance
The Neal Company wants to estimate next year's return on equity (ROE) under different financial leverage ratios. Neal's total capital is $13 million, it currently uses only common equity, it has no future plans to use preferred stock in its capital structure, and its federal-plus-state tax rate is 40%. The CFO has estimated next year's EBIT for three possible states of the world: $5 million with a 0.2 probability, $2.9 million with a 0.5 probability, and $0.4 million with a 0.3 probability. Calculate Neal's expected ROE, standard deviation, and coefficient of variation for each of the following debt-to-capital ratios. Do not round intermediate calculations. Round your answers to two decimal places at the end of the calculations.
Debt/Capital ratio is 0.
| RÔE = | % |
| σ = | % |
| CV = |
Debt/Capital ratio is 10%, interest rate is 9%.
| RÔE = | % |
| σ = | % |
| CV = |
Debt/Capital ratio is 50%, interest rate is 11%.
| RÔE = | % |
| σ = | % |
| CV = |
Debt/Capital ratio is 60%, interest rate is 14%.
| RÔE = | % |
| σ = | % |
| CV = |
In: Finance
FINANCIAL LEVERAGE EFFECTS The Neal Company wants to estimate next year's return on equity (ROE) under different financial leverage ratios. Neal's total capital is $20 million, it currently uses only common equity, it has no future plans to use preferred stock in its capital structure, and its federal-plus-state tax rate is 40%. The CFO has estimated next year's EBIT for three possible states of the world: $4.2 million with a 0.2 probability, $3.1 million with a 0.5 probability, and $0.7 million with a 0.3 probability. Calculate Neal's expected ROE, standard deviation, and coefficient of variation for each of the following debt-to-capital ratios. Do not round intermediate calculations. Round your answers to two decimal places at the end of the calculations. Debt/Capital ratio is 0. RÔE = % σ = % CV = Debt/Capital ratio is 10%, interest rate is 9%. RÔE = % σ = % CV = Debt/Capital ratio is 50%, interest rate is 11%. RÔE = % σ = % CV = Debt/Capital ratio is 60%, interest rate is 14%. RÔE = % σ = % CV =
In: Finance
The Neal Company wants to estimate next year's return on equity (ROE) under different financial leverage ratios. Neal's total capital is $15 million, it currently uses only common equity, it has no future plans to use preferred stock in its capital structure, and its federal-plus-state tax rate is 40%. The CFO has estimated next year's EBIT for three possible states of the world: $5.2 million with a 0.2 probability, $2.4 million with a 0.5 probability, and $0.7 million with a 0.3 probability. Calculate Neal's expected ROE, standard deviation, and coefficient of variation for each of the following debt-to-capital ratios. Do not round intermediate calculations. Round your answers to two decimal places at the end of the calculations.
Debt/Capital ratio is 0.
| RÔE = | % |
| σ = | % |
| CV = |
Debt/Capital ratio is 10%, interest rate is 9%.
| RÔE = | % |
| σ = | % |
| CV = |
Debt/Capital ratio is 50%, interest rate is 11%.
| RÔE = | % |
| σ = | % |
| CV = |
Debt/Capital ratio is 60%, interest rate is 14%.
| RÔE = | % |
| σ = | % |
| CV = |
In: Finance
Collision derivation problem. A car is released from rest on a
frictionless inclined plane (Figure 5.3). EXAMPLES: Calculate the
momentum pi at the end of the plane in terms of the measured
quantities x, y, L, and m. Assume is very small so that h/L is
approximately equal to y/x. (Hint: use conservation of energy and
the fact that K=1 2mv2=p2 2m.)
[Answer: .]
If a car suffers a nearly elastic collision it will coast back up
the ramp a distance Lf before reversing direction. What is the
momentum pf immediately following the collision? The general
expression for the change in momentum suffered in a collision is is
= - . What is p (the magnitude of ) in terms of x, y, Li, Lf, and
m?
