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Thread: Sample CFA Level 2 question bank for June 2013 exam

  1. #81
    Solutions to Item set for 29-March:

    1. Correct Answer is C: Change in working capital investment = (Accounts receivable + Inventory – Accounts payable) 2012 – (Accounts receivable + Inventory – Accounts payable) 2011 = (55+145-95) – (40+120-105) = 105 – 55 = $50,000.
    2. Correct Answer is B: Change in fixed capital investment = Ending Net PP&E – Beginning Net PP&E + Depreciation – gain on sale of long-term asset = 440 – 450 + 55 – 20 = $25,000.
    3. Correct Answer is A: FCFF = NI + NCC + Int*(1-t) –FCInv – WCInv = 48 + (55-20 (gain on sale of asset)) + 35*(1-0.4) - 25 – 50 = 48 + 35 + 21 - 25 – 50 = $29,000.
    Or
    It can be calculated by uses of FCFF. FCFF will be equal to the change in cash plus after tax interest expense plus net repayment of debt plus cash dividends plus net stock repurchases. FCFF = (103-75) + 35*(1-0.4) + (-10-10) + 0 + 0 = 28 + 21 – 20 = $29,000.
    4. Correct Answer is C: WACC for the firm = 0.08*(1-0.4)*(0.8/1.8) + 0.125*(1/1.8) = 9.077%. Value of the firm = 29*(1.1/1.09077) + 29*(1.1/1.09077)2 + 29*(1.1/1.09077)3 + 29*1.13*1.04/[(0.09077-0.04)*1.090773] = $697,633.
    5. Correct Answer is C: None of the dividends payment, stock issuance and debt issuance has any impact on the current year’s FCFF as these things are done after the calculation of FCFF. Debt issuance will impact FCFE but not FCFF.
    6. Correct Answer is C: If dividends are paid, then the firm is reinvesting less money and thus the growth rate of FCFF will be less and thus the future FCFF will tend to decrease. However, it can also happen that company does not need any money for reinvestment. In that case, there will be no impact on the firm’s future FCFF. Future FCFF is least likely to increase on payment of dividends.

  2. #82
    Item set for 30-March (Equity):

    Robert Higgs Case Scenario

    Robert Higgs, CFA, is working as a security analyst in Casey Research. His primary job is to calculate the required return on equity for various stocks. He has developed an expertise in this field by working more than five years.

    He is looking at S&P Index. He calculates the equity risk premium using macroeconomic model estimates. The data for the security is given in Exhibit 1.

    Exhibit 1
    S&P Index

    Expected inflation, EINFL 2.0%
    Expected growth rate in real earnings per share, EGREPS 2.5%
    Expected growth rate in P/E ratio, EGPE 5.0%
    Expected income component, EINC 3.0%

    The expected risk free rate is 6% per annum.

    He also calculates the equity risk premium of S&P Index using Gordon growth model estimates. The dividend yield on the index based on year-ahead aggregate forecasted dividends and aggregate market value is 2.5%. The consensus long-term earnings growth rate is 4.5%. The current long-term government bond yield is 3.0%.

    Bob Murphy, portfolio manager in Casey Research, asks Robert to calculate the required return on equity for a small cap stock using Fama-French model. Robert extracts the data for the small cap stock, Bluestone Inc., which is given in Exhibit 2.

    Exhibit 2
    Bluestone Inc.

    RMRF (return on market value-weighted equity index in excess of the one-month T-bill rate) 6.0%
    SMB (average return on small cap portfolios minus the average return on large cap portfolios) 1.5%
    HML (average return on high book-to-market portfolios minus the average return on low book-to-market portfolios) 3.0%
    Beta (market) 1.2
    Beta (value) -0.7
    Beta size 0.9
    Risk-free rate 6.0%

    Bob inquires Robert about the model to be used for calculating the required return on equity for relatively illiquid securities. Robert replies that a model known as Pastor-Stambaugh model (PSM) can be used to calculate the required return on equity. The liquidity premium is also added to Fama-French model and the beta of the stock with respect to liquidity is multiplied with the liquidity premium to get the liquidity premium for the stock. He also makes following statements:

    Statement 1: The more liquid stock will have a higher liquidity beta
    Statement 2: Average-liquidity equity should have a liquidity beta of zero
    Statement 3: The liquidity premium represents the excess returns to a portfolio that invests the proceeds from shorting high-liquidity stocks in a portfolio of low-liquidity stocks

    One colleague asks Robert to calculate the required return on an equity using bond yield plus risk premium method for Capstone Inc. The data for Capstone Inc. is given in Exhibit 3.

