I think the given sample answer includes a reference (“non-synchronous” return data) to last year’s Andrew Lo assignment, for which I am not aware of 2009 reference, but still relevant - David

E1.02. [source: sample 2009 FRM Full Exam I. Question 02] You are asked by your boss to estimate the exposure of a hedge fund to the S&P 500. Though the fund claims to mark to market weekly, it does not do so and marks to market once a month. The fund also does not tell investors that it simply holds an ETF which is indexed to the S&P500. Because of the claims of the hedge fund, you decide to estimate the market exposure by regressing weekly returns of the fund on the weekly return of the S&P500. Which of the following properties correctly describes a property of your regression estimates?

• a. The beta of your regression will be one because the fund holds the S&P 500.
• b. The beta of your regression will be zero because the fund returns are not synchronous with the S&P 500 returns.
• c. The intercept of your regression will be positive, showing that the fund has a positive alpha when estimated using an OLS regression.
• d. The beta will be misestimated because hedge fund exposures are non‐linear.

My Adds:

• E1.02e. If the S&P 500 were a proxy for the market (which it isn’t because it is large cap; the S&P 1500 is nearer to a proxy), what does beta represent in the regression?
• E1.02f. As faithful disciples of Andrew Lo, among the 6-7 assumptions of the classical linear regression model (CLRM), which violation are we expecting here?
• E1.02g. Can we call the intercept hedge fund alpha? (source: Grinold)
• E1.02h. Is the alpha skill or luck (source: Grinold)?
• E1.02i. If the alpha is skill, is it the only skill; i.e., can the manager add value aside from alpha? (source: Grinold)

Answers here in forum or here in wiki.

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