Question

In: Accounting

Quarter Year 1 Year 2 Year 3 Year 4 Year 5 1 20 37 75 92...

Quarter

Year 1

Year 2

Year 3

Year 4

Year 5

1

20

37

75

92

176

2

100

136

155

202

282

3

175

245

326

384

445

4

13

26

48

82

181

Question 3

Again ignore any trend or seasonality in the data.  Suppose the company uses exponential smoothing to make forecasts.  

  1. What are the forecasts for periods Q2 Year 1 through Q4 Year 5 assuming alpha = 0.3. Assume that the forecast for Q1 Year 1 was 25 units.
  2. What are the forecasts for periods Q2 Year 1 through Q4 Year 5 assuming alpha = 0.8.  Assume that the forecast for Q2 Year 1 was 25 units.
  3. Compare the accuracies of the forecasts in (a) and (b) using Mean Absolute Percent Error.  Which value of alpha gives us the better forecasts?

Question 4

Now make adjustments for trend and seasonality.

  1. Quantify the trend in the time series.  What does the trend equation tell you?  
  2. Quantify the seasonality in the time series by calculating seasonality indexes.  What do these indexes tell you?
  3. Using the trend and the seasonality information from (a) and (b) make forecasts from Q1 Year 1 through Q4 Year 5.  
  4. Use MAPE to calculate the accuracy of your forecasts.

Question 5

  1. Compare the preferred method in Question 2, the preferred method in Question 3, and the method in Question 4.  Which one would you choose on the basis of MAPE?
  2. Using the method in Question 4 make forecasts for the 4 quarters of Year 6.

Solutions

Expert Solution

please post the other questions separately.

thanks

ekkarill92 answered 2 years ago
Next > < Previous

Related Solutions

  Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1 2   Budgeted unit sales...
  Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1 2   Budgeted unit sales 50,000 65,000 115,000 70,000 80,000 90,000   Selling price per unit $7 per unit             1 Chapter 7: Applying Excel 2 3 Data Year 2 Quarter Year 3 Quarter 4 1 2 3 4 1 2 5 Budgeted unit sales 50,000 65,000 115,000 70,000 80,000 90,000 6 7 � Selling price per unit $8 per unit 8 � Accounts receivable, beginning balance...
Chapter 9: Applying Excel Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1...
Chapter 9: Applying Excel Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1 2 Budgeted unit sales 40,000 60,000 100,000 50,000 70,000 80,000 • Selling price per unit $8 per unit • Accounts receivable, beginning balance $65,000 • Sales collected in the quarter sales are made 75% • Sales collected in the quarter after sales are made 25% • Desired ending finished goods inventory is 30% of the budgeted unit sales of the next quarter • Finished...
Chapter 8: Applying Excel Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1...
Chapter 8: Applying Excel Data Year 2 Quarter Year 3 Quarter 1 2 3 4 1 2 Budgeted unit sales        40,000         60,000      100,000      50,000         70,000         80,000 • Selling price per unit $8 per unit • Accounts receivable, beginning balance $65,000 • Sales collected in the quarter sales are made 75% • Sales collected in the quarter after sales are made 25% • Desired ending finished goods inventory is 30% of the budgeted unit sales...
Quarter Year 1 Year 2 Year 3 1 5 8 10 2 1 3 7 3...
Quarter Year 1 Year 2 Year 3 1 5 8 10 2 1 3 7 3 3 6 8 4 7 10 12 (A) What type of pattern exists in the data? a. Positive trend, no seasonality b. Horizontal trend, no seasonality c. Vertical trend, no seasonality d. Positive tend, with seasonality e. Horizontal trend, with seasonality f. Vertical trend, with seasonality (B) Use a multiple regression model with dummy variables as follows to develop an equation to account for...
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 2 5...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 2 5 7 2 0 2 6 3 5 8 10 4 5 8 10 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 2 5...
Consider the following time series data. Quarter Year 1 Year 2 Year 3 1 2 5 7 2 0 2 6 3 5 8 10 4 5 8 10 (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...
The 1-year, 2-year, 3-year and 4-year zero rates are 2%, 3%, 4% and 5% per annum...
The 1-year, 2-year, 3-year and 4-year zero rates are 2%, 3%, 4% and 5% per annum (APR) with quarterly compounding/payment. a) What are the corresponding per annum zero rates with continuous compounding? b) What is today’s forward rate for an investment initiated one year from today and maturing 3 years from today?  (Give your answer per annum with continuous compounding)? c) What is today’s forward rate for a one-year investment initiated three years from today?  (Give your answer per annum with continuous...
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...
ADVERTISEMENT
Subjects
ADVERTISEMENT
Latest Questions
ADVERTISEMENT