    Exhibit 3
    Capstone Inc.

    Macaulay Duration of long-term debt 12.80
    Modified duration of long-term debt 11.95
    Number of coupon payment per year for long-term debt 1.0
    Risk premium for holding the security 4.5%
    Risk-free rate 6.0%

    Bob asks him about the difference between the statistical multifactor models and macroeconomic factor models. Robert makes the following statements:

    Statement 4: In macroeconomic factor models, the factors are economic variable that have impacted the historical cash flows of companies
    Statement 5: In statistical factor models, statistical methods are applied to historical returns to determine portfolios of securities that explain those returns in various senses.

    1. What is the equity risk premium for S&P Index? Use macroeconomic model estimates to calculate the equity risk premium.
    a) 6.50%
    b) 6.78%
    c) 7.07%

    2. What is the GGM (Gordon growth model) equity risk premium estimate?
    a) 3.90%
    b) 4.00%
    c) 4.11%

    3. What is the required return on equity for Bluestone Inc. using Fama-French model?
    a) 12.45%
    b) 14.85%
    c) 16.65%

    4. Which of the following statements made by Robert is least likely to be accurate for PSM model?
    a) Statement 1
    b) Statement 2
    c) Statement 3

    5. What is the required return on equity for Capstone Inc. using bond yield plus risk premium method?
    a) 9.80%
    b) 10.50%
    c) 11.61%

    6. Which of the following statements made by Robert regarding the statistical multifactor model and macroeconomic multifactor model is least accurate?
    a) Statement 4
    b) Statement 5
    c) Both statements are correct

  3. #83
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    Answer to Item set for 30-March (Equity):
    1. B
    2. B
    3. A
    4. A
    5. C
    6. A

  4. #84
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    Solution to 30th March

    1. c
    2. b
    3. a
    4. b
    5. c
    6. b

  5. #85
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    Quote Originally Posted by Konvexity Institute View Post
    Solutions to Item set for 29-March:

    1. Correct Answer is C: Change in working capital investment = (Accounts receivable + Inventory – Accounts payable) 2012 – (Accounts receivable + Inventory – Accounts payable) 2011 = (55+145-95) – (40+120-105) = 105 – 55 = $50,000.
    2. Correct Answer is B: Change in fixed capital investment = Ending Net PP&E – Beginning Net PP&E + Depreciation – gain on sale of long-term asset = 440 – 450 + 55 – 20 = $25,000.
    3. Correct Answer is A: FCFF = NI + NCC + Int*(1-t) –FCInv – WCInv = 48 + (55-20 (gain on sale of asset)) + 35*(1-0.4) - 25 – 50 = 48 + 35 + 21 - 25 – 50 = $29,000.
    Or
    It can be calculated by uses of FCFF. FCFF will be equal to the change in cash plus after tax interest expense plus net repayment of debt plus cash dividends plus net stock repurchases. FCFF = (103-75) + 35*(1-0.4) + (-10-10) + 0 + 0 = 28 + 21 – 20 = $29,000.
    4. Correct Answer is C: WACC for the firm = 0.08*(1-0.4)*(0.8/1.8) + 0.125*(1/1.8) = 9.077%. Value of the firm = 29*(1.1/1.09077) + 29*(1.1/1.09077)2 + 29*(1.1/1.09077)3 + 29*1.13*1.04/[(0.09077-0.04)*1.090773] = $697,633.
    5. Correct Answer is C: None of the dividends payment, stock issuance and debt issuance has any impact on the current year’s FCFF as these things are done after the calculation of FCFF. Debt issuance will impact FCFE but not FCFF.
    6. Correct Answer is C: If dividends are paid, then the firm is reinvesting less money and thus the growth rate of FCFF will be less and thus the future FCFF will tend to decrease. However, it can also happen that company does not need any money for reinvestment. In that case, there will be no impact on the firm’s future FCFF. Future FCFF is least likely to increase on payment of dividends.
    @Konvexity:- Kindly elaborate pt 5 & 6. I m not clear abt it.

  6. #86
    Solutions to Item set for 30th March:

    1. Correct Answer is B: The equity risk premium of S&P = [(1+EINFL)(1+EGREPS)(1+EGPE) – 1] + EINC – Expected risk free return = [1.02*1.025*1.05-1]+0.03-0.06 = 6.78%.

    2. Correct Answer is B: GGM equity risk premium estimate = dividend yield + long term earnings growth rate – long-term government bond yield = 2.5% + 4.5% - 3.0% = 4.00%.