[Answer: .]
This is the expression you should use in the experiment. Make sure
you understand how to derive these equations.
QUESTION:
If the car has a mass of 0.3 kg, the ratio of height to width of
the ramp is 11/110, the initial displacement is 1.8 m, and the
change in momentum is 0.62 kg*m/s, how far will it coast back up
the ramp before changing directions?
In: Physics
I want this program written in JAVA with the algorithm(The step by step process for the problem) . Please help it is due in a couple of hours. I don't want the C++ program, I want it in JAVA please
#20 Theater Ticket Sales
Create a TicketManager class and a program that uses it to sell tickets for a single performance theater production.
Here are the specifications:
• The theater's auditorium has 15 rows, with 30 seats in each row.
To represent the seats, the TicketManager class should have a
two-dimensional array of SeatStructures. Each of these structures
should have data members to keep track of the seat's price and
whether or not it is available or already sold.
• The data for the program is to be read in from two files located
in the Chapter 8 programs folder on this book's companion website.
The first one, SeatPrices.dat, contains 15 values representing the
price for each row. All seats in a given row are the same price,
but different rows have different prices. The second file,
SeatAvailability. dat, holds the seat availability information. It
contains 450 characters (15 rows with 30 characters each),
indicating which seats have been sold (' • ') and which are
available ( '#' ). Initially all seats are available. However, once
the program runs and the file is updated, some of the seats will
have been sold. The obvious function to read in the data from these
files and set up the array is the constructor that runs when the
TicketManager object is first created.
• The client program should be a menu-driven program that provides
the user with a menu of box office options, accepts and validates
user inputs, and calls appropriate class functions to carry out
desired tasks. The menu should have options to display the seating
chart, request tickets, print a sales report, and exit the
program.
• When the user selects the display seats menu option, a
TicketManager function should be called that creates and returns a
string holding a chart, similar to the one shown here. It should
indicate which seats are already sold ( *) and which are still
available for purchase (#) . The client program should then display
the string.
Seats 1234567890 12345678901234567890
Row 1 ***###***###******############
Row 2 ####*************####*******##
Row 3 **###**********########****###
Row 4 **######**************##******
Row 5 ********#####*********########
Row 6 ##############************####
Row 7 #######************###########
Row 8 ************##****############
Row 9 #########*****############****
Row 10 #####*************############
Row 11 #**********#################**
Row 12 #############********########*
Row 13 ###***********########**######
Row 14 ##############################
Row 15 ##############################
• When the user selects the request tickets menu option , the
program should prompt for the number of seats the patron wants, the
desired row number, and the desired starting seat number. A
TicketManager ticket request function should then be called and
passed this information so that it can handle the ticket request.
If any of the requested seats do not exist, or are not available,
an appropriate message should be returned to be displayed by the
client program. If the seats exist and are available, a string
should be created and returned that lists the number of requested
seats, the price per seat in the requested row, and the total price
for the seats. Then the user program should ask if the patron
wishes to purchase these seats.
• If the patron indicates they do want to buy the requested seats ,
a TicketManager purchase tickets module should be called to handle
the actual sale. This module must be able to accept money, ensure
that it is sufficient to continue with the sale, and if it is, mark
the seat(s) as sold, and create and return a string that includes a
ticket for each seat sold (with the correct row, seat number, and
price on it).
• When the user selects the sales report menu option, a
TicketManager report module should be called. This module must
create and return a string holding a report that tells how many
seats have been sold, how many are still available, and how much
money has been collected so far for the sold seats. Think about how
your team will either calculate or collect and store this
information so that it will be available when it is needed for the
report.
• When the day of ticket sales is over and the quit menu choice is
selected, the program needs to be able to write the updated seat
availability data back out to the file. The obvious place to do
this is in the TicketManager destructor.
