本帖最后由 Kakashi_8 于 2015-7-16 14:02 编辑
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. R/ V! v, l1 z0 _Question：6 Which of the following standards may be violated when investment advisors cover their own trading errors with compensating trades? A) 8 ~) M) ]" w8 n" g) L# o- j
. m$ Z4 U" f1 Q* B7 P | Prohibition Against Plagiarism. ' a3 F& P- U$ C, I; {9 D
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| Disclosure of Conflicts to Clients and Prospects. ( m1 y* X c0 G B9 \! x
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6 e; X4 O$ I7 N) ]( ~ | Reasonable Basis and Representations.
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| Independence and Objectivity.9 Y: m2 |6 q8 R# p. P' B9 @( a
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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) ( L% C' Z* e/ W) m% H" Y+ U
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| paid must be minimized. % v/ n# f" K) a, g
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2 ~1 ]- u$ e$ ?5 P0 k5 c | 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. ; Z8 ~+ T/ ^2 S- k; T$ L4 M
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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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# Q: {. p& `( f | The assumption of linear regression is that the residuals are heteroskedastic. O. |0 J5 w/ ] I1 Q3 P) {: ]
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| Heteroskedasticity may occur in cross-section or time-series analyses. 8 v2 `2 A* O, m, p8 P0 |
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8 ~& i2 A& f/ ] | Heteroskedasticity results in an estimated variance that is too large and, therefore, affects statistical inference.
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$ J2 V( C4 E4 n. u9 H | 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) 2 J1 x+ Q9 U9 A5 e$ s: u
0 F0 Z! F8 {# x2 G8 h& _ | -0.55
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# S7 _# d0 k* @* `1 N" y" d X* Q# [& f | 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) " F* M' w. o0 C! K) ~. N+ O
: X/ N9 Y( `5 H, X+ j0 U3 \0 G" p | H0: σA2 = σB2 versus Ha: σA2 ≠ σB2. , |5 D( A' ]: Z, K0 f8 W" Q
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" D/ ~$ a$ t. V, z | H0: σA2 = σ02 versus Ha: σA2 ≠ σ02. - y4 Y9 H" H! Y; D4 O: i1 k/ W- B# ?
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| H0: σA2 ≠ σB2 versus Ha: σA2 = σB2. & H8 [) h& g$ J, `
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* E4 X" W9 m) V% z2 m' w | H0: σA2 > σ02 versus Ha: σA2 < σ02. |
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