本帖最后由 Kakashi_8 于 2015-7-16 14:02 编辑 5 k/ Q+ U+ d/ y- p- |
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Question：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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0 r& {1 z/ j: ?' Z; k; W, n | Prohibition Against Plagiarism. 9 R7 @ Q/ f, X' i+ r3 o
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| Disclosure of Conflicts to Clients and Prospects.
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| Reasonable Basis and Representations.
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* N* x9 `* Z4 T" u- P | Independence and Objectivity.# N) ^# q" I1 [4 w
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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) $ e' j U6 k; X. o$ V
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| paid must be minimized. ! u- b& X4 }1 p3 ?
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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. % w3 T# { `) P' i1 i! | C3 u
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| C) $ p$ a1 ?" B( z5 S { w
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| paid must be reasonable in relation to the research and execution services provided. : x: l# p: m# P/ p" L. @" K
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| D)
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| 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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0 d$ E2 M! Q1 s, I9 |" ], X | The assumption of linear regression is that the residuals are heteroskedastic. * o5 j0 U" O' E+ ]# k l( Q
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| Heteroskedasticity may occur in cross-section or time-series analyses.
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| C)
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| Heteroskedasticity results in an estimated variance that is too large and, therefore, affects statistical inference. 8 k, e. r/ _$ W0 q$ o8 Z# s; Y* Z
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| D)
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| Conditional heteroskedasticity is the case in which the residuals are correlated with the values of the independent variables. 8 s7 H; Q* L. R5 Q
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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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( I$ b% |2 m) t. ] u; B% n; L | -0.55
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( z' m6 l; W+ V& B0 M* m | 5.83
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| C)
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5 t: i8 l0 k# b- g7 J6 o' f1 a# v | 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)
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7 d/ \, {" M/ M% Y. I$ t4 ] | H0: σA2 = σB2 versus Ha: σA2 ≠ σB2. ; I8 s3 \/ S/ l9 B- K: v
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| B)
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* m& @, |! Q" p | H0: σA2 = σ02 versus Ha: σA2 ≠ σ02.
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/ Z- `! r, [/ Y( B9 l | H0: σA2 ≠ σB2 versus Ha: σA2 = σB2.
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| H0: σA2 > σ02 versus Ha: σA2 < σ02. |
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