CFA Institute CFA-LEVEL-1 Online Practice Questions and Exam Preparation

CFA Institute CFA-LEVEL-1 Online Questions & Answers

• Question 2471:

  Which of the following events would a technical analyst interpret as bullish?

  A. a decline in the ratio of specialist's short sales to total short sales
  B. all of these answers
  C. an increase in debit balances in brokerage accounts
  D. when the proportion of bullish speculators declines to 30 percent
  B. all of these answers

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  Explanation

  (1)

  Decline of specialist's short sale ratio to below 30%;

  (2)

  Increase in debit balance means that investors have to post increasing margin to for more investments;

  (3)

  Percentage of bullish stock futures speculators decline (because if market is bullish then speculation is irrelevant) - are all signs that the market may be turning bullish.

• Question 2472:

  Firms A and B are identical. In one year, Firm A's statements have the beginning inventory understated and the ending inventory overstated. Then,

  I. A's tax payment is higher.

  II. B's tax payment is higher.

  III. B shows a higher income.

  IV.

  A shows a higher income.

  A. I and IV
  B. II and III
  C. I and III
  D. II and IV
  A. I and IV

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  Explanation

  COGS = Beginning inventory - Ending inventory + Purchases. Hence, if BI is understated and EI overstated, COGS is understated, implying income is overstated. Hence, Firm A will show higher income and pay higher taxes. It should be remembered that implicit in the use of the above inventory equation is the assumption that there have been no write-downs or write-ups in the inventory.

• Question 2473:

  Which of the following is true?

  A. During a recession, cyclical unemployment will be low.
  B. Frictional unemployment implies a lack of available jobs.
  C. When an economy is at full employment, actual unemployment will be less than the natural unemployment.
  D. When actual GDP equals potential GDP, the actual unemployment will equal the economy's natural unemployment.
  D. When actual GDP equals potential GDP, the actual unemployment will equal the economy's natural unemployment.

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  Explanation

  Under full employment, the rate of unemployment will be equal to the natural rate of unemployment given the economy's frictional and structural characteristics. Potential GDP is defined as the amount of output that could be expected at full employment. Therefore, at potential GDP, the rate of unemployment is equal to the natural rate of unemployment.

• Question 2474:

  Duncan Manz believes that he has found an error in a sample CFA Study Program question. Prior to e-mailing the provider about the error, he discusses his logic with Julia Cook, a fellow finance student at the Hess School of Business. Manz does not believe that the following question provides enough information to completely answer the question. Cook disagrees. Who is correct ?Manz or Cook? And, if Cook is correct, what is the correct answer? Question: An investorportfolio currently consists of 100% of stocks that have a mean return of 18 percent and an expected variance of 0.0625. The investor plans to diversify slightly by replacing 30 percent of her portfolio with U.S. Treasury bills that earn 4. 25 percent. Assuming the investor diversifies, what are the expected return and expected standard deviation of the portfolio?

  A. Cook is correct. The portfolio's expected return is 13. 875%and the expected standard deviation is 4. 375%.
  B. Cook is correct. The portfolio's expected return is 18.000% and the expected standard deviation is 15. 250%.
  C. Manz is correct. There is not enough information to completely answer the question.
  D. Cook is correct. The portfolio's expected return is 13. 875% and the expected standard deviation is 17. 500%.
  D. Cook is correct. The portfolio's expected return is 13. 875% and the expected standard deviation is 17. 500%.

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  Explanation

  Cook is correct. Since Treasury bills (T-bills) are consideredrisk-free, we know that the standard deviation of this asset and the correlation between T-bills and the other stocks is 0. Thus, we can calculate the portfolio expected return and

  standard deviation.

  Step 1: Calculate the expected return:

  Expected ReturnPortfolio= (wT-bills* ERT-bills) + (wStocks* ERStocks)= (0.30) * (0.0425) + (1.00 - 0.30) * (0.18) = 0.13875, or 13. 875%.

  Step 2: Calculate the expected standard deviation:

  When combining a risk-free asset and a risky asset (or portfolio of risky assets), the equation for the standard deviation of 1,2= [(w12)( 12) + (w22)( 22) + 2w1w2 1 2r1,2]1/2reduces to: Portfolio= [(wStocks)( Stocks)] = 0.70 *

  0.06251/2= 0.17500, or 17. 500%. (Remember to convert variance to standard deviation.)

• Question 2475:

  The allowance for uncollectible accounts is

  A. a reduction in revenue
  B. a liability
  C. long-term asset
  D. a contra account
  D. a contra account

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  Explanation

  Allowance for Uncollectible Accounts, sometimes referred to as Bed Debt Reserve, is a contra account to Accounts Receivable.

• Question 2476:

  A financial analyst with Smith, Kleen, and Beetchnutty is examining shares of Claypool Manufacturing for possible investment. Assume the following information:

  Sales: $50,000,000 Fixed costs: $33,000,000 Variable costs: $8,500,000 Interest expense: $900,000 Tax rate: 35% Weighted Average Cost of Capital: 11.50% Beta coefficient: 0.96 Common shares outstanding: 4,000,000 Using this information, what are the earnings per share (EPS) for Claypool Manufacturing?

