Answer:
0.90
Explanation:
The debt to equity ratio is a type of leverage ratio. It is also known as a risk ratio. It is calculated using the formula below.
Debt to Equity Ratio=Total Shareholders Equity/ Total Liabilities.
Shareholders' equity is comprised of retained earnings, share capital, income, and dividends.
Total liabilities are the current liabilities plus long term liabilities.
For Creatz Ltd, Total liabilities are $3500 + $7500= $11,000
Shareholders is $10,000
debt to equity ration
= $10,000/$11,000
=0.90
Answer:
Tha annual effective yield rate for the bond is:
= 6.2%
Explanation:
a) Data and Calculations:
Bond par value = $1,000
Annual coupon rate = 6%
Annual spot interest rates = 7%, 8%, and 9% for year 1, year 2, and year 3 respectively
Current value of bond = $970 ($1,000 * 99% * 99% * 99%)
Annual coupon payments = $60 * 3 = $180
Effective rate for the three years = $180/$970 * 100 = 18.6%
Annualized effective yield rate = 6.2% (18.6%/3)
OR
Annualized effective yield rate = (Annual coupon payments/Current value of bonds)
= 6.2% ($60/$970)
Answer:
It should accept the special order at the price of $36 as the total marginal cost will be $28.5 (27 variable cost + 1.15 shipping cost).
Explanation:
Special orders are accepted only if marginal revenue increases the marginal cost. Marginal cost is the total cost incurred to fulfill any order.
In the given scenario, since the Company already has adequate capacity and it will not incur any additional fixed cost, therefore the order can be accepted by taking variable cost in to consideration.
Marginal Revenue 36
Less: Marginal Cost
Variable Cost (27)
Shipping Cost <u> (1.15)</u>
Total Profit from Order <u> 7.85</u>
Answer: Geocentric managers
Explanation: Geocentric managers are the managers that accept the fact that every country have different culture and environment which can affect the business overall. Therefore, these managers use different techniques and procedures for different economies.
These are usually the managers of multinational corporations operating globally. These managers usually do not lack resources and can use the latest and best techniques for their operations.
In addition to prototyping, Powder Bed Fusion (PBF) AM processes have lately been more widely used to manufacture end-use parts. These changes lead to necessity of higher requirements to quality of a final product. Optimization of process parameters is one of the ways to achieve desired quality of a part.
In addition to prototyping, Powder Bed Fusion (PBF) AM processes have lately been more widely used to manufacture end-use parts. These changes lead to necessity of higher requirements to quality of a final product.
Optimization of process parameters is one of the ways to achieve desired quality of a part. Finite Element Method (FEM) and machine learning techniques are applied to evaluate and optimize AM process parameters. While FEM requires specific information, Powder Bed Fusion Machine Learning is based on big amounts of data. This paper provides a conceptual framework on combination of mathematical modelling and Machine Learning to avoid these issues.
Learn more about Powder Bed Fusion here
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