1f. Compare 1a and 1d, and 1b and 1e, explain why the percentage in 1a is much larger than that in 1d and why the value in 1b is much smaller than that in 1e?

1. Suppose that for Edwardsville High School, distances between students’ homes and the high school observe normal distribution with the average distance being 4.76 miles and the standard deviation being 1.74 miles. Express distances and z scores to two decimal places. Write the formula to be used before each calculation.

1a. What percentage of students in the high school live farther than 6.78 miles from the school?

1b. A survey shows that 8% of the students who live closest to the school choose to walk to school. What is the maximum walking distance of these 8% of students? In other words, what is the distance below which these 8% of students live from the school?

1c. Suppose that the school district’s policy allows students living beyond 4.50 miles from the school to take school buses to go to school. There are 3,567 students who enroll in the fall semester, 2006. How many students in the high school are not eligible to take school buses?

1d. Suppose all samples of size 12 are taken. What percentage of sample means has a value larger than 6.78 miles?

1e. Below what value are 8% of sample means of size 12?

Justin Owens is an analyst for an equity mutual fund that invests in British stocks. At the beginning of 2008, Owens is examining domestic stocks for possible inclusion in the fund. One of the stocks that he is analyzing is British Sky Broadcasting Group (London Stock Exchange: BSY). The stock has paid dividends per share of £9, £12.20, and £15.50 at the end of 2005, 2006, and 2007, respectively. The consensus forecast by analysts is that the stock will pay a dividend per share of £18.66 at the end of 2008 (based on 19 analysts) and £20.20 at the end of 2009 (based on 17 analysts). Owens has estimated that the required rate of return on the stock is 11 percent.

A. Compare the compound annual growth rate in dividends from 2005 to 2007 inclusive (i.e., from a beginning level of £9 to an ending level of £15.50) with the consensus predicted compound annual growth rate in dividends from 2007 to 2009, inclusive.

B. Owens believes that BSY has matured such that the dividend growth rate will be constant going forward at half the consensus compound annual growth rate from 2007 to 2009, inclusive, computed in Part A. Using the growth rate forecast of Owens as the constant growth rate from 2007 onwards, estimate the value of the stock as of the end of 2007 given an 11 percent required rate of return on equity.

C. State the relationship between estimated value and r and estimated value and g

Problem

a) Zoey Enterprises manufactures solar engines for helicopters. Given the fuel savings available, new orders for 125 units have been made by customers requesting credit. The variable cost is $11,400 per unit, and the credit price is $13,000 each. Credit is extended for one period. The required return is 1.9 percent per period. If Zoey Enterprises extends credit, it expects that 30 percent of the customers will be repeat customers and place the same order every period forever, and the remaining customers will place one-time orders. Should credit be extended?

b) Now, assume that the probability of default is 15 percent. Should the orders be filled now? Assume the number of repeat customers is affected by the defaults. In other words, 30 percent of the customers who do not default are expected to be repeat customers.

(Please provide all the equation and step by step or Excel.xml in google drive )

(Please don't copy from another places, the answer will upload to Turnitin)

S- You note during the review of sales, that a rebate was issued for the 2018 Income Tax Game to encourage sales. 24,500 games were sold. Customers can mail in their receipt and receive a $1 rebate per game. It is estimated that 48% of customers will send in the rebate. The rebate expires on January 31, 2019. To date, 12,800 rebates have been refunded. Without any direction, the accounting clerk debited Miscellaneous Selling Expense and credited Cash for the $12,800. The management of Czar would prefer to have this type of expense in a separate account (Rebate Expense) so they can properly analyze for future ideas.

T- Czar has a straight tax rate of 30%. Income tax expense is Net Income before taxes times 30%. (Hint: Prepare the Income Statement up to Net Income before Taxes and then record this adjusting journal entry.)

Read and study all the material and the Case Study: American Investment Management Services

Read and study all the material and the Case Study: American Investment Management Services in Week 9 before beginning the final exam. “Exhibits” are found in that Case. Then answer the following questions about the Case Study: American Investment Management Services:

#3. Noting that excess capacity is charged back to active accounts, if AIMS scaled back to 3,000,000 active households and planned only a 10% excess capacity reserve for future growth, a large proportion of cost could be eliminated. Estimate how much of total cost for 1999 could be eliminated, based on facts presented in the case.