In: Computer Science
Article: Anheuser-Busch Orders 40 Tesla Semi Trucks (Brewer hasn't yet decided whether to buy vehicles outright or lease them as it seeks to cut fuel costs and vehicle emissions.
Forget the Clydesdales. Anheuser-Busch has reserved 40 of Tesla Inc.’sTSLA -1.15% all-electric Semi trucks, as the maker of Budweiser seeks to reduce fuel costs and vehicle emissions.
The U.S. subsidiary of Anheuser-Busch InBev BUD -2.22% NV plans to use the trucks for shipments to wholesalers within 150 to 200 miles of its brewery locations—well within the 500-mile range that Tesla Chief Executive Elon Musk has promised. The vehicles would be deployed among the brewer’s so-called dedicated fleets of about 750 trucks, which bear the company’s branding but are owned and managed by outside carriers.
One of the largest known reservations since the Semi was unveiled last month, Anheuser-Busch’s preorder is still tiny relative to the broader heavy-duty-truck market, which produces 250,000 to 300,000 big rigs a year.
Anheuser-Busch hasn’t yet decided whether to buy the vehicles outright or lease them, said James Sembrot, the company’s senior director of logistics strategy. It could also ask one of its dedicated carriers to buy or lease the trucks. The Semi won’t be available until 2019. “We put the reservations down so we can prioritize our place in line,” he said. “We don’t know who the carrier is going to be in two to three years when these things are actually produced.”
He declined to discuss the cost for the reservation, which he said was made before Tesla introduced the Semi in California last month. Tesla had set deposits at $5,000 at the time of the November announcement but has since raised the amount to $20,000. Tesla expects the trucks to list for $150,000 to $200,000; a new diesel-powered heavy-duty truck can sell for $150,000.
The Semi tractors are designed to travel as much as 500 miles on a single charge. Some question whether electric vehicles are a viable option for long-haul trucking, citing concerns about range and battery weight.
Still, companies looking to trim transportation costs are seeking to test out the Tesla truck. J.B. Hunt Transport Services Inc. and Wal-Mart Stores Inc., which each operate thousands of trucks, have reserved Semis, as has Deutsche Post AG’s DHL Supply Chain and truck-leasing and fleet-management company Ryder System Inc.
Fuel, along with labor, is historically one of the biggest expenses for trucking companies, according to the American Transportation Research Institute, an industry research group.
Anheuser-Busch spends about $120 million on fuel each year for its dedicated fleets and long-haul transportation by for-hire carriers moving beer between breweries and wholesalers, Mr. Sembrot said. The company wants to cut its carbon footprint by 30% by 2025, and has invested in alternative-fuel vehicles, such as leasing delivery trucks that run on compressed natural gas. It is also in discussions with Nikola Motor Co., which is developing hydrogen-electric semi-trucks.
Mr. Sembrot said Anheuser-Busch views the Tesla truck and the Nikola vehicle, which the company says will be able to travel from 800 to 1,200 miles on one fill-up, as potentially complementary technologies.
“We have needs for all those types of distances,” he said.
How much the Semi can haul remains in question, however.
“You don’t have a transmission, you don’t have an engine, but how much exactly does the battery weigh,” Mr. Sembrot said. “We’re not shipping cotton balls around, so the weight of the equipment matters to us.”
But many trucking companies, which move freight thousands of miles across the country, might not be as eager to test out the new Tesla trucks.
“We’re going to sit on the sidelines and watch that develop,” said James Welch, chief executive of YRC Worldwide Inc., one of the largest less-than-truckload carriers.
YRC trucks make both local and long-distance trips, and the Tesla truck’s 500-mile range would be a liability on long-haul routes, he said. The company would also have difficulty maximizing electric trucks’ time on the road because they need longer to recharge, compared with time needed to refuel a diesel-powered big rig.
“Recharging time has to be quick because you’re paying a driver whether he or she is running or sitting,” Mr. Welch said.
Question
What are the three key takeaway statements (please write a discussion)?
