DURING 2009, THE “MISFIT” ACTIVE RETURN EARNED BY BRIGG’S INVESTME...

24. During 2009, the “misfit” active return earned by Brigg’s investments was closest to: A. 0.3%. B. 0.4%. C. 0.7%. By accessing this mock exam, you agree to the following terms of use: This mock exam is provided to currently-registered CFA candidates. Candidates may view and print the exam for personal exam preparation only. The following activities are strictly prohibited and may result in disciplinary and/or legal action: accessing or permitting access by anyone other than currently-registered CFA candidates; copying, posting to any website, emailing, distributing and/or reprinting the mock exam for any purpose. Brian O’Reilly Case Scenario Brian O’Reilly is a capital markets consultant for the Tennessee Teachers’ Retirement System (TTRS). O’Reilly is meeting with the TTRS board to present his capital market expectations for the next year. Board member Kay Durden asks O’Reilly about the possibility that data measurement biases exist in historical data. O’Reilly responds: “Some benchmark indexes suffer from survivorship bias. For example the returns of failed or merged companies are dropped from the data series resulting in an upward bias to reported returns. This may result in an overly-optimistic expectation with respect to future index returns. Another bias results from the use of appraisal data in the absence of market transaction data. Appraisal values tend to be less volatile than market determined values for identical assets. The result is that calculated correlations with other assets tend to be biased upward in absolute value compared to the true correlations and the true variance of the asset is biased downward.” Board member Arnold Brown asks O’Reilly about the use of high-frequency (daily) data in developing capital market expectations. O’Reilly answers: “Sometimes it is necessary to use daily data to obtain a data series of the desired length. High-frequency data are more sensitive to asynchronism across variables and, as a result, tend to produce higher correlation estimates.” Board member Harold Melson noted he recently read an article on psychological traps related to making accurate and unbiased forecasts. He asks O’Reilly to inform the board about the anchoring trap and the confirming evidence trap. O’Reilly offers the following explanation: “The anchoring trap is the tendency for forecasts to be overly influenced by the memory of catastrophic or dramatic past events that are anchored in a person’s memory. The confirming evidence trap is the bias that leads individuals to give greater weight to information that supports a preferred viewpoint than to evidence that contradicts it.” The board asks O’Reilly about using a multifactor model to estimate asset returns and covariances among asset returns. O’Reilly presented the factor covariance matrix for global equity and global bonds shown in Exhibit 1 and market factor sensitivities and residual risk shown in Exhibit 2. Exhibit 1 Factor Covariance Matrix Global Equity Global Bonds Global Equity 0.0022 0.0225 Global Bonds 0.0025 Exhibit 2 Market Factor Sensitivities and Residual Risk Sensitivities Residual Risk Global Equity Global Bonds