本帖最后由 Kakashi_8 于 2015-7-16 14:02 编辑 * @ a1 m$ H+ G2 ^
" o5 Z! ?9 l0 Y3 ~Question：6 Which of the following standards may be violated when investment advisors cover their own trading errors with compensating trades? A) - T0 A- M- f. K6 w1 {* h+ [: L6 q
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| Prohibition Against Plagiarism. & E( a" `; ?5 K: V
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| Disclosure of Conflicts to Clients and Prospects.
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| C)
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| Reasonable Basis and Representations.
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| Independence and Objectivity.& l- k0 W* }& C, ?) r2 P
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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) 9 p) H+ i& N- Z5 W; J. D- D
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| paid must be minimized. / |8 c- M4 p6 b3 E
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| B) 0 W0 R4 A; e9 `- r2 N
. E' @& w1 w( Y1 @' ~; b | cannot be greater than normal unless the trades being placed are in compensation for a trading error.
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| C)
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| paid must be reasonable in relation to the research and execution services provided.
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, V7 G) I' K9 t: m% } | paid must be held in escrow for the benefit of the client. 5 Q. I0 S4 S' y( \/ a$ a8 r
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Question：8 Which of the following statements regarding heteroskedasticity is FALSE? A) - ~' T- V/ l& n }% ^
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| The assumption of linear regression is that the residuals are heteroskedastic.
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| B)
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| Heteroskedasticity may occur in cross-section or time-series analyses. 9 e4 G4 g. T/ s. H1 a' k- N% D6 ]
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| C)
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' Z" N5 z- |$ p F6 B, i/ [ | Heteroskedasticity results in an estimated variance that is too large and, therefore, affects statistical inference. $ \3 u! V2 p& U' W: `
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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)
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| -0.55
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| B)
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| 5.83
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| 2.83
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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 = σ02 versus Ha: σA2 ≠ σ02. 7 V& z/ K/ }0 R9 m- s8 I2 o6 i
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| H0: σA2 ≠ σB2 versus Ha: σA2 = σB2.
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| H0: σA2 > σ02 versus Ha: σA2 < σ02. |
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