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investment analysis portfolio

Questions and Answers of Investment Analysis Portfolio

2. Assuming regularization is utilized in the machine learning technique used for executing Step 1, which of the following ML models would be least appropriate:A. Regression tree with pruning.B.
1. The machine learning techniques appropriate for executing Step 1 are most likely to be based on:A. regression B. classification C. clustering
35. Based on Exhibit 5, which single time-series model would most likely be appropriate for Busse to use in predicting the future stock price of Company 3?A. Log-linear trend model B.
34. Based on Exhibit 5, for which company would the regression of stock prices on oil prices be expected to yield valid coefficients that could be used to estimate the long-term relationship between
33. Based on Exhibit 5, Busse should conclude that the variance of the error terms for Company 1:A. is constant.B. can be predicted.C. is homoskedastic.
32. Based on the regression output in Exhibit 3 and sales data in Exhibit 4, the forecasted value of quarterly sales for March 2016 for PoweredUP is closest to:A. $4.193 billion.B. $4.205 billion.C.
31. Based on the regression output in Exhibit 2, what should lead Busse to conclude that the Regression 3 equation is not correctly specified?A. The Durbin–Watson statistic B. The t-statistic for
30. In order to perform the nonstationarity test, Busse should transform the Regression 1 equation by:A. adding the second lag to the equation.B. changing the regression’s independent variable.C.
29. Based on the regression results in Exhibit 1, the original time series of exchange rates:A. has a unit root.B. exhibits stationarity.C. can be modeled using linear regression.
28. Based on the regression output in Exhibit 1, the first-differenced series used to run Regression 2 is consistent with:A. a random walk.B. covariance stationarity.C. a random walk with drift.
27. Which of Busse’s conclusions regarding the exchange rate time series is consistent with both the properties of a covariance-stationary time series and the properties of a random walk?A.
26. Based on the mean-reverting level implied by the AR(1) model regression output in Exhibit 1, the forecasted oil price for September 2015 is most likely to be:A. less than $42.86.B. equal to
25. Based on the data for the AR(1) model in Exhibits 1 and 2, Martinez can conclude that the:A. residuals are not serially correlated.B. autocorrelations do not differ significantly from zero.C.
24. Based on Exhibit 1, the forecasted oil price in September 2015 based on the AR(2)model is closest to:A. $38.03.B. $40.04.C. $61.77.
23. Martinez’s Conclusion 1 is:A. correct.B. incorrect because the mean and variance of WTI oil prices are not constant over time.C. incorrect because the Durbin–Watson statistic of the AR(2)
22. Based on the regression output in Exhibit 1, there is evidence of positive serial correlation in the errors in:A. the linear trend model but not the log-linear trend model.B. both the linear
21. Based on Exhibit 1, the predicted WTI oil price for September 2015 using the loglinear trend model is closest to:A. $29.75.B. $29.98.C. $116.50.
20. Based on Exhibit 1, the predicted WTI oil price for October 2015 using the linear trend model is closest to:A. $29.15.B. $74.77.C. $103.10.
19. Suppose we want to predict the annualized return of the five-year T-bill using the annualized return of the three-month T-bill with monthly observations from January 1993 to December 2002. Our
18. Describe how to test for autoregressive conditional heteroskedasticity (ARCH) in the residuals from the AR(1) regression on first differences in the civilian unemployment rate, UERt ¼ b0 þ
17. Suppose we decide to use an autoregressive model with a seasonal lag because of the seasonal autocorrelation in the previous problem. We are modeling quarterly data, so we estimate Equation 15:
16. Exhibit 14 shows the autocorrelations of the residuals from an AR(1) model fit to the changes in the gross profit margin (GPM) of the Home Depot, Inc.Exhibit 15 shows the output from a regression
15. Exhibit 13 shows the quarterly sales of Avon Products from 1Q 1992 to 2Q 2002.Describe the salient features of the data shown. 13 Quarterly Sales at Avon Millions of Dollars 1900 1700 1500- 1300-
14. Exhibit 11 shows the quarterly sales of Cisco Systems from 3Q 2001 to 2Q 2019.A. Describe the salient features of the quarterly sales series.B. Describe the procedures we should use to determine
13. Using monthly data from January 1992 to December 2000, we estimate the following equation for lightweight vehicle sales: ln(Salest) ¼ 2.7108 þ 0.3987ln(Salest−1) þ εt. Exhibit 10 gives
12. Exhibit 9 shows a plot of first differences in the log of monthly lightweight vehicle sales over the same period as in Problem 11. Has differencing the data made the resulting series, ln(Salest)
11. Exhibit 8 shows monthly observations on the natural log of lightweight vehicle sales, ln(Salest), for January 1992 to December 2000.A. Using the figure, comment on whether the specification
10. A. The AR(1) model for the civilian unemployment rate, UERt ¼ −0.0405 −0.4674UERt−1, was developed with five years of data. What would be the drawback to using the AR(1) model to predict
9. Exhibit 7 gives the actual change in the log of sales of Cisco Systems from 1Q 2019 to 4Q 2019, along with the forecasts from the regression model ln(Salest) ¼ 0.0068 þ 0.2633ln(Salest−1)
8. Exhibit 6 gives the actual sales, log of sales, and changes in the log of sales of Cisco Systems for the period 1Q 2019 to 4Q 2019.Forecast the first- and second-quarter sales of Cisco Systems for
7. Suppose the following model describes changes in the civilian unemployment rate:UERt ¼ −0.0668 − 0.2320UERt−1. The current change (first difference) in the unemployment rate is 0.0300.