  A. $1.34
  B. $1.40
  C. The answer cannot be determined from the information provided.
  D. $1.70
  E. $1.24
  F. $1.11
  E. $1.24

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  Explanation

  The EPS figure is perhaps the single most popular term in the field of conventional equity investments, along with the Price-to-Earnings Ratio (P/E). Any glance into financial media and business periodicals will undoubtedly uncover numerous

  instances in which the EPS figure is cited or discussed. While quite popular and useful, most investors, and many business professionals, undoubtedly do not understand the mechanics behind the EPS calculation, and an investigation into

  the components of EPS is a valuable learning experience. The EPS calculation is found by the following equation:

  {EPS = [(Sales - Fixed Costs - Variable Costs - Interest Expense)(1 - Tax Rate)] / [# of Common Shares Outstanding]}

  Additionally, the EPS figure can be found by:

  {EPS = [(EBIT - Interest Expense)(1 - Tax Rate) / # of Common Shares Outstanding]} Incorporating the given information into the first EPS equation will yield the following: {EPS = [($50,000,000 - $33,000,000 - $8,500,000 - $900,000)(1 0.35)] / 4,000,000} = $1.24.

• Question 2477:

  The portion of the supplies inventory that has been consumed during the fiscal period is classified as

  A. an expense
  B. an increase in retained earnings
  C. a liability
  D. an asset
  A. an expense

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  Explanation

  In accordance with the matching rule, the amount of an asset such as supplies that has been consumed during the accounting period must be recorded and classified as an expense for the period.

• Question 2478:

  Which of the following statements is false regarding confidence levels and/or tests of significance?

  A. In most hypothesis testing, the confidence level is equal to 0.10, 0.05, and 0.01. B. All else equal, the confidence interval of a hypothesis test with a 5% level of significance is less than the confidence interval for a hypothesis test with a 1% level of significance.
  C. In most hypothesis tests, the power of the test is equal to (1 - alpha).
  D. More than one of these answers is incorrect.
  E. The significance level of a test is equal to (1 - confidence level).
  F. The power of a test is equal to the confidence level.
  D. More than one of these answers is incorrect.

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  Explanation

  More than one of these answers is incorrect. Specifically, in most hypothesis tests, the significance level is equal to the probability of a Type I error (denoted by the Greek letter alpha) and the power of the test can be found by (1 - beta), where beta represents the probability of a Type II error. Remember that statisticians are much more concerned with the probability of a Type I error, which is defined as the act of incorrectly rejecting the null hypothesis. A Type II error, which is defined as the act of incorrectly failing to reject the null hypothesis, is much more difficult to predict. Second, power of a test is not equal to the confidence level of the test.

• Question 2479:

  What annual interest rate, compounded annually, will cause a deposit of $850 to become $1,475 in 10 years?

  A. 5. 67%
  B. 7. 60%
  C. 7. 88%
  D. 4. 65%
  E. 5. 50%
  A. 5. 67%

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  Explanation

  On the BAII Plus, press 10 N, 850 PV, 1475 +/- FV, 0 PMT, CPT I/Y. On the HP12C, press 10 n, 850 PV, 1475 CHS FV, 0 PMT, i. Make sure that the BAII Plus has the P/Y value set to 1.

• Question 2480:

  Walter Jennings, a quantitative analyst with Smith, Kleen and Beetchnutty Brokerage, has just been informed of an important error in one of his recent statistical endeavors. Specifically, in one hypothesis test, Mr. Jennings failed to reject a null hypothesis that later was proven to be false. Which of the following best describes this type of error in hypothesis testing? Further, if the confidence level of the test were increased, would the probability of this error increase, decrease, or is this probability difficult to determine?

  A. Type II error; difficult to determine
  B. Type I error; difficult to determine
  C. Type I error; decrease
  D. Type II error; decrease
  E. Type I error; increase
  F. Type II error; increase
  A. Type II error; difficult to determine

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  Explanation

  In this example, Mr. Jennings has incorrectly failed to reject a null hypothesis. This type of error in hypothesis testing is called a Type II error. In hypothesis testing, the Type I error is given more attention than the Type II error. A Type I error is defined as the act of incorrectly rejecting the null hypothesis. In most hypothesis tests, the probability of a null hypothesis is equal to the significance level of the test. A significance level of 0.01, for example, indicates that a 1% chance exists that the null hypothesis will be rejected when it is indeed true. Another way to think of the probability of a Type I error is to observe the following relationship: {Probability of a Type I error = (1 - confidence level)}. For example, a confidence level of 95% leaves a 5% probability of a Type I error occurring. If this confidence level were to increase to say, 98%, then the probability of a Type I error would reduce to 2%. While a relationship exists between the confidence level for a hypothesis test and the probability of a Type I error, the relationship between confidence levels and Type II errors is not as explicit. The probability of a Type II error is inherently difficult to quantify, and as such, few hypothesis tests call for a determination of the probability of a Type II error. If the confidence level of a hypothesis test to be increased, it would be difficult to determine what effect, if any, this would have on the probability of a Type II error.