FRM一級數(shù)量分析例題解析linear regression

發(fā)布時間：2025-06-27 14:35編輯：融躍教育FRM

Bob, FRM and Joy, FRM are planning to do a regression analysis. They discuss specifying the stock return equation they wish to estimate. Bob proposes the specification E(Yi |Xi)= B0+(B1)×(X^2). Joy process the specification (Yi |Xi)= B0+(B1^2×Xi). Which, or either, is appropriate when applying linear regression?

A. Neither the specification of Bob nor that of Joy.

B. The specification of Bob but not that of Jay.

C. Both the specification of Bob and Jay.

D. The specification of Jay but not that of Bob.

答案：B

解析：線性回歸(不是線性函數(shù))，要求系數(shù)是線性的，對變量是否是線性沒有要求；也就是說變量可以是線性的，也可以是非線性的。

Joy 的描述中B1^2 不是線性的，所以這個不是線性回歸

關(guān)聯(lián)考點：線性回歸假設(shè)之線性易錯點分析：線性回歸(不是線性函數(shù))，要求系數(shù)是線性的，而不是自變量是線性的。只要系數(shù)β是線性的就稱為線性回歸。這個問題弄錯的原因是，大家把“線性回歸方程”等價于“線性函數(shù)”,兩者的概念不一樣。

To test the hypothesis that the autocorrelations of a time series are jointly equal to zero based on a small sample, an analyst should most appropriately calculate

A. a Ljung-Box (LB) Q-statistic.

B. a Box-Pierce (BP) Q-statistic.

C. either a Ljung-Box (LB) or a Box-Pierce (BP) Q-statistic.

D. neither a Ljung-Box (LB) nor a Box-Pierce (BP) Q-statistic.

答案：A

解析： The LBQ-statistic is appropriate for testing this hypothesis based on a small sample.

關(guān)聯(lián)考點：白噪音檢驗、BPQ檢驗、L-BPQ檢驗

易錯點分析：相對于Box-Pierce (BP) Q-statistic，Ljung-Box (LB) Qstatistic更加適合小樣本檢驗。

關(guān)鍵詞： FRM一級真題

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