6. Assume that changes in the civilian unemployment rate are covariance stationary and that an AR(1) model is a good description for the time series of changes in the unemployment rate. Specifically,
5. Exhibit 5 gives the regression output of an AR(1) model on first differences in the unemployment rate. Describe how to interpret the DW statistic for this regression. EXHIBIT 5 Estimating an AR(1)
4. Exhibit 4 shows a plot of the first differences in the civilian unemployment rate (UER)between January 2013 and August 2019, UERt ¼ UERt − UERt−1.A. Has differencing the data made the new
3. You have been assigned to analyze automobile manufacturers, and as a first step in your analysis, you decide to model monthly sales of lightweight vehicles to determine sales growth in that part
2. Exhibit 2 compares the predicted civilian unemployment rate (PRED) with the actual civilian unemployment rate (UER) from January 2013 to August 2019. The predicted results come from estimating the
1. The civilian unemployment rate (UER) is an important component of many economic models. Exhibit 1 gives regression statistics from estimating a linear trend model of the unemployment rate: UERt ¼
45. The best rationale for Quinni’s caution about the three-variable model is that the:A. dependent variable is defined differently.B. sample sizes are different in the two models.C. dividend
44. If Varden’s beliefs about ROE and CEO tenure are true, which of the following would violate the assumptions of multiple regression analysis?A. The assumption about CEO tenure distribution only
43. Varden’s best answer to Quinni’s question about overall significance is:A. R2.B. adjusted R2.C. the F-statistic.
42. Based on Exhibit 1, Varden’s best answer to Quinni’s question about the F-statistic is:A. both independent variables are significant at the 0.05 level.B. neither independent variable is
41. Based on Exhibit 2, Quinni’s best answer to Varden’s question about the effect of adding a third independent variable is:A. no for R2 and no for adjusted R2.B. yes for R2 and no for adjusted
40. Based on Exhibit 1, the predicted ROE for DF Associates is closest to:A. 10.957%.B. 16.593%.C. 20.388%.
39. Based on Exhibit 1, which independent variables in Varden’s model are significant at the 0.05 level?A. ESG only B. Tenure only C. Neither ESG nor tenure
38. At a significance level of 1%, which of the following is the best interpretation of the regression coefficients with regard to explaining ROE?A. ESG is significant, but tenure is not.B. Tenure is
37. Based on Exhibit 1 and given Varden’s expectations, which is the best null hypothesis and conclusion regarding CEO tenure?A. b2 0; reject the null hypothesis B. b2 ¼ 0; cannot reject the
36. Should Honoré have estimated the models in Exhibit 1 and Exhibit 2 using probit or logit models instead of traditional regression analysis?A. Both should be estimated with probit or logit
35. Based on her estimated Durbin–Watson statistic, Honoré should:A. fail to reject the null hypothesis.B. reject the null hypothesis because there is significant positive serial correlation.C.
