本帖最后由 Kakashi_8 于 2015-7-16 14:02 编辑 8 ?3 l; Q7 R8 K) |% a% n k
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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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| Prohibition Against Plagiarism. ( o: D* i7 x, J- P
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* X" s# T! X! N& ]3 o$ b, C | Disclosure of Conflicts to Clients and Prospects.
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0 U" u. L4 T( ?9 m+ p | Reasonable Basis and Representations.
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| 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) . B* ^: d d4 R- p1 A8 W4 h
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| B) * q6 o9 E9 Z) r4 Y: J6 E8 f- f
2 @) \& m( a7 t | cannot be greater than normal unless the trades being placed are in compensation for a trading error. & k4 e7 r& |- c- Q: c
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| paid must be reasonable in relation to the research and execution services provided. , g2 h6 e+ ?* b/ t
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| paid must be held in escrow for the benefit of the client. " ]( ?% S' Z4 Q* v. t1 R
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Question:8 Which of the following statements regarding heteroskedasticity is FALSE? A) ( i1 X8 b0 {/ u; o4 Q
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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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| Heteroskedasticity results in an estimated variance that is too large and, therefore, affects statistical inference. 4 ^% t6 J3 q/ u+ S
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| Conditional heteroskedasticity is the case in which the residuals are correlated with the values of the independent variables. : |' q8 V0 B# w8 l* w6 Y3 w
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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) ' _3 G a: s7 U. e/ t: X; u5 |& h
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| B)
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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) $ n p5 P, T. _$ s+ @8 Q) ~
t3 j6 s3 _8 ~7 z: z5 E; _: k | H0: σA2 = σB2 versus Ha: σA2 ≠ σB2. + J# R# X: x' f4 Y
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| H0: σA2 = σ02 versus Ha: σA2 ≠ σ02. 8 B7 ~* C1 y: i$ I: G
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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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