American Investment Management Services (AIMS)

Kim Davis, Executive Vice President ofAIMS, sat in her 43rdfloor corner office overlooking the Manhattan skyline, reflecting on the challenges facing the investment services business in 2000. Profits had come easily during the longest economic expansion ofthe century. However, signs ofweakness in the economy,

financial market volatility, intense competition for high net worth customers, and the proliferationofcomplex technology-dependent products were all making her life much more complicated AIMS had recently invested in new analytic tools to help think more strategically about its operations and customers. Kim wondered how much the new analytic approach would really impact business decision-making. Was intensive customer segment analysis a real opportunity orjust another "shot in the dark?"

AIMS is one of the larger investment services providers in the U.S., approaching $500 billion in assets in 2000. Ofthis total, a little more than halfwas in mutual funds and the balance in brokerage accounts. This case deals with customer profitability assessment for AIMS' 3.9 million households, up from 1.8 million in just four years. Until I999, AIMS had no system for measuring the profitability of any specific customer.

SEGMENT A TION

AIMS spanned two separate and very different product lines (mutual funds and full-line brokerage services), but that was only one element of the complexity it faced. In addition to this product complexity, it also spanned three distinct "distribution channels" (Call Centers, Full Service Branches, and E-business), and a complex array of customers with diverse asset holdings, trading patterns, investment objectives and service requirements. There was no particularly sharp focus on what kind of households to add. The basic idea was high wealth, but that was not pushed exclusively at all. Basically, AIMS wanted to do business with the same 2 million American households (over $1 million in invested assets) that 2 I other major financial services firms were pursuing.

In I999, AIMS introduced segment analysis, starting with a four-way segmentation that mixed three different dimensions: asset holdings, trading activity and age (as a proxy for investment objectives). The first segment was any household with more than $500,000 in assets under management at AIMS ("High Net Worth," or "HNW''). Failing this test, the second segment was households trading more than 36 times in I998 ("Active Traders," or "AT"). Failing this test as well, the third segment was households where the principal customer was already retirement age (60 years old). Finally, customers failing all three of these tests comprised the fourth segment-all other, termed "Core" customers. "Core," with more than 70% of all households, was the largest segment.

The primary role of any segmentation is to facilitate analysis leading to management actions tailored to the specific needs of defined customer subgroups. No particular segmentation is ever beyond dispute. Whatever approach is chosen necessarily emphasizes some distinctions and de­ emphasizes others. But, the AIMS segmentation was particularly contentious on two grounds: I) it segmented current customers rather than a market. It is as if Procter & Gamble were to segment the detergent market based on how many pounds of Tide are purchased; 2) the sequence specific classification scheme meant that labels could be misleading: for example, the segment Active Trader applies only to households which are not each HNW. And, "Retiree" applied only to households which were not each HNW or AT.

2

AIMS

FINANCIAL RESULTS

As shown in Exhibit I, AIMS did quite well in 1999. Net margin afteJ tax was about $156 million on an underlying equity investment of about $625 million. But, 1999 represented the height of the prolonged bull market. The year 2000 was projected to be much less bullish, and most Wall Street observers envisioned the next few years to be much less rosy than the previous ten.

Even in 1999, performance was not consistent across all the customer segments. Pre-tax margin ranged from a high of48% for HNW, to only 6% for Retirees and minus 4% for Core.

The revenue breakdown across segments in Exhibit I is based on actual identification with individual customers. The expense breakdown starts with an annual "unit cost" study that uses "Activity-Based Costing" (ABC) principles. The study first assigned all operating costs from the General Ledger to specific processes or "activities." Then, the activity costs were divided by throughput measures for each activity, to create "cost per unit of activity" for each sub-stage of each process. This process is illustrated in Exhibit 2 for estimated costs for 2000. Individual unit costs were then multiplied by throughput totals for each segment and aggregated to provide total expenses per segment as shown in Exhibit I, a report format which was new at AIMS in 1999.

THE, CUSTOMER/PRODUCT PROFITABILITY INITIA TIVE

As a management report, Exhibit I was too aggregated to identify actionable issues. In 2000, AIMS undertook a project to take customer/product profitability reporting down to the individual household level to provide more useable, timely, and integrated information for decision­ making. The new system combined unit costs from the annual ABC study with current actual household activity and attributes (e.g., products held, services used, number of trades, number of rep-assisted phone calls) extracted from the Marketing Database to generate profitability by household. The data then were exported into easily queried online analytical processing (OLAP) "cubes." OLAP cubes allow profitability analysis of the intersections among customer attributes, product/service attributes, and channels ofdistribution.