    3. Correct Answer is A: Required return on equity for Bluestone Inc. using Fama-French model = Risk free rate + βmarket*RMRF + βsize*SMB + βvalue*HML = 6.0% + 1.2*6.0% + 0.9*1.5% - 0.7*3.0% = 12.45%

    4. Correct Answer is A: Statement 1 is not correct. The more liquid stock will have a negative (lower) beta and the less liquid stock will have a positive (higher) beta.

    5. Correct Answer is C: Modified duration = Macaulay duration/ (1+ (YTM/n)) = > 1+YTM = 12.80/11.95 = 1.07113 => YTM = 7.11%. Required return for Capstone Inc. = YTM on long-term bond + Risk premium = 7.11% + 4.5% = 11.61%.

    6. Correct Answer is A: Statement 4 is not correct. In macroeconomic model, the factors are macroeconomics variables that affect the future expected cash flows of the company.

  7. #87
    Item set for 31-March (Quantitative Methods):

    Daniel Brown Case Scenario

    Daniel Brown, a CFA charter holder, has run a regression on time series data for the sales data. He has used a log-linear model and the results of the regression model are shown in Exhibit 1.

    Exhibit 1

    Coefficient Standard error t-statistics
    Intercept 2.15 0.025 86.0
    Trend 0.055 0.005 11.0

    Model is ln revenue=b0+b1(t) where t=1, 2… 32 and revenue is in million dollars.

    He has used quarterly data from 1st quarter of 2000 to the last quarter of 2007.

    Daniel is contemplating between choosing AR (1) model or AR (2) model for a particular auto-regression of some data. To check the forecasting accuracy of both the models, he used both model for forecasting the results from 1st quarter of 2008 to last quarter of 2012. He also calculated the root mean squared error (RMSE) for the residuals of data from 1st quarter of 2000 to the last quarter of 2007. The results of the RMSE are shown in Exhibit 2.

    Exhibit 2

    AR(1) model AR(2) model
    RMSE for data from 2000 to 2007 5.64 4.12
    RMSE for data from 2008 to 2012 12.59 14.11

    He wants to form a hypothesis test for autoregressive conditional heteroskedasticity. The ARCH (1) model is et2=a0+ (a1-1) e(t-1)^2+μt

    He also runs a regression using two time series of stock returns and GDP growth where none of the time series are covariance stationary and are not co-integrated as well.

    Joseph Lentz, a colleague of Daniel, asks him about the conditions for a time series model to be covariance stationary. Daniel makes the following statements:

    Statement 1: It should have a constant and finite expected value
    Statement 2: It should have a constant and finite variance
    Statement 3: It should have a constant and finite covariance between values at any given lag

    Joseph asks him about the random walk model as well. He wants to know about the properties of random walk model. Daniel makes the following statements:

    Statement 4: The expected value of each error term is zero
    Statement 5: The variance of the error terms is constant and there is no serial correlation between the error terms
    Statement 6: The random walk model is covariance stationary

    7. What is the approximate predicted value of revenue for the 3rd quarter of 2010?
    a) $91.38 million
    b) $73.33 million
    c) $15.72 million

    8. Which autoregressive model he should use by looking at the residual mean squared errors (RMSE)?
    a) AR(1) model
    b) AR (2) model
    c) Either of AR(1) model or AR(2) model

    9. Can the linear regression model be used for modelling the relationship between two time series in the given example of stock return and GDP growth rate?
    a) Yes, because they are not co-integrated
    b) Yes, because they are not covariance stationary
    c) No

    10. What would be the null hypothesis for the autoregressive conditional heteroskedasticity?
    a) a0 = 0
    b) a1 = 0
    c) a1 = 1

    11. Which of the following statements made by Daniel is least likely to be accurate regarding the conditions of a time series model to be covariance stationary?
    a) Statement 2 as it should have only finite variance which may or may not be constant
    b) Statement 3 as it should have a constant variance which need not be finite
    c) All statements are correct

    12. Which of the following statements made by Daniel is least likely to be accurate regarding the properties of a random walk model?
    a) Statement 5
    b) Statement 6
    c) All statements are correct

  8. #88
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    Quote Originally Posted by mahesh View Post
    @Konvexity:- Kindly elaborate pt 5 & 6. I m not clear abt it.
    @Mahesh

    FCFF = Cash flow from operations - Capex

    FCFE = Net Income - Net Capital Expenditure - Change in Net Working Capital + New Debt - Debt Repayment

    So the explanation of Q.5 is directly from the above formula.

