You are the Director of a large investment fund in Canada. One of your top priorities is to expand your team of mutual fund managers. You are reviewing the resumes of two candidates, Laure Marshall and Kenneth Huang, who have been screened and forwarded to you by your firm’s HR coordinator. Laure has worked as a mutual fund manager for 15 years, 13 of which she led her fund to beat its market benchmark. Kenneth has worked as a mutual fund manager for 10 years, 7 of which he led his fund to beat its market benchmark. Assuming that for each mutual fund manager the likelihood of beating their market benchmark in any given year is constant and independent of their performance in previous years, you evaluate the candidacy of Laure and Kenneth for joining your investment fund.
1 (a)It is well-known that mutual funds, on average, underperform their market benchmark. That is, across all mutual funds and many years, the proportion of funds that beat their market benchmark in terms of annual performance is 0.475. You have a strong reason to believe that both Laure and Kenneth are better than average fund managers, otherwise the HR coordinator would not have forwarded you their CV in the first place. Using hypothesis testing, examine whether your prior belief about their abilities is accurate.
(i) Clearly state your null and alternative hypotheses.
(ii) Copy your StatTools output below (make sure your output copies properly and is easy to read).
(iii) Briefly state and explain your findings, making sure to connect them to the relevant portions of the StatTools output.
1 (b)Based on the past performance of Laure and Kenneth as fund managers, can you confidently say that Laure is a better fund manager than Kenneth? Does your answer depend on whether you run a 1-tailed test or a 2-tailed test?
(i) Clearly state your null and alternative hypotheses for both tests.
(ii) Show your StatTools output for both tests.
(iii) Briefly state and explain your findings for both tests, making sure to connect them to the relevant portions of the StatTools output.
1 (c)Now reconsider part (b), but suppose that Laure and Kenneth each have twice as much experience (Laure has 30 years, and Kenneth 20 years), and the same success rate as before (13 out of 15 years for Laure, and 7 out of 10 years for Kenneth). See the data under column Q1c. Can you now confidently say that Laure is a better fund manager than Kenneth? Does your answer depend on whether you run a 1-tailed test or a 2-tailed test?
(i) Clearly state your null and alternative hypotheses for both tests.
(ii) Show your StatTools output for both tests.
(iii) Briefly state and explain your findings for both tests, making sure to connect them to the relevant portions of the StatTools output. Comment specifically onwhatchanges relative to part (b) andwhy.
2 (a)Run a regression of price on the following variables: year, ppm, colordum, dpi, hp, ibm, apple, and brother. (The printer brand variables are dummy variables, i.e., ibm = 1 if firmname = “IBM/LEXMARK” and 0 otherwise, apple = 1 if firmname = “APPLE_COMPUTER_CO” and 0 otherwise, and brother = 1 if firmname = “BROTHER_INTERNATIONAL_CORP” and 0 otherwise.)
Copy your StatTools regression output below (make sure your output copies properly and is easy to read).
2 (b)Based on the results in part (a) what you can say about the population relationship between price and each of the following variables: year, ppm, colordum, and dpi?
2 (c)Based on the results in part (a), how does the average price of Brother printers compare to the average price of printers that are neither Apple, nor HP nor IBM, in the population?
2 (d)Based on the results in part (a), how does the average price of Brother printers compare to the average price of Apple printers ?
2 (e)Suppose you want to investigate how the relationship between ppm and price is different for Apple and Brother printers vis-à-vis non-Apple non-Brother printers (in the population).
(i) Run a single regression that includes ALL the variables included in part (a), plus theminimalnumber of variables that are required to answer this question, and show the entire StatTools output for this regression.
(ii) Based on the results of this regression, answer the following questions:
How does the Price-PPM for Apple printers compare to that for non-Apple non-Brother printers (in the population)?
How does the Price-PPM for Brother printers compare to that for non-Apple non-Brother printers (in the population)?
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2 (e)Suppose you want to investigate how the relationship between ppm and price is different for Apple and Brother printers vis-à-vis non-Apple non-Brother printers (in the population).
(i) Run a single regression that includes ALL the variables included in part (a), plus theminimalnumber of variables that are required to answer this question, and show the entire StatTools output for this regression.
(ii) Based on the results of this regression, answer the following questions:
How does the Price-PPM for Apple printers compare to that for non-Apple non-Brother printers (in the population)?
How does the Price-PPM for Brother printers compare to that for non-Apple non-Brother printers (in the population)?
As the Chief Analyst in the IPO arm of Alex Brown & Sons, you are responsible for pricing the initial public offerings (IPO) of firms in the information processing industries. The correct pricing of a client’s shares is key to a successful IPO…and to the reputation of both an investment bank and the analyst involved.
Alex Brown’s CEO charges you with the following assignment: “We need to price the shares of Quantum Leap Chips (QLC), and we really need to get this priced accurately. Our reputation took a big hit on that mispricing of Advanced Bio-semi Chips back in August. The financial press killed us in the day-after reviews, after we couldn’t sell all the shares on IPO day. We can’t afford another inaccurate assessment. So, predict the IPO market value of QLC, and then we can set the IPO share price accordingly.”
3 (a)With the goal of predicting the IPO market value of QLC, run the following three regressions andpresent the results in a regression tablethat follows the standard format discussed in class.
Regression (i):
Dependent variable: IPO Market Value ($000)
Independent variables: ASIC, Logic, Pre-IPO rev ($000), Age at IPO, MBA CEO, Serial Entrepreneur, Engineer CEO
Regression (ii):
Dependent variable: IPO Market Value ($000)
Independent variables: ASIC, Logic, Pre-IPO rev ($000), Age at IPO, Univ alliances, MBA CEO, Serial Entrepreneur, Engineer CEO, Engineer CEO*Univ alliances
Regression (iii):
Same variables as regression (ii), PLUS the minimal set of additional independent variables that are necessary to estimate how IPO market value varies over time.
Notes: (1) Precision for regression coefficients: two digits after the decimal point. (2) Do NOT report standard errors.
3 (b)Using your results in part (a), come up with an estimate of the IPO market value of QLC.The company has the following characteristics.
- It is specializing in Logic.
- It plans to launch its IPO in January 2022.
- QLC currently has 5 patents, 3 university alliances, 2 industry alliances, and zero government alliances (these numbers will remain valid until the IPO).
- The 4-year-old firm’s CEO has an MBA degree and also has an engineering PhD.
- This is the CEO’s first entrepreneurial venture.
- QLC has revenue of $6,500 during the last 12 months. (Note that this corresponds to 6.5 if one measures pre-IPO revenue in $000).
NOTE: Please provide full details of all the steps that you are taking to reach your answer, i.e., your estimate of the IPO market value of QLC.
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