Suppose you are given the yield curve as follows:
i1 = 2%; i2 = 3%; i3 = 4%; i4 = 5%. i5 = 7%, i10 = 10%. These represent the 1-year, 2-year, 3-year and 4-year, 5-year, 10-year bond yields today. Under the pure expectations theory, find a) the expected future one-year rates that will prevail from year 1 to year 2 b) from year 2 to year 3; & c) from year 3 to year 4.
Discuss how financial advisors use the shape of the curve in above questions as part of investment advice.
?
In: Finance
Suppose that X1 and X2 are two random variables. Suppose that X1 has mean 1 and variance 4 while X2 has mean 3 and variance 9. Finally, suppose that the correlation between X1 and X2 is 3/8. Denote Y = 2X1 − X2. (67) The mean of Y is (a) 1 (b) 4 (c) -2 (d) -1 (68) The variance of Y is (a) 25 (b) 4 (c) 9 (d) 16 (69) The standard deviation of Y is (a) 5 (b) 2 (c) 3 (d) 4 (70) The correlation between X1 and Y is (a) 0 (b) 23/32 (c) 16/9 (d) 1 i need a clear, thorough answer to question 70 please.
In: Statistics and Probability
(Be sure to paste the R Console Output and code!!!) Using the following data and R, write a brief paragraph about whether the in-home treatment is equally effective as the out-of-home treatment for two separate groups. Here are the data. The outcome variable is level of anxiety after treatment on a scale from 1 to 10.
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In-Home Treatment |
Out-of-Home Treatment |
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In: Statistics and Probability
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Question 45 (1 point)
All of the following are related to active life expectancy for minorities except:
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Question 46 (1 point)
One of the recommendations to preserve Social Security is to raise the normal retirement age. A consequence of raising it is that:
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Question 47 (1 point)
A women's risk of poverty ________ if she gets a divorce.
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Question 48 (1 point)
In comparison with the types of diseases that caused deaths among older people in the United States in the nineteenth century, one of the major causes of death among people 65 years and older today is _____.
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Question 49 (1 point)
Functional age may be measured by:
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In: Psychology
Sentinel Company is considering an investment in technology to
improve its operations. The investment will require an initial
outlay of $256,000 and will yield the following expected cash
flows. Management requires investments to have a payback period of
3 years, and it requires a 8% return on investments. (PV of $1, FV
of $1, PVA of $1, and FVA of $1) (Use appropriate factor(s)
from the table provided.)
| Period | Cash Flow | |||
| 1 | $ | 47,400 | ||
| 2 | 52,800 | |||
| 3 | 76,600 | |||
| 4 | 95,800 | |||
| 5 | 125,100 | |||
Required:
1. Determine the payback period for this
investment.
2. Determine the break-even time for this
investment.
3. Determine the net present value for this
investment.
Complete this question by entering your answers in the tabs below.
Determine the payback period for this investment. (Enter cash outflows with a minus sign. Round your Payback Period answer to 1 decimal place.)
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Complete this question by entering your answers in the tabs below.
Determine the payback period for this investment. (Enter cash outflows with a minus sign. Round your Payback Period answer to 1 decimal place.)
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Complete this question by entering your answers in the tabs below.
Determine the payback period for this investment. (Enter cash outflows with a minus sign. Round your Payback Period answer to 1 decimal place.)
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Complete this question by entering your answers in the tabs below.
Determine the payback period for this investment. (Enter cash outflows with a minus sign. Round your Payback Period answer to 1 decimal place.)
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Complete this question by entering your answers in the tabs below.
Determine the net present value for this investment.
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In: Accounting
Suppose that the Gross Domestic Product (GDP) in the US is denoted as Gt. Let the quarterly data of Gt from 1980:1 to 2015:1 is non-stationary but the first difference of Gt, denoted as DGt, is stationary. Assume that a researcher identified the following AR model for DGt:
DGt = Alpha0 + Alpha1DGt-1 + Alpha3DGt-3 + Alpha4DGt-4 + et
Suppose the estimated results of the above AR model are as follows:
DGt = 6.09 + 0.18DGt-1 + 0.12DGt-3 + 0.05DGt-4
(a) Based on what criteria of the coefficients of auto-correlation function (ACF) and the coefficients of partial auto-correlation function (PACF), the researcher identified the above AR model? Explain. Also explain why the researcher chose 1, 3, and 4 lags.
