本帖最后由 Kakashi_8 于 2015-7-16 14:02 编辑
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3 n; c5 E: b% ]$ C/ LQuestion：6 Which of the following standards may be violated when investment advisors cover their own trading errors with compensating trades? A)
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( j+ N- v5 F- h) V& r* J | Prohibition Against Plagiarism. % W' ^ v+ r1 F) e4 M B
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% H4 T: U7 I, K4 U+ y% `# D/ D | Disclosure of Conflicts to Clients and Prospects. # i7 k+ R+ n/ \: l- M$ s
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% ]) E6 o# ?9 R6 S | Reasonable Basis and Representations. 3 F- }/ j: ?# @) J
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| Independence and Objectivity.! X% R- [# m( H8 {/ a
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Question：7 Which of the following is one of the four requirements for meeting fiduciary obligations with regard to soft dollar arrangements? Commissions: A)
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5 N$ S ]5 _. z% [ | paid must be minimized. ) ?3 ]2 w1 x( h, N4 Q# P/ t! h, C
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| B)
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| cannot be greater than normal unless the trades being placed are in compensation for a trading error.
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| paid must be reasonable in relation to the research and execution services provided. : S; X( \, q6 V& w1 z
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S- Y ?6 C' M' Y. A | paid must be held in escrow for the benefit of the client.
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Question：8 Which of the following statements regarding heteroskedasticity is FALSE? A)
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| The assumption of linear regression is that the residuals are heteroskedastic.
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| Heteroskedasticity may occur in cross-section or time-series analyses.
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9 u$ h1 }) x; W- M5 J& D | Heteroskedasticity results in an estimated variance that is too large and, therefore, affects statistical inference. " C! L Y1 z. V- W7 p# H2 G! H) a
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| Conditional heteroskedasticity is the case in which the residuals are correlated with the values of the independent variables.
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Question：9 Given: Y = 2.83 + 1.5X What is the predicted value of the dependent variable when the value of an independent variable equals 2? A) X h0 X$ S. s% K0 Y$ A
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2 S0 I! P- H& N% I* b5 i& \ | 5.83
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Question：10 The variance of 100 daily stock returns for Stock A is 0.0078. The variance of 90 daily stock returns for Stock B is 0.0083. What are the hypotheses to test whether these variances are different from one another? A)
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| H0: σA2 = σB2 versus Ha: σA2 ≠ σB2.
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| B)
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3 e! V- _# r6 k& H | H0: σA2 = σ02 versus Ha: σA2 ≠ σ02. # I! Q2 {4 ^0 J3 {
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| H0: σA2 ≠ σB2 versus Ha: σA2 = σB2. 8 V- r# N- @- U% i- R& k! k
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| H0: σA2 > σ02 versus Ha: σA2 < σ02. |
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