本帖最后由 Kakashi_8 于 2015-7-16 14:02 编辑
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/ P$ S* o& W, O5 L, K/ J3 @( ?; Q5 bQuestion:6 Which of the following standards may be violated when investment advisors cover their own trading errors with compensating trades? A) 6 z. r4 C5 l! L* ^/ b( K; H1 _
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| Prohibition Against Plagiarism.
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| B)
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2 O% p2 h, Z& t | Disclosure of Conflicts to Clients and Prospects.
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: h: {$ h3 N( U$ O, r3 M | Reasonable Basis and Representations. / L3 f; }& M2 p! Z
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* I7 k5 n/ F6 S: ?) g$ | | Independence and Objectivity.
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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) 4 u; M1 |3 w/ h2 X' w1 a K
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| paid must be minimized. ' H- c. H9 z- g. @
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! q# i3 _% j) t | 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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2 W8 k6 e6 n$ [' p. { | 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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. C' M" r' m$ {: J' X | The assumption of linear regression is that the residuals are heteroskedastic.
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& H$ B1 H7 w- i | Heteroskedasticity may occur in cross-section or time-series analyses. - ~5 K6 U" ~2 `
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( b5 E P8 S5 S% o. k; t) k6 {3 x' B) P | Heteroskedasticity results in an estimated variance that is too large and, therefore, affects statistical inference. , x) c# [* h( Z0 H8 |' L
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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) ; ]9 Q& }1 U9 f
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* A2 B, k* u4 n7 Y* |- | G | 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. & `5 |& J; A$ @. z( R. E2 k
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) B8 n$ h; S: w. @' V& Z3 S. l- E | H0: σA2 = σ02 versus Ha: σA2 ≠ σ02.
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| H0: σA2 ≠ σB2 versus Ha: σA2 = σB2.
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( ?" P. K, A4 \6 n/ z | H0: σA2 > σ02 versus Ha: σA2 < σ02. |
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