34. Is Honoré’s description of the effects of positive serial correlation (in Exhibit 2) correct regarding the estimated coefficients and the standard errors?A. Yes B. No, she is incorrect about
33. Honoré is concerned about the consequences of heteroskedasticity. Is she correct regarding the effect of heteroskedasticity on the reliability of the F-test and t-tests?A. Yes B. No, she is
32. Which of the three methods suggested by Smith would best capture the ability of the Morningstar rating system to predict mutual fund performance?A. Method 1 B. Method 2 C. Method 3
31. Honoré describes three potential consequences of multicollinearity. Are all three consequences correct?A. Yes B. No, 1 is incorrect C. No, 2 is incorrect
30. Based on Exhibit 1, the difference between the predicted annualized returns of a growth fund and an otherwise similar value fund is closest to:A. 1.86%.B. 2.44%.C. 3.01%.
29. Considering Exhibit 1, the F-statistic is closest to:A. 3.22.B. 8.06.C. 30.79.
28. Is Chiesa’s concluding statement correct regarding parameter estimate uncertainty and regression model uncertainty?A. Yes.B. No, predictions are not subject to parameter estimate uncertainty.C.
27. With respect to the default spread, the estimated model indicates that when business conditions are:A. strong, expected excess returns will be higher.B. weak, expected excess returns will be
26. In response to Question 4, the 95 percent confidence interval for the regression coefficient for the default spread is closest to:A. 0.13 to 5.95.B. 1.72 to 4.36.C. 1.93 to 4.15.
25. Regarding Question 3, the Pres party dummy variable in the model indicates that the mean monthly value for the excess stock market return is:A. 1.43 percent larger during Democratic presidencies
24. Which of the following is Chiesa’s best response to Question 2 regarding serial correlation in the error term? At a 0.05 level of significance, the test for serial correlation indicates that
23. Regarding the intern’s Question 1, is the regression model as a whole significant at the 0.05 level?A. No, because the calculated F-statistic is less than the critical value for F.B. Yes,
22. Is Chang’s Statement 2 correct?A. Yes.B. No, because the model’s coefficient estimates will be unbiased.C. No, because the model’s coefficient estimates will be consistent.Gary Hansen is a
21. Is Chang’s Statement 1 correct?A. Yes.B. No, because the model’s F-statistic will not be biased.C. No, because the model’s t-statistics will not be biased.Gary Hansen is a securities
20. The most appropriate interpretation of the multiple R-squared for Hansen’s model is that:A. unexplained variation in the dependent variable is 36 percent of total variation.B. correlation
19. The most appropriate null hypothesis and the most appropriate conclusion regarding Hansen’s belief about the magnitude of the initial return relative to that of the pre-offer price adjustment
18. The 95 percent confidence interval for the regression coefficient for the pre-offer price adjustment is closest to:A. 0.156 to 0.714.B. 0.395 to 0.475.C. 0.402 to 0.468.Gary Hansen is a
17. Based on Hansen’s regression, the predicted initial return for the upcoming IPO is closest to:A. 0.0943.B. 0.1064.C. 0.1541.Gary Hansen is a securities analyst for a mutual fund specializing in
16. You have noticed that hundreds of non-US companies are listed not only on a stock exchange in their home market but also on one of the exchanges in the United States.You have also noticed that
15. You are analyzing the cross-sectional variation in the number of financial analysts that follow a company (also the subject of Problems 3 and 8). You believe that there is less analyst following
14. You are analyzing the variables that explain the returns on the stock of the Boeing Company. Because overall market returns are likely to explain a part of the returns on Boeing, you decide to
13. The book-to-market ratio and the size of a company’s equity are two factors that have been asserted to be useful in explaining the cross-sectional variation in subsequent returns. Based on this
12. In estimating a regression based on monthly observations from January 1987 to December 2002 inclusive, you find that the coefficient on the independent variable is positive and significant at the
11. You are analyzing if institutional investors such as mutual funds and pension funds prefer to hold shares of companies with less volatile returns. You have the percentage of shares held by
10. You are examining the effects of the January 2001 NYSE implementation of the trading of shares in minimal increments (ticks) of $0.01 (decimalization). In particular, you are analyzing a sample
9. You believe there is a relationship between book-to-market ratios and subsequent returns. The output from a cross-sectional regression and a graph of the actual and predicted relationship between
8. Problem 3 addressed the cross-sectional variation in the number of financial analysts who follow a company. In that problem, company size and debt-to-equity ratios were the independent variables.
