本帖最后由 Kakashi_8 于 2015-7-16 14:02 编辑 ! M, d6 c) I. h$ n/ A) a4 m4 ^0 t
! [6 L# q. K7 I1 HQuestion：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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| Prohibition Against Plagiarism. ) b8 B: }0 ?! |' H# ~' N
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| B)
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, `$ K! \8 y/ T* t | Disclosure of Conflicts to Clients and Prospects.
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| C)
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6 `. w2 M( r! @# G: ] | Reasonable Basis and Representations.
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| D)
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8 Z+ k9 F' V& [9 c1 N L$ T | Independence and Objectivity.1 t" t2 u3 m, O! N( s* R! V
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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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& u7 P8 o8 G5 F- \* r( Y | paid must be minimized.
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| B)
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- L4 v" D9 G7 A0 B1 _5 Q | 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.
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| D)
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| paid must be held in escrow for the benefit of the client. 1 C7 g0 P3 l X
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Question：8 Which of the following statements regarding heteroskedasticity is FALSE? A)
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, @" ]$ X' r7 U5 T# d6 N+ X" b | The assumption of linear regression is that the residuals are heteroskedastic.
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7 W" V2 P f/ g! Y, C | Heteroskedasticity may occur in cross-section or time-series analyses.
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n( t% u) \# p$ b | Heteroskedasticity results in an estimated variance that is too large and, therefore, affects statistical inference. 0 G2 z: v4 p6 Q! u
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3 }' |1 w+ Z/ R1 }9 o0 d | Conditional heteroskedasticity is the case in which the residuals are correlated with the values of the independent variables. 5 H" e8 K6 I$ F5 r7 w2 ^3 a
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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) ! k* w" J% T( i, D* V% N' q% p
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| B)
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| 5.83
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l. v& a* K9 o- t( t) m8 V( L% a8 t | 6.50
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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) 1 _6 k5 D! r1 K+ H$ R; s- X, H* s
) | a1 |/ e! N: X3 A | H0: σA2 = σB2 versus Ha: σA2 ≠ σB2. 0 ^# K1 G# H9 N) i; n! m
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6 q u) F* T9 M" l7 h1 G0 T1 ] | H0: σA2 = σ02 versus Ha: σA2 ≠ σ02.
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: D1 W0 U% q/ k! U | H0: σA2 ≠ σB2 versus Ha: σA2 = σB2. 6 J$ D: g$ z5 ^; k* g: E: ^
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1 u+ d, B: ^2 \$ O0 {, Q | H0: σA2 > σ02 versus Ha: σA2 < σ02. |
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