Exhibit 2, which illustrates the first step in this n.ew .system (unit costs across processes), is highly s1mpltfied for purposes of the case. As shown, a "driver" was chosen to proxy the activity in each process­ telephone calls as the driver of activity in the Call Center, for example. Next, a count was made of the total estimated units of the activity for 2000 for each driver­ 7~.l million calls for the Call Center, for example. Fmally, the total cost for the process was divided by the total activity count to calculate cost per unit of activity for that process.

Some ofthe assignments ofcosts to activities and some of the activity measures are "soft," but the activity costs tagged to individual households based on actual household activity are conceptually plausible and at least directionally correct. Similarly, product-specific and service-specific revenues are driven down to a household level. Household profitability calculations are thus based on actual asset holdings, fee-based services consumed and activity usage. The actual system in use allows for 11 categories o f customer revenue and 70 categories o f process cost.

Conceptually, Exhibit 2 represents "long-run average cost" for each activity. It does not attempt to portray marginal or incremental cost because it is not intended for use in short-run cost-volume-profit (CVP) analyses. Since very little cost at AIMS is variable with short-run volume fluctuations anyway, short-run CVP analysis is really just based on revenue changes.

Almost all costs are "step costs" which go up (or down), in chunks as capacity is added to (or deleted from) the system. In a business as fast-growing as AIMS has been in recent years, capacity is typically being added every year in many places across the process value chain ahead o f usage requirements. Thus, there is almost always excess capacity in the system. And, the extent of excess capacity varies across processes, depending on where growth has been fastest and where recent expansions have been made. The analysis in Exhibit 2 divides current cost by current throughput to calculate unit cost. The analysis thus charges any excess capacity to the current users of the process. This is debatable, conceptually, but is not recognized as a practical problem at AIMS.

The expense base grew substantially faster than throughput volume between 1995 and 1999 in anticipation of even greater future growth. In 1995, ~here was about 10% excess capacity (on average) in the operating expense base. Capacity grew at a compound rate of about 26% from 1995 to 1999, versus households growth at about 21%. As a result, excess capacity in 1999 was a much larger percentage of the expense base, across branches, the call center, on-line activity, transactions processing and account maintenance activity. Kim wondered how much of operating capacity was devoted to unprofitable customers.

THE SEGMENTATION REFINEMENT

INITIATIVE

Another new initiative in 2000 to enhance customer profitability analysis involved further refining the segmentation. The goal was to better identify customer clusters that would be responsive to specific managerial actions. Kim Davis was chairing the task force coordinati~g this effort. The primary four-way segmentation was expanded to 11 categories as shown below.

AIMS

3

High Net Worth(> $500,000 ofassets under management) I. (16,000 Households)> $2,000,000 in assets under

management
2. (141,000 Households) - $500,000 to $2,000,000

Active Traders(> 36 trades per year)
3. ( 9,000 Households) - more than 200 trades 4. (12,000 Households) - 60 to 200 trades
5. (19,000 Households)- 36 to 60 trades

Retirees
6. (262,000 Households)- $100,000 to $500,000 in

assets under management
7. (607,000 Households)< $100,000

Core
8. (426,000 Households)- $100,000 to $500,000 in

assets under management
9. (1,762,000 Households) - "Boomers" (40 to 59 years

o f age)
10. (434,000 Households)- "Young Professionals"

(under 40 years o f age)
11. (192,000 Households) - All Other, including

employees

CUSTOMER PROFITABILITY ANAL YSIS

As noted earlier, although the company was very profitable in 1999 as the ten-year bull market continued, the senior management group was concerned about the tremendous range o f profitability across customer segments and about the potential for substantial profit erosion when overall markets slowed down, as was widely anticipated over the next few years. Kim challenged the management team to analyze customer mix carefully to identify problem areas and potential corrective actions.

One new management report now being produced each quarter showed income statements for each of he eleven segments broken down by deciles, starting with the most profitable 10% of households and ending with the least profitable 10%. Not surprisingly, the tenth decile in all eleven segments was unprofitable, even before considering any allocation of marketing expenses directed at acquisition of new customers. It was generally agreed that profitability analysis of current households should exclude all expenditures directly related to new households-either "prospecting" expenses in marketing

or new account set-up expenses in the back office. When the segmentation was ignored, 75% of the bottom decile customers were in the Core segment and 80% had less than $100,000 in assets under management.

The wide range ofprofitability across deciles and segments is summarized in Exhibit 3 for 1999. The aggregate loss on all unprofitable households in 1999 was $248 million. Obviously, unprofitable households are an important concern for AIMS. Kim Davis wanted to identify the roots ofthe problem as clearly as possible.