(b) Forecast the GDP for 2015:2, assuming that the GDP in 2015:1, 2014:4, 2014:3, 2014:2, 2014:1, 2013:4, 2013:3, and 2013:2 respectively are: 16264.1, 16294.7, 16205.6, 16010.4, 15831.7, 15916.2,15779.9, and 15606.6.
(c) Explain how to conduct a diagnostic test to check if the researcher has identified the correct AR model. (Hint: Step 3 of Box-Jenkin’s Method)
Please show work.
In: Math
On December 31, 2019, Sumner Company held Wall Company bonds in its portfolio of trading securities. The bonds have a par value of $40,000, carry a 10% annual interest rate, mature in 2026, and had originally been purchased at par. The market value of the bonds on December 31, 2019 was $38,000.
On January 1, 2020, Sumner acquired bonds of Doherty Company with a par value of $30,000 for $30,200. The Doherty Company bonds carry an annual interest rate of 12% and mature on December 31, 2024. Additionally, on the same date, Sumner acquired Maggio Company bonds with a face value of $20,000 for $19,500. The Maggio Company bonds carry an 8% annual interest rate and mature on December 31, 2029. At the end of 2020, the respective market values of the bonds were: Wall, $39,000; Doherty, $31,000; and Maggio, $21,000. Sumner classifies all of the debt securities as trading. Assume that Sumner uses the straight-line method to amortize any discounts or premiums.
Required:
| 1. | Prepare the journal entries necessary to record the purchase of the investments on January 1, 2020, the annual interest payments on December 31, 2020, and the adjusting entry needed on December 31, 2020. |
| 2. | What would Sumner disclose on its December 31, 2020, balance sheet related to these investments? |
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In: Accounting
** Use R for the following analysis.
Use the BoneAcid.xlsx data to check what is causing the variation in the acid content in bones among 42 male skeletons from 2 cemeteries. The independent variables included are internment lengths, ages, depths, lime addition and contamination in soil.
Variables/Columns
Burial Site (1 or 2)
Internment Time (Years)
Burial Depth (feet)
LimeAdded (at internment) (1=Yes, 0=No)
Death_Age (Age of Person at the time of death)
Acid Level (g/100g of bone)
Contamination (In soil) (1=Yes, 0=No)
1. Undertake appropriate basic data analytics to motivate the regression model Use dummy variables for each of Burial Site, LimeAdded, and Contamination (If required create the dummy-variables for each).
2. Do you suspect any multicollinearity problem could affect the regression coefficients?
3. Run a regression model of the Acid Level on all independent variables provided and interpret all regression coefficients.
4. Briefly describe what you need to do before conducting any hypothesis testing when you find evidence of heteroscedasticity in an OLS regression model? Test for heteroscedasticity to check for evidence of heteroscedasticity in part 3
5. Test the hypothesis that
i. Beta_InternmentTime < -0.00675
ii. Jointly Beta_BurialSite = Beta_BurialDepth =Beta_LimeAdded=0
6, What is the best model specification that would explain acid content in bones better?
