Question
In: Finance
Consider the following data: Year 1 Year 2 Year 3 Year 4 Book Value of Equity...
Consider the following data:
| Year 1 | Year 2 | Year 3 | Year 4 | |
| Book Value of Equity | 25 | |||
| ROE | 22% | 22% | 30% | 30% |
| Payout | 65% | 65% | 60% | 60% |
| Net Income | ||||
| Dividends | ||||
| Retained Earnings | ||||
| g | - |
a) Complete the table.
b) Check that in period 2 and period 4, the dividends grow according to the formula: g = ROE (1 - Payout) and explain.
c) Determine the value of equity (E), taking into account that the dividend growth rate after the 4th year is the same as in the 4th year, and that the required return on equity is 20%.
Solutions
jeff jeffy answered 1 year agoRelated Solutions
Consider the following data for the airline industry for July 2018 (EV=enterprise value, Book=equity book value)....
Consider the following data for the airline industry for July
2018 (EV=enterprise value, Book=equity book value). Suppose Alaska
Air (ALK) has 124 million shares outstanding. Estimate Alaska Air's
share value using each of the five valuation multiples, based on
the median valuation multiple of the other seven airlines shown.
Company Name Market Capitalization Enterprise Value (EV) EV/Sales
EV/EBITDA EV/EBIT P/E Forward P/E Alaska Air (ALK) 7286 8207 1.02
5.1 6.7 7.7 12.5 American Airlines (AAL) 17879 37327 0.87 5.7 8.2...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 2 4...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
2
4
5
2
4
5
8
3
1
3
4
4
7
9
10
(a)
Choose the correct time series plot.
(i)
(ii)
(iii)
(iv)
- Select your answer -Plot (i)Plot (ii)Plot (iii)Plot (iv)Item
1
What type of pattern exists in the data?
- Select your answer -Positive trend pattern, no
seasonalityHorizontal pattern, no seasonalityNegative trend
pattern, no seasonalityPositive trend pattern, with
seasonalityHorizontal pattern, with...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 4 6...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
4
6
7
2
0
1
4
3
3
5
6
4
5
7
8
(b)
Use a multiple regression model with dummy variables as follows
to develop an equation to account for seasonal effects in the data.
Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2, 0
otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise.
If required, round your...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 4 6...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
4
6
7
2
2
3
6
3
3
5
6
4
5
7
8
Compute seasonal indexes and adjusted seasonal indexes for the
four quarters (to 3 decimals).
Quarter
Seasonal
Index
Adjusted
Seasonal
Index
1
(___)
(___)
2
(___)
(___)
3
(___)
(___)
4
(___)
(___)
Total
(___)
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
5
5
6...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 4 6...
Consider the following time series data.
Quarter
Year 1
Year 2
Year 3
1
4
6
7
2
2
3
6
3
3
5
6
4
5
7
8
(a)
Choose the correct time series plot.
(i)
(ii)
(iii)
(iv)
- Select your answer -Plot (i)Plot (ii)Plot (iii)Plot (iv)Item
1
What type of pattern exists in the data?
- Select your answer -Only randomnessRandomness & Linear
trendRandomness & SeasonalityRandomness, Linear trend &
SeasonalityItem 2
(b)
Use a multiple regression model...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 4 6...
Consider the following time series data.
Quarter Year 1 Year 2 Year 3
1 4 6 7
2 2 3 6
3 3 5 6
4 5 7 8
1.plot with line dot chart.
2.What type of pattern exists in the data?
a.Upward Trend Patter,
b. Downward Trend Pattern
c. Horizontal Pattern With Seasonality.
3.Use a multiple regression model with dummy variables as
follows to develop an equation to account for seasonal effects in
the data. Qtr1 = 1 if...
2. Consider the following data: x= 1, 2, 3, 4, 5 y =3, 2, 4, 6,...
2. Consider the following data:
x= 1, 2, 3, 4, 5
y =3, 2, 4, 6, 5
By hand, not using Matlab, and showing your work:
(a) Compute the correlation coefficient.
(b) Find the least-squares line.
(c) Find the standard deviation around the least-squares
line.
Question 1. Consider the following time series data. Week 1 2 3 4 5 6 Value...
Question 1. Consider the following time series
data.
Week
1
2
3
4
5
6
Value
118
113
116
111
117
114
Construct a time series plot. What type of pattern
exists in the data?
Develop a three-week moving average for this time
series. Compute MSE and a forecast for week 7.
Use a =0.2 to compute the exponential smoothing values
for the time series. Compute MSE and a forecast for week
7.
Compare the three-week moving average forecast with...
Consider the following time series data. Quarter Year 1Year2 Year 3 1 4 6 7 2...
Consider the following time series data.
Quarter
Year
1Year2
Year 3
1
4
6
7
2
2
3
6
3
3
5
6
4
5
7
8
b.) Use the following dummy variables to develop an estimated
regression equation to account for any seasonal and linear trend
effects in the data: Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1
if Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise (to 3
decimals if necessary)....
Consider the following time series data. Week 1 2 3 4 5 6 Value 19 12...
Consider the following time series data.
Week
1
2
3
4
5
6
Value
19
12
15
11
18
13
a. Use α = 0.2 to compute the exponential smoothing
forecasts for the time series.
Week
Time Series
Value
Forecast
1
19
2
12
3
15
4
11
5
18
6
13
Compute MSE. (Round your answer to two decimal places.)
MSE =
b. Use a smoothing constant of α = 0.4 to compute the
exponential smoothing forecasts.
Week
Time...
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