In: Accounting
You are applying for a data job, and your assignment is to analyze the following data set for monthly average temperatures at St Catherines in the programming language R.
(a) Prepare some plots that visualize the data.
(b) Find the appropriate time series model and fit the data. Explain your choice of parameters.
(c) Make predictions for the next 3 years, plot these predictions.
(d) Summarize your findings.
The Data is provided below. Please show the R codes as well. Thank you!
"Month","Average monthly temperatures St Cathrines"
“1980-01", 3.3
“1980-02", 5.5
“1980-03", 0.5
“1980-04", 7.4
“1980-05", 14.4
“1980-06", 16.6
“1980-07", 21.8
“1980-08", 22.8
“1980-09", 16.9
“1980-10", 8.4
“1980-11", 3.4
“1980-12", 4.3
“1981-01", 7.6
“1981-02", 0.6
“1981-03”, 1.6
“1981-04", 8.5
“1981-05", 12.4
“1981-06", 19.2
“1981-07", 22.1
“1981-08", 20.7
“1981-09", 16.0
“1981-10", 7.7
“1981-11", 4.5
“1981-12", 1.3
“1982-01", 7.7
“1982-02", 5.3
“1982-03", 0.3
“1982-04", 5.7
“1982-05", 14.0
“1982-06", 15.9
“1982-07", 21.9
“1982-08", 18.4
“1982-09", 15.9
“1982-10", 11.2
“1982-11", 5.8
“1982-12", 3.0
“1983-01", 2.3
“1983-02", 1.6
“1983-03", 1.9
“1983-04", 6.5
“1983-05", 11.6
“1983-06", 19.6
“1983-07", 23.3
“1983-08”, 21.5
“1983-09", 17.5
“1983-10", 10.8
“1983-11", 4.9
“1983-12", 4.2
“1984-01", 6.1
“1984-02", 0.4
“1984-03", 3.0
“1984-04", 7.5
“1984-05", 11.0
“1984-06", 19.6
“1984-07", 21.0
“1984-08", 22.0
“1984-09", 15.4
“1984-10", 11.3
“1984-11", 4.6
“1984-12", 0.9
“1985-01", 6.0
“1985-02", 4.0
“1985-03", 2.3
“1985-04", 8.7
“1985-05", 14.3
“1985-06", 17.0
“1985-07", 21.1
“1985-08", 20.7
“1985-09", 18.3
“1985-10”, 10.9
“1985-11", 4.9
“1985-12", 3.2
“1986-01", 3.6
“1986-02", 4.8
“1986-03", 1.9
“1986-04", 8.1
“1986-05", 15.0
“1986-06", 17.7
“1986-07", 21.9
“1986-08", 19.7
“1986-09", 16.1
“1986-10", 10.4
“1986-11", 2.9
“1986-12", 0.4
“1987-01”, 3.1
“1987-02", 3.7
“1987-03", 2.7
“1987-04", 9.0
“1987-05", 15.0
“1987-06", 20.2
“1987-07", 23.5
“1987-08", 20.3
“1987-09", 16.8
“1987-10", 8.3
“1987-11", 5.3
“1987-12", 1.1
“1988-01", 3.3
“1988-02", 4.5
“1988-03”, 1.1
“1988-04", 6.7
“1988-05", 14.6
“1988-06", 18.4
“1988-07", 23.7
“1988-08", 22.2
“1988-09", 16.4
“1988-10", 8.4
“1988-11", 6.0
“1988-12", 1.1
“1989-01", 0.7
“1989-02", 4.7
“1989-03", 0.3
“1989-04", 5.6
“1989-05", 13.2
“1989-06", 19.2
“1989-07", 22.2
“1989-08", 20.7
“1989-09", 16.8
“1989-10", 11.1
“1989-11", 3.7
“1989-12", 7.5
“1990-01", 0.7
“1990-02", 1.8
“1990-03", 2.1
“1990-04”, 8.9
“1990-05", 12.1
“1990-06", 19.4
“1990-07", 21.5
“1990-08", 21.0
“1990-09", 16.2