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Burial Site |
InternmentTime |
Baurial Depth |
LimeAdded |
Death_Age |
Contamination |
Acid Level |
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1 |
88.5 |
7 |
1 |
34 |
1 |
3.88 |
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1 |
88.5 |
7 |
1 |
38 |
1 |
4 |
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1 |
85.2 |
7 |
1 |
27 |
1 |
3.69 |
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1 |
71.8 |
7.6 |
1 |
26 |
0 |
3.88 |
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1 |
70.6 |
7.5 |
1 |
42 |
0 |
3.53 |
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1 |
68 |
7 |
1 |
28 |
0 |
3.93 |
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1 |
71.6 |
8 |
1 |
35 |
0 |
3.88 |
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1 |
70.2 |
6 |
1 |
44 |
0 |
3.64 |
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1 |
55.5 |
6 |
0 |
29 |
0 |
3.97 |
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1 |
36.5 |
6.5 |
0 |
29 |
0 |
3.85 |
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1 |
36.3 |
6.5 |
0 |
48 |
0 |
3.96 |
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1 |
46.5 |
6.5 |
0 |
35 |
0 |
3.69 |
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1 |
35.9 |
6.5 |
0 |
40 |
0 |
3.76 |
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1 |
45.5 |
6.5 |
0 |
34 |
0 |
3.75 |
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1 |
43 |
6.5 |
0 |
38 |
0 |
3.75 |
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1 |
44.9 |
6.5 |
0 |
27 |
0 |
3.92 |
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1 |
59.5 |
8 |
0 |
26 |
0 |
3.76 |
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1 |
58.3 |
8 |
0 |
23 |
0 |
3.93 |
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1 |
56.5 |
8 |
0 |
35 |
0 |
3.7 |
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1 |
56.3 |
8 |
0 |
23 |
0 |
3.82 |
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1 |
43 |
6.5 |
0 |
40 |
0 |
3.78 |
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1 |
42.5 |
9 |
0 |
31 |
0 |
4 |
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1 |
29 |
7.5 |
0 |
31 |
0 |
3.92 |
|
1 |
35.3 |
8.5 |
0 |
39 |
0 |
3.79 |
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2 |
93.6 |
4 |
1 |
39 |
0 |
3.49 |
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2 |
90 |
4 |
1 |
43 |
0 |
3.57 |
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2 |
88 |
5.5 |
1 |
26 |
0 |
3.43 |
|
2 |
84.4 |
5 |
1 |
47 |
0 |
3.55 |
|
2 |
84 |
4.75 |
1 |
39 |
0 |
3.5 |
|
2 |
79.7 |
4.75 |
1 |
27 |
0 |
3.27 |
|
2 |
67.4 |
4.5 |
1 |
39 |
0 |
3.66 |
|
2 |
64.7 |
5 |
1 |
27 |
0 |
3.9 |
|
2 |
64.7 |
5.5 |
1 |
35 |
1 |
3.91 |
|
2 |
38.3 |
7 |
0 |
21 |
0 |
3.73 |
|
2 |
59.6 |
9.25 |
0 |
46 |
0 |
3.72 |
|
2 |
32 |
9 |
0 |
24 |
0 |
3.85 |
|
2 |
32.2 |
9 |
0 |
27 |
0 |
3.85 |
|
2 |
26.5 |
7 |
0 |
34 |
0 |
4.06 |
|
2 |
34.7 |
8.5 |
0 |
30 |
0 |
4.04 |
|
2 |
27.6 |
6 |
0 |
22 |
0 |
4 |
|
2 |
35.7 |
9 |
0 |
19 |
0 |
3.93 |
|
2 |
49.6 |
9 |
0 |
50 |
0 |
3.85 |
In: Statistics and Probability
A statistician for a drug company wishes to
determine whether short-term memory scores are affected by the type
of medication in hyperactive children. Sixty hyperactive children
(30 boys and 30 girls) were randomly assigned to receive either
Cylert or Ritalin (two kinds of amphetamines which are CNS
stimulants). Their short-term memory was tested on a 20-point scale
(where 0 = no memory and 20 = perfect memory).
Boys Cylert: 12, 10, 13, 10, 9, 12, 13, 10, 11,
12
Boys Placebo: 5, 6, 7, 6, 4, 5, 6, 7, 5, 7
Boys Ritalin: 3, 2, 5, 6, 1, 4, 2, 6, 1, 5
Girls Cylert: 5, 6, 2, 4, 3, 2, 4, 6, 2, 4
Girls Placebo: 4, 6, 7, 6, 5, 4, 5, 6, 7, 7
Girls Ritalin: 12, 9, 14, 13, 9, 12, 8, 15, 12, 11
solve for degrees of freedom, sum of squares and f values
In: Statistics and Probability
Using the table below, Classify the variables and the levels of measurement used? Explain your choice of the levels of measurement.
| Respondent # | Age | Sex | Ever Smoked | Grades | Marijuana Smoked |
| 1 | 18 | 1 | 2 | 2 | 1 |
| 2 | 17 | 1 | 2 | 2 | 1 |
| 3 | 16 | 1 | 2 | 1 | 1 |
| 4 | 15 | 1 | 1 | 3 | 1 |
| 5 | 17 | 1 | 2 | 3 | 1 |
| 6 | 15 | 1 | 2 | 1 | 1 |
| 7 | 14 | 1 | 1 | 1 | 1 |
| 8 | 15 | 1 | 1 | 1 | 1 |
| 9 | 15 | 1 | 1 | 2 | 1 |
| 10 | 15 | 1 | 1 | 2 | 1 |
In: Statistics and Probability