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Question: Branch banks must keep enough money on

Branch banks must keep enough money on hand to satisfy customers’ cash demands. Suppose that the daily demand for cash at a branch of University Bank follows a lognormal distribution with means and standard deviation summarized as follows (in $1,000s):
Branch banks must keep enough money on hand to satisfy customers’ cash demands. Suppose that the daily demand for cash at a branch of University Bank follows a lognormal distribution with means and standard deviation summarized as follows (in $1,000s):

An armored truck delivers cash to this bank once a week. The manager of the bank can order any amount of cash she desires for this delivery. Of course, running out of cash in any week is very undesirable as customers of the bank expect to be able to withdraw their deposits on demand. Of course, keeping excessive cash reserves would guard against this happenstance. However, cash is a non-interest earning asset, so there is an opportunity cost for holding excess cash reserves. 
a. Suppose the bank manager follows the practice of ordering enough cash to start each week with a balance of $825,000. Create a spreadsheet model to track the daily cash balance throughout the week.
b. What is the probability that the bank will run out of money at some point during the week?
c. What amount of money is needed at the start each week to ensure there is at most a 0.10% chance of running out of money?

An armored truck delivers cash to this bank once a week. The manager of the bank can order any amount of cash she desires for this delivery. Of course, running out of cash in any week is very undesirable as customers of the bank expect to be able to withdraw their deposits on demand. Of course, keeping excessive cash reserves would guard against this happenstance. However, cash is a non-interest earning asset, so there is an opportunity cost for holding excess cash reserves. a. Suppose the bank manager follows the practice of ordering enough cash to start each week with a balance of $825,000. Create a spreadsheet model to track the daily cash balance throughout the week. b. What is the probability that the bank will run out of money at some point during the week? c. What amount of money is needed at the start each week to ensure there is at most a 0.10% chance of running out of money?


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> Under what condition(s) is it appropriate to use simulation to analyze a model? That is, what characteristics should a model possess in order for simulation to be used?

> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method versus the

> Create an exponential smoothing model that minimizes the MSE for the data set. Use Solver to determine the optimal value of a. a. What is the optimal value of a? b. Prepare a line graph comparing the exponential smoothing predictions against the origi

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> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?

> Use Holt-Winter’s multiplicative method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the pr

> Mac Brown knew something had to change. As the new Vice President of Sales & Marketing for the PB Chemical Company, Mac understood that when you sell a commodity product, where there is minimal difference between the quality and price, customer service a

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> Use the multiplicative seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against

> Use the additive seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against the or

> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?

> Use Holt-Winter’s multiplicative method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the pr

> Use Holt-Winter’s additive method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the predicti

> Use the multiplicative seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against

> Use the additive seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against the or

> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?

> A used-car broker needs to transport his inventory of cars from locations 1 and 2 in Figure 5.39 to used-car auctions being held at locations 4 and 5. The costs of transporting cars along each of the routes are indicated on the arcs. The trucks used to c

> Use regression to estimate the parameters of a 6th order polynomial model for this data. That is, estimate the least squares estimates for the parameters in the following estimated regression equation: a. What are the optimal values of b0, b1, â

> Compute the two-period and four-period moving average predictions for the data set. a. Prepare a line graph comparing the moving average predictions against the original data. b. Do the moving averages tend to overestimate or underestimate the actual da

> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to estimate the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method against the

> Create a Double Moving Average model (with k 5 4) for the data set. a. Prepare a line graph comparing the Double Moving Average predictions against the original data. b. What are the forecasts for the next 2 months using this technique?

> Create an exponential smoothing model that minimizes the MSE for the data set. Use Solver to estimate the optimal value of a. a. What is the optimal value of a? b. Prepare a line graph comparing the exponential smoothing predictions against the original

> Use Solver to determine the weights for a four-period weighted moving average on the data set that minimizes the MSE. a. What are the optimal values for the weights? b. Prepare a line graph comparing the weighted moving average predictions against the or

> Compute the two-period and four-period moving average predictions for the data set. a. Prepare a line graph comparing the moving average predictions against the original data. b. Compute the MSE for each of the two moving averages. Which appears to provi

> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?

> Use regression analysis to answer the following questions. a. Fit a linear trend model to the data set. What is the estimated regression function? b. Interpret the R2 value for your model. c. Prepare a line graph comparing the linear trend predictions ag

> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to estimate the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method against the

> In the wake of the Enron scandal two public accounting firms, Oscar Anderson (OA) and TriceMilkhouse -Loopers (TML), merged (forming OATML) and are reviewing their methods for detecting management fraud during audits. The two firms had each developed the

> Create a Double Moving Average model (with k 5 4) for the data set. a. Prepare a line graph comparing the Double Moving Average predictions against the original data. b. What are the forecasts for the next 4 months using this technique?

> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?

> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?

> Use Holt-Winter’s multiplicative method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the pr

> Use Holt-Winter’s additive method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the predicti

> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method against th

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> Use regression analysis to fit a linear trend model to the data set. a. What is the estimated regression function? b. Interpret the R2 value for your model. c. Prepare a line graph comparing the linear trend predictions against the original data. d. Wha

> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to estimate the optimal values of a and b. a. What are the optimal values of a and b? b. Are these values surprising? Why or why not? Questions 35 through 39 refer to

> Create an exponential smoothing model that minimizes the MSE for the data set. Use Solver to estimate the optimal value of a. a. What is the optimal value of a? b. Prepare a line graph comparing the exponential smoothing predictions against the original

> A company has three warehouses that supply four stores with a given product. Each warehouse has 30 units of the product. Stores 1, 2, 3, and 4 require 20, 25, 30, and 35 units of the product, respectively. The per unit shipping costs from each warehouse

> Use Solver to determine the weights for a four-period weighted moving average on the data set that minimizes the MSE. a. What are the optimal values for the weights? b. Prepare a line graph comparing the weighted moving average predictions against the or

> Compute the two-period and four-period moving average predictions for the data set. a. Prepare a line graph comparing the moving average predictions against the original data. b. Compute the MSE for each of the two moving averages. Which appears to prov

> Prepare a line graph of these data. Do the data appear to be stationary or nonstationary?

> Each month, Joe’s Auto Parts uses exponential smoothing (with a 5 0.25) to predict the number of cans of brake fluid that will be sold during the next month. In June, Joe forecast that he would sell 37 cans of brake fluid during July. Joe actually sold 4

> Use regression analysis to fit an additive seasonal model with linear trend to the data set. a. What is the estimated regression function? b. Interpret the R2 value for your model. c. Interpret the parameter estimates corresponding to the indicator varia

> Use Holt-Winter’s multiplicative method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the pr

> Use Holt-Winter’s additive method to create a seasonal model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a, b, and g. a. What are the optimal values of a, b, and g? b. Prepare a line graph comparing the predicti

> Use Holt’s method to create a model that minimizes the MSE for the data set. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from Holt’s method against th

> Use the multiplicative seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against

> Use the additive seasonal technique for stationary data to model the data. Use Solver to determine the optimal values of a and b. a. What are the optimal values of a and b? b. Prepare a line graph comparing the predictions from this method against the or

> Nolan Banks is an auditor for the Public Service Commission for the state of Georgia. The Public Service Commission is a government agency responsible for ensuring that utility companies throughout the state manage their operations efficiently so that th

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