7. Both researchers and the popular press have discussed the question as to which of the two leading US political parties, Republicans or Democrats, is better for the stock market.A. Write a
6. Some developing nations are hesitant to open their equity markets to foreign investment because they fear that rapid inflows and outflows of foreign funds will increase volatility.In July 1993,
5. The neglected-company effect claims that companies that are followed by fewer analysts will earn higher returns on average than companies that are followed by many analysts.To test the
4. In early 2001, US equity marketplaces started trading all listed shares in minimal increments (ticks) of $0.01 (decimalization). After decimalization, bid–ask spreads of stocks traded on the
3. There is substantial cross-sectional variation in the number of financial analysts who follow a company. Suppose you hypothesize that a company’s size (market cap) and financial risk
2. One of the most important questions in financial economics is what factors determine the cross-sectional variation in an asset’s returns. Some have argued that book-to-market ratio and size
1. With many US companies operating globally, the effect of the US dollar’s strength on a US company’s returns has become an important investment issue. You would like to determine whether
33. Which of Olabudo’s noted limitations of regression analysis is correct?A. Only Limitation 1 B. Only Limitation 2 C. Both Limitation 1 and Limitation 2 Doug Abitbol is a portfolio manager for
32. Based on Exhibit 1, Olabudo should calculate a prediction interval for the actual US CPI closest to:A. 2.7506 to 2.7544.B. 2.7521 to 2.7529.C. 2.7981 to 2.8019.Doug Abitbol is a portfolio manager
31. Based on Exhibit 1, Olabudo should:A. conclude that the inflation predictions are unbiased.B. reject the null hypothesis that the slope coefficient equals 1.C. reject the null hypothesis that the
30. Using information from Exhibit 2, Vasileva should compute the 95% prediction intervalfor Amtex share return for Month 37 to be:A. 0.0882 to 0.1025.B. 0.0835 to 0.1072.C. 0.0027 to 0.0116. Elena
29. Based on Exhibit 2 and Vasileva’s prediction of the crude oil return for Month 37, the estimate of Amtex share return for Month 37 is closest to:A. 0.0024.B. 0.0071.C. 0.0119. Elena Vasileva
28. Based on Exhibit 2, Vasileva should compute the:A. 99% confidence interval for the slope coefficient to be 0.1594 to 0.3114.B. 95% confidence interval for the intercept to be 0.0037 to 0.0227.C.
27. Based on Exhibit 2, Vasileva should reject the null hypothesis that:A. the slope is less than or equal to 0.15.B. the intercept is less than or equal to 0.C. crude oil returns do not explain
26. Based on Exhibit 1, the standard error of the estimate is closest to:A. 0.044558.B. 0.045850.C. 0.050176. Elena Vasileva recently joined Energy Invest as a junior portfolio analyst. Vasileva's
25. Which of Vasileva’s assumptions regarding regression analysis is incorrect?A. Assumption 1 B. Assumption 2 C. Assumption 3 Elena Vasileva recently joined Energy Invest as a junior portfolio
24 Based on Liu’s regression results in Exhibit 2, the F-statistic for testing whether the slope coefficient is equal to zero is closest to:A 2.2219.B 3.5036.C 4.9367.Anh Liu is an analyst
23. Based on Exhibit 2, the short interest ratio expected for MQD Corporation is closest to:A. 3.8339.B. 5.4975.C. 6.2462.Anh Liu is an analyst researching whether a company’s debt burden affects
22. Which of the following should Liu conclude from these results shown in Exhibit 2?A. The average short interest ratio is 5.4975.B. The estimated slope coefficient is statistically significant at
21. The upper bound for the 95 percent confidence interval for the coefficient on the debt ratio in the regression is closest to:A. 1.0199.B. 0.3947.C. 1.4528.Anh Liu is an analyst researching
20. Based on Exhibit 2, the degrees of freedom for the t-test of the slope coefficient in this regression are:A. 48.B. 49.C. 50.Anh Liu is an analyst researching whether a company’s debt burden
19. The dependent variable in Liu’s regression analysis is the:A. intercept.B. debt ratio.C. short interest ratio.Anh Liu is an analyst researching whether a company’s debt burden affects
18. Which of the interpretations best describes Liu’s findings for her report?A. Interpretation 1 B. Interpretation 2 C. Interpretation 3 Anh Liu is an analyst researching whether a company’s
17. Based on Exhibits 1 and 2, the correlation between the debt ratio and the short interest ratio is closest to:A. 0.3054.B. 0.0933.C. 0.3054.Anh Liu is an analyst researching whether a company’s
16. Based on Exhibit 1, the sample covariance is closest to:A. 9.2430.B. 0.1886.C. 8.4123.Anh Liu is an analyst researching whether a company’s debt burden affects investors’ decision to short

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