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- A household savings-account spreadsheet shows the following entries for the first day of each month: Month January February March April May June July August Additions Withdrawals Value 148,000 2,500 4,000 1,500 13,460 3,000 23,000 198,000 Required: Use the Excel function XIRR to calculate the dollar-weighted average return for this period. (Round your answer to 2 decimal places.) Dollar-weighted average Answer is complete but not entirely correct. 70.01%13. For the credit card account, assume one month between billing dates (with the appropriate number of days) and interest of 1.4% per month on the average daily balance. Find (a) the average daily balance, (b) the monthly finance charge, and (c) the account balance for the next billing. Previous Balance: $449.50 January 13 Billing Date January 15 Returns January 22 Clothes January 27 Bus tickets February 2 Payment February 6 Flowers $105.58 $122.54 $77.74 $120 $65.22 (a) The average daily balance is $ (Round to the nearest cent as needed.). (b) The finance charge is $ (Round to the nearest cent as needed.) (c) The account balance for the next billing is $ (Round to the nearest cent as needed.) C O a IS ry ry av to2. A credit card statement showed these transactions during October.October 1 Previous balance $257.28October 12 Purchases $79.55October 29 Payment $55.00The credit card has an interest rate of 4.5% on the average daily balance. Findthe average daily balance, the finance charge for the month, and the newbalance on November 1. [Hint: Remember that October has 31 days.]
- In June, Widgets, Inc. makes on account sales to Customs Motors of $800 and receives a payment of $500 from them. How would this affect the Accounts Receivable control account? O A. The AR total would be decreased by $300. O B. The AR total would be decreased by $500. O C. The AR total would be increased by $800. O D. The AR total would be increased by $300.Lotus fabrics wants to forecast its accounts receivable for the year 2021 with the following annual information. Also state two advantages of forecasting of accounts receivables for the entity. Receivable days assumption = 60 days Payable days assumption = 72 days Forecasted revenue = 325,000 Forecasted cost of goods sold = 180,250 Choices: 51,195 53,425 49,800 41,705Oman company had $180,000 sales on credit last year. The accounts receivable balance was $14,000 What is the average collection period? Select one: O 20.2 days. O 36.5 days. O 56.78 days O 28.3 days ENG 07:59 3238page=11# 38°C Sunny INTL 25/07/2021
- SimpleFlight Inc has a policy of keeping accounts receivables at 47 days of sales. In 2019 they received $95M in revenue. In 2020 they expect to receive $100 M in revenues. What do you forecast their account receivables to be in 2020? (enter answer in $M, with two decimal points precision)7. Using the following table containing the dates of purchases and payments to determine the average daily balance of a credit card at the end of the billing cycle, assuming 30 days in the month (Round to the nearest cent). Days Purchase/Payment Dollar Amount Unpaid Balance Раyment $1,500 $120 3 $670 $375 $85 10 Purchase 22 Purchase 26 PaymentProblem #1. You have a Visa credit card account with a 26.49% annual percentage rate calculated on the average daily balance. The billing date is the first day of each month, and the billing cycle is the number of days in that month. Your credit card balance on April 1 was $552. On April 10th you made a $119 purchase. You made another purchase, a $25 gift card, on April 24th. You made a $150 payment on April 29th. Show your work for all parts of the problem. (a) What is the average daily balance for April? (b) What is your finance charge on the account as of May 1st? (c) What is your new credit card balance?
- Fitbands estimated sales are: What are the balances in accounts receivable for January, February, and March if 65% of sales is collected in the month of sale, 25% is collected the month after the sale, and 10% is second month after the sale?Consider again the example introduced in Section 4.5 of a credit card company that has a database of information provided by its customers when the customers apply for credit cards. An analyst has created a multiple regression model for which the dependent variable in the model is credit card charges accrued by a customer in the data set over the past year (y), and the independent variables are the customers annual household income (x1), number of members of the household (x2), and number of years of posthigh school education (x3). Figure 4.23 provides Excel output for a multiple regression model estimated using a data set the company created. a. Estimate the corresponding simple linear regression with the customers annual household income as the independent variable and credit card charges accrued by a customer over the past year as the dependent variable. Interpret the estimated relationship between the customers annual household income and credit card charges accrued over the past year. How much variation in credit card charges accrued by a customer over the past year does this simple linear regression model explain? b. Estimate the corresponding simple linear regression with the number of members in the customers household as the independent variable and credit card charges accrued by a customer over the past year as the dependent variable. Interpret the estimated relationship between the number of members in the customers household and credit card charges accrued over the past year. How much variation in credit card charges accrued by a customer over the past year does this simple linear regression model explain? c. Estimate the corresponding simple linear regression with the customers number of years of posthigh school education as the independent variable and credit card charges accrued by a customer over the past year as the dependent variable. Interpret the estimated relationship between the customers number of years of posthigh school education and credit card charges accrued over the past year. How much variation in credit card charges accrued by a customer over the past year does this simple linear regression model explain? d. Recall the multiple regression in Figure 4.23 with credit card charges accrued by a customer over the past year as the dependent variable and customers annual household income (x1), number of members of the household (x2), and number of years of posthigh school education (x3) as the independent variables. Do the estimated slopes differ substantially from the corresponding slopes that were estimated using simple linear regression in parts a, b, and c? What does this tell you about multicollinearity in the multiple regression model in Figure 4.23? e. Add the coefficients of determination for the simple linear regression in parts a, b, and c, and compare the result to the coefficient of determination for the multiple regression model in Figure 4.23. What does this tell you about multicollinearity in the multiple regression model in Figure 4.23? f. Add age, a dummy variable for gender, and a dummy variable for whether a customer has exceeded his or her credit limit in the past 12 months as independent variables to the multiple regression model in Figure 4.23. Code the dummy variable for gender as 1 if the customers gender is female and 0 if male, and code the dummy variable for whether a customer has exceeded his or her credit limit in the past 12 months as 1 if the customer has exceeded his or her credit limit in the past 12 months and 0 otherwise. Do these variables substantially improve the fit of your model?Sheridan Company provided the following information for the month of October: Beginning cash balance=$34700 Cash receipts=459600 Cas disbursements=486000 Sheridan's policy is to keep a minimum end-of-the-month cash balance of $29300. How much will Sheridan need to borrow during October? $21000 $26400 $8300 $0
