Answer: The value of the bond will decrease
Explanation:
The Interest rate has a negative inverse relationship with the value of a bond
. When the interest rate increases the value of a bond decreases and when interest rate decreases the bond value increases. Bonds with low coupon rates tend to be more sensitive to interest rate changes this is known has coupon effect.
Bonds with long time frame (long term bonds), they also tend to be are more sensitive to changes in the interest rate this is known has the maturity effect. Therefore a change in the interest rate will cause a huge change in the value of a Bond with low coupon rate and long time period.
The Bond is a 20 year Bonds which qualifies it to be a long term bond and the coupon Rate is 7%, with these facts and knowing that long term bonds are more sensitive to interest rate changes we can conclude that the sudden increase of the interest rate to 15% will cause a huge decrease in the value of the bond
Answer:
Consider the following explanation
Explanation:
Option A, B and D are correct, It will reduce the profit of the company who is loosing the monopoly, and fewer drugs will be invented in the market and firms are loosing the monopoly, and the sunk cost will increase.
Answer:
total product costs = $101750
Explanation:
given data
overhead costs = $ 100
Direct materials of $41,000
direct manufacturing labor = 450
per hour = $35
markup rate = 30 %
solution
we get here total product costs that is express as
total product costs = Direct materials + DML + MOH ..........1
total product costs = $41,000 + ( 450 × $35 ) + ( 450 × $100 )
total product costs = $41,000 + $15750 + $45000
total product costs = $101750
Answer: parametric
Explanation:
As a general rule of thumb, when the dependent variable’s level of measurement is nominal (categorical) or ordinal, then a non-parametric test should be selected. When the dependent variable is measured on a continuous scale, then a parametric test should typically be selected. Fortunately, the most frequently used parametric analyses have non-parametric counterparts. This can be useful when the assumptions of a parametric test are violated because you can choose the non-parametric alternative as a backup analysis.