“1990-10", 10.7
“1990-11", 5.8
“1990-12", 0.6
“1991-01", 3.9
“1991-02", 0.6
“1991-03", 2.9
“1991-04", 9.1
“1991-05", 16.8
“1991-06", 20.6
“1991-07", 22.1
“1991-08", 21.8
“1991-09", 16.4
“1991-10", 11.4
“1991-11", 4.2
“1991-12”, 0.1
“1992-01", 2.5
“1992-02", 2.1
“1992-03", 0.1
“1992-04", 6.1
“1992-05", 12.8
“1992-06", 16.9
“1992-07", 18.8
“1992-08", 18.9
“1992-09", 15.9
“1992-10", 8.5
“1992-11", 4.2
“1992-12", 0.3
“1993-01", 1.8
“1993-02", 6.8
“1993-03”, 1.7
“1993-04", 7.4
“1993-05", 12.7
“1993-06", 17.8
“1993-07", 22.4
“1993-08", 21.7
“1993-09", 15.1
“1993-10", 9.0
“1993-11", 3.9
“1993-12", 1.7
“1994-01”, 9.1
“1994-02", 6.2
“1994-03", 0.2
“1994-04", 8.2
“1994-05", 11.6
“1994-06", 19.3
“1994-07", 22.2
“1994-08", 19.6
“1994-09", 16.4
“1994-10", 10.6
“1994-11", 6.8
“1994-12", 1.0
“1995-01", 1.2
“1995-02", 5.7
“1995-03", 3.0
“1995-04", 5.2
“1995-05", 13.6
“1995-06", 20.0
“1995-07", 22.1
“1995-08", 21.9
“1995-09", 15.4
“1995-10”, 12.0
“1995-11", 2.4
“1995-12", 3.4
“1996-01", 5.2
“1996-02", 4.4
“1996-03", 2.0
“1996-04", 6.0
“1996-05", 12.2
“1996-06", 19.4
“1996-07", 20.5
“1996-08”, 21.7
“1996-09", 17.3
“1996-10", 10.7
“1996-11", 2.4
“1996-12", 0.8
“1997-01", 4.1
“1997-02", 0.9
“1997-03", 0.4
“1997-04", 6.2
“1997-06", 20.0
“1997-07", 20.7
“1997-08", 19.6
“1997-09", 16.3
“1997-10", 10.1
“1997-11", 3.3
“1997-12", 0.5
“1998-01", 0.6
“1998-02", 0.7
“1998-03", 3.3
“1998-04", 9.0
“1998-05", 16.9
“1998-06", 19.5
“1998-07", 21.8
“1998-08”, 22.1
“1998-09", 19.0
“1998-10", 11.6
“1998-11", 6.1
“1998-12", 2.5
“1999-01", 4.7
“1999-02", 0.5
“1999-03", 0.7
“1999-04", 8.1
“1999-05”, 15.4
“1999-06", 21.2
“1999-07", 24.6
“1999-08", 20.3
“1999-09", 18.5
“1999-10”, 10.6
“1999-11", 6.8
“1999-12", 0.5
In: Statistics and Probability
Soap Makers International
Several years ago, Ingrid Krause wanted some international expertise and applied for a transfer to her company’s soap division, which is located south of Warsaw, Poland. The soap division manufactures hand soap for use in a large number of settings, from hospitals to luxury hotels. Ingrid was awarded the transfer to the soap division and was assigned to the accounting department. She is responsible for overseeing the costing and probability analysis of the various soaps and soap-making processes. During her tenure in the soap division, there were numerous changes in the number of soaps manufactured and the processes to make the different soaps. Consequently, Ingrid’s position required her to consider changes in the accounting processes to reflect the changes in the soap division’s business.
