本帖最后由 Kakashi_8 于 2015-7-16 14:02 编辑
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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) : P. X+ I+ ?" }1 k7 P7 p: a
' x) f% ~2 m5 o( @7 v | Prohibition Against Plagiarism. 1 }6 V) ?2 x. e: y( d! t
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6 q8 l/ n9 }9 Y | Disclosure of Conflicts to Clients and Prospects. + U7 f% I' r/ U8 w
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+ W! t" _4 |; ]6 a7 c7 A5 S& `$ H | Reasonable Basis and Representations.
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( s* F% E4 |/ E% i6 _ | 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)
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| paid must be minimized.
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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. * U9 k) C) r6 r6 Y* `2 u. Q+ c* z
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| C)
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& j3 O3 j- L( x | paid must be reasonable in relation to the research and execution services provided.
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/ P( R. ~# \- j2 m: d' r3 p5 f | paid must be held in escrow for the benefit of the client. l+ U4 S. s' G) u
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Question:8 Which of the following statements regarding heteroskedasticity is FALSE? A)
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| The assumption of linear regression is that the residuals are heteroskedastic. , W: H- X7 i- W- X' a
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| Heteroskedasticity may occur in cross-section or time-series analyses.
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| C)
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1 Z* _' M! e) Q! F+ A* Q5 B | Heteroskedasticity results in an estimated variance that is too large and, therefore, affects statistical inference. . ~1 ?" e, y) ?& Z, ]: _2 I' I
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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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| 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) % F7 I9 D$ ]* }5 w& K' X
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| H0: σA2 = σB2 versus Ha: σA2 ≠ σB2.
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| B)
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| H0: σA2 = σ02 versus Ha: σA2 ≠ σ02. 3 o0 s8 _+ P9 q: x3 c
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! s8 w# P* I1 s0 M% n$ s# `. } | H0: σA2 ≠ σB2 versus Ha: σA2 = σB2.
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, j& H" ^1 A, F! p% d- w | H0: σA2 > σ02 versus Ha: σA2 < σ02. | ; w% G% d% Q# q4 s6 z% c: [+ [7 d
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