  9. #89
    Solutions to Item set for 31-March:

    1. Correct Answer is A: The predicted value of revenue for 3rd quarter for 2010 = exp [b (0) + b (1)*t] = exp (2.15+0.055*43) = $91.38 million. Note there that the t is equal to 43 (10*4 = quarters from 2000 to 2009 plus 3 quarter of 2010)
    2. Correct Answer is A: The AR (1) model should be used as it has a lower RMSE for out-of-sample forecast.
    3. Correct Answer is C: No, he can’t use the regression model as the time series are not covariance stationary and also not co-integrated.
    4. Correct Answer is C: The null hypothesis should be that the coefficient of et-12 is equal to zero i.e. a1 -1 =0 or a1 = 0.
    5. Correct Answer is C: All statements are correct.
    6. Correct Answer is B: Statement 6 is incorrect as a random walk model is not covariance stationary because it does not have a mean reverting level because of unit root.
    Last edited by Konvexity Institute; 02-04-2013 at 01:25 AM.

  10. #90
    Item set for 1-April (Quantitative Methods):

    Peter Robinson Case Scenario

    Peter Robinson is trying to calculate the cost of equity for a company, Little Flower. He thinks that the Fama-French model would be applicable for that company and wants to check whether the model is statistically explaining the returns of the stock over a period. He runs the regression model for the company for the monthly return data of last 5 years and the results of the regression are given in Exhibit 1. He runs the regression by keeping the constant term as zero.

    Exhibit 1

    Coefficient Standard error t-statistics
    R(m) - R(f) 1.60 0.40 4.00
    R(small) - R(big) 0.40 0.12 3.33
    R(HBM) - R(LBM) -0.70 0.27 -2.59

    Anova df SS MS F Significance F
    Regression - 84.50 - - <0.005
    Error - 120.50 -
    Total - 205.00 -
    R^2 -


    The Fama-French model is formulated as: Ri – Rf = βmkt,i*(RM – Rf) + βSMB,i*(Rsmall – Rbig) + βHML*(RHBM – RLBM)+ ei
    • Where Rmkt- Rf= return on a value-weighted market index minus the risk-free rate
    • Rsmall-Rbig = average return on 3 small-cap portfolios minus the average return on 3 large-cap portfolios
    • RHBM-RLBM= average return on 2 high book-to-market portfolio minus the average return on 2 low book-to-market portfolios

    The critical value of test statistic at 5% degree of significance and 59 degrees of freedom is 2.00 for two-tailed test and 1.67 for one-tailed test.

    Peter is worried about the presence of heteroskedasticity in the given data. He checks the heteroskedasticity using Breusch-Pagan test. He runs a regression on the squared residuals with the independent variables and the result of that regression is given in Exhibit 2.

    Exhibit 2
    SS
    Regression 128.55
    Error 312.12
    Total 440.67


    The one-tailed critical value for a chi-square distribution for 5% level of significance is given in Exhibit 3.

    Exhibit 3
    Degrees of freedom Value of chi-square
    1 3.841
    2 5.991
    3 7.815


    Peter is also contemplating the addition of another independent variable liquidity premium in the Fama-French model (it will become Pastor-Stambaugh model after addition of that). He wants to check whether the addition of new independent variable is desirable or not. He checks that by adding another variable and by running the regression on the data and finds out that because of addition of that data, R2 value increased by 2.0%.

    1. What is the F-statistic value for the given multiple regression model?
    a) 0.70
    b) 13.09
    c) 40.67

    2. How much percentage of variation in the equity risk premium is unexplained by the regression model?
    a) 29.17%
    b) 41.22%
    c) 58.78%

    3. What is the required return on equity for Little Flower using Fama-French regression model if the market risk premium is 6%, Rsmall – Rbig = 2.5% and RHMB – RLBM = 1.5%? Assume the risk free rate to be 5.5%.
    a) 9.55%
    b) 15.05%
    c) 17.15%

    4. Is heteroskedasticity present in the given regression data?
    a) Yes, because the test statistic is greater than the critical value of 3.841
    b) Yes, because the test statistic is greater than the critical value of 7.815
    c) No, because the test statistic is lesser than the critical value of 7.815

    5. Should Peter include the additional independent variable liquidity premium in the Fama-French model?
    a) Yes, because R2 increased by 2.0% on addition of that independent variable
    b) Yes, because adjusted R2 increased on addition of that independent variable
    c) No, because adjusted R2 decreased on addition of that independent variable

    6. At 5% level of significance, is the beta of market (coefficient of market risk premium) statistically significant than 1?
    a) Yes, because the calculated t-statistic 4.0 is greater than the critical test statistic of 2.00
    b) Yes, because the calculated t-statistic 4.0 is greater than the critical test statistic of 1.67
    c) No

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