For several decades, the company’s soap-making process required a large labour force that manufactured and packaged the soap mainly by hand. Local economic changes meant that the labour force that the factory required was not as available as it had been in the past. As a result, the division was experiencing slower processing time, and more snap being rejected during inspections because of quality concerns. To address the issues related to the lack of labour availability, the division’s management decided three years ago that automation was the way to go. Consequently, over the last three years, the soap making processes have changed with the implementation of automation.
The automation of the soap making processes have allowed for a much larger variety of soap and packing, a reduced direct labour force and direct labour costs, and a higher level of traceability of costs to the various soaps because of technological improvements. Soaps made for industrial applications require different ingredients, less time in processing, less time in finishing, and less time in and cheaper packaging than do soaps for the hotel industry. The costs of materials and packaging are directly traceable to the various types of soaps through new software that uses bar codes and counters to trace material costs to the various soaps directly.
Ingrid feels that the current costing system should be revisited. The cost driver for allocation of the overhead costs (such as supervisory salaries and plant utilities) have always been direct labour hours cost. However, given the decline in the use of labour due to automation, Ingrid is questioning its suitability as a basis of allocation. Ingrid would like to explore activity based costing to allocate overhead costs.
Ingrid has gathered cost data for two representative soaps: one sold to hospitals and one sold to hotels. Further, Ingrid has gathered data from the automated system on the amount of time each type of soap spends in the three manufacturing processes: processing, finishing, and packaging. The soap is produced in large batches, consequently, the data are adjusted to reflect the average cost per 100g of soap. The data for type of soap for one month’s production are in Exhibit 1.
REQUIRED
Prepare a report for Ingrid Krause that addresses her interest in exploring an activity-based costing (ABC) system while including the following:
EXHIBIT 1 – COSTS FOR ONE MONTH’S PRODUCTION OF SOAP
|
Cost Components |
Total |
Costs Per 100 g of soap |
|
|
Industrial Soap (Hospital) |
Luxury Soap (Hotel) |
||
|
Direct Materials |
$4.000,000 |
$0.40 |
$0.80 |
|
Packaging |
$2,000,000 |
$0.10 |
$0.60 |
|
Direct Labour |
$750,000 |
$0.14 |
$0.15 |
|
Manufacturing |
$5,000,000 |
||
|
Processing |
$2,500,000 |
||
|
Finishing |
$1,500,000 |
||
|
Packaging |
$1,000,000 |
||
EXHIBIT 2 – TIME REQUIRED FOR ONE MONTH’S PRODUCTION OF SOAP
|
Time Components |
Total |
Time per 100 g of soap |
|
|
Industrial Soap (Hospital) |
Luxury Soap (Hotel) |
||
|
Processing |
750,000 seconds |
0.2 second |
0.4 second |
|
Finishing |
300,000 seconds |
0.03 second |
0.4 second |
|
Packaging |
100,000 seconds |
0.006 second |
0.5 second |
In: Accounting
Marsha Jones has bought a used Mercedes horse transporter for
her Connecticut estate. It cost $50,000. The object is to save on
horse transporter rentals.
Marsha had been renting a transporter every other week for $215 per
day plus $1.75 per mile. Most of the trips are 80 or 100 miles in
total. Marsha usually gives Joe Laminitis, the driver, a $40 tip.
With the new transporter she will only have to pay for diesel fuel
and maintenance, at about $0.60 per mile. Insurance costs for
Marsha’s transporter are $1,950 per year.
The transporter will probably be worth $30,000 (in real terms)
after eight years, when Marsha’s horse Spike will be ready to
retire. Assume a nominal discount rate of 7% and a 3% forecasted
inflation rate. Marsha’s transporter is a personal outlay, not a
business or financial investment, so taxes can be ignored.
Calculate the NPV of the investment. (Do not round
intermediate calculations. Round your answer to the nearest whole
dollar amount.)
In: Finance