At a casual level of analysis, an unprofitable household suggests one oftwo responses:

• "Fire" them, because AIMS does not want customers on whom it loses money.

• "Do nothing," because there is usually some compensating business reason for keeping .them-the "loss leader" concept. It is possible to construct a long list of reasons to choose to

keep any one currently unprofitable household. At a deeper level of analysis, an unprofitable household suggests that AIMS change its behavior (or the household's behavior) to convert the household to profitable status. In general, there are three ways to convert unprofitable households into profitable ones:

• Raise prices.
• Substitute less expensive for more expensive

services.
• Reduce the cost of delivering some (or all)

services.
Exhibit 4 presents activity profiles o f six

individual tenth decile households chosen to highlight management problems across different segments. Each household presented in Exhibit 4 proxies for thousands of households with the same general profile. The activity profile of the "average" account is also shown for comparison.

Preliminary discussions about "improving customer profitability" focused on the 2000 forecast for representative "problem households" such as those depicted in Exhibit 4. Management wanted to consider both revenue enhancement proposals and service containment proposals.

Potential Account Profitability Enhancement Programs

l)

2) 3)

4)

5) 6) 7)

Charge $15. per rep-assisted call, over 50 calls per year (22,000 l0th Decile Households generate more than 50 calls/year)
Charge $.02 per quote over 100 per transaction Charge a minimum annual fee on brokerage assets or mutual fund assets of $200 or 20 BP, whichever is greater (a fee for the right to trade, even when trading is very inactive)

For customers who generate less than $560. revenue per year (the average), limit access to branches and customer representatives:

charge $100. for branch consultations
- route all incoming calls to the automated

answering service, bypassing account reps Charge $.75 for automated calls over 300 per year.

Charge $1.25 for on-line visits over 10 per transaction.
Set a minimum balance for all new accounts of $50,000 of assets invested (perhaps exempt persons under 35 years old), and a minimum balance of $75,000 of assets invested for persons over 45 years old.

4 AIMS

(Research indicated that AIMS only had about 40% of the invested assets of its custo)llers, on average. The other 60% was invested elsewhere.)

Each ofthese proposals was modeled on charges levied by one or another of AIMS' major competitors, including Charles Squibb, Morton Staley Dan Withers, Merry Lurch, or United Express. Other competitors such as Towncorp Bank or County Road Financial Services approached this problem by limiting their offer of investment advisory services to customers with more than $1 million in invested assets. A good question was why AIMS bothered at all with low net worth customers when so many of them were unprofitable now and likely to remain so.

Questions:

Which are the potential sources of “hidden profitability” that you detect for AIMS?

Why is the firm facing this situation? How can this be prevented towards the future?

What is your opinion of the process the firm followed to assess the customer profitability?

How would you use this information to improve your business?

Please answer questions 6 - 10. Thank you.

6. What are the three major market indexes?

7. What is the difference between options and future contracts?

8. What determines the option price?

9. What is the difference between primary and secondary market for security sales?

10. What are market order, limit order, and stop order? Explain each one.

Three vectors are given as A=<3.5, -5.3, 1.1> B=<4.5, 7.5, -7> C=<-3.9, 4.8, -6>

a) Determine the angle between A and B.

b) Determine the angle between A and C

c) Compute the dot product of B and C

d) Determine the size of the area associated with vectors B and C.

e) Determine the quantity (B (dot)(A(cross)C))

Three deer, A, B, and C, are grazing in a field. Deer B is located 61.6 m from deer A at an angle of 52.2 ° north of west. Deer C is located 79.4 ° north of east relative to deer A. The distance between deer B and C is 91.4 m. What is the distance between deer A and C? (Hint: Consider the laws of sines and cosines given in Appendix E.)

1. What is the magnitude of the average gravitational force between the Sun and Mercury?
2. What is the magnitude of the average gravitational force between the Sun and Mercury if the orbital radius of Mercury was doubled?

(you will have to look up Newton's Universal Law of Gravitation and some values of mass and distance) and please list them with the solution.

Please answer in scientific notation and round to three significant figures.

Kelp Company produces three joint products from seaweed. At the split-off point, three basic products emerge: Sea Tea, Sea Paste, and Sea Powder. Each of these products can either be sold at the split-off point or be processed further. If they are processed further, the resulting products can be sold as delicacies to health food stores. Cost and revenue information is as follows.

Required:

A. What is the selling price per pound of Sea Paste at the split-off point at which the company is indifferent?