Answer:
B - $13,556.82
Explanation:
Amount to be invested is equal to the present value of future inflows
Present value = future value/(1+Interest rate)^Number of years
The actual amount at the end of the first year should be $3000 if there is an answer in the options
The amount at the end of the second year is $4000
The amount at the end of the third, fourth and fifth year is $5000
Hence, amount to be invested = 3000/(1.17) + 4000/(1.17)^2 + 5000/(1.17)^3 + 5000/(1.17)^4 + 5000/(1.17)^5
= $13,556.82
Hence, the answer is $13,556.82
Answer:
$14,887.5
Explanation:
Carrying Value of the bond is the net of Face value and any amortised discount on the bond.
Face Value of the bond = $19,000
Issuance Value = $14,300
Discount Value = $19,000 - $14,300 = $4,700
This Discount will be amortized over the bond's life until the maturity on straight line basis.
Amortization in each period = $4,700 / (8x2) = $293.75 semiannually
Until December 31, 2017 two payment have been made and $587.5 is amortized in the two semiannual periods.
Un-amortized Discount = $4,700 - $587.5 = $4,112.5
Carrying value of the bond = Face value - Un-amortized Discount = $19,000 - $4,112.5 = $14,887.5
Answer:
the value of the quick ratio is 1.11 times
Explanation:
The computation of the value of the quick ratio is shown below:
Quick Ratio = Total Quick Assets ÷ Total current liabilities
= [Cash + Accounts Receivables] ÷ Accounts Payable
= [$145 + $99] ÷ $219
= $244 ÷ $219
= 1.11 Times
Hence, the value of the quick ratio is 1.11 times
Answer:
6.75%
Explanation:
Data provided in the question:
Beta of the stock = 1.12
Expected return = 10.8% = 0.108
Return of risk free asset = 2.7% = 0.027
Now,
Since it is equally invested in two assets
Therefore,
both will have equal weight = 
= 0.5
Thus,
Expected return on a portfolio = ∑(Weight × Return)
= [ 0.5 × 10.8% ] + [ 0.5 × 2.7% ]
= 5.4% + 1.35%
= 6.75%
Answer:
decision support system.
Explanation:
A decision support system is an intelligent system that automates the organizational decision process by collecting data regarding organizational processes and logical and quantitative learning of factors that directly impact a business.
It is then configured as a very effective tool to reduce the risk inherent in the decision-making process of an expert who does not have much experience to make a decision based on their own knowledge.
