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6.The lag length for the autoregressive and moving average parts are chosen to minimise the Schwartz Bayesian Criterion (SBC; Schwartz, 1978).

7.All ARIMA models seem to be well specified, as is indicated by relevant diagnostic tests for autocorrelation and heteroskedasticity.

8.It can be noted that across all routes, the adjusted coefficient of determination for changes in spot rates are higher than those of forward rates, indicating potentially higher predictability in spot rates than forward rates.

9.The next set of columns in Tables 3.1–3.2A present the estimates of coefficients of the VAR models. These are similar to the ARIMA model in terms of the appropriate number of lag lengths used and the diagnostic tests.

10.As expected, the adjusted coefficients of determination for the VAR models are slightly higher than those of the ARIMA model due to the use of extra information, namely, the lagged forward rates in the spot equation and vice versa.

2 Answers

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  • 小君
    Lv 6
    1 decade ago
    Favorite Answer

    6 。滯後長度為自回歸和移動平均線的部分是選擇,以盡量減少施瓦茨貝葉斯準則( SBC公司;施瓦茨, 1978年) 。

    7.所有ARIMA模型似乎很好指定的,這是表示,有關的診斷測試,為自和異方差。

    8.它可以指出,所有路線,調整係數測定的變化,在即期匯率高於遠期利率,表明潛在的更高的可預見性,在即期匯率比利率前進。

    9 。下一組列在表3.1 - 3.2a目前的估計係數的VAR模型。這些都是類似的向ARIMA模型,在條件適當的數目滯後長度的使用和診斷測試。

    10.預期,調整係數測定的VAR模型,稍微高於該ARIMA模型由於使用額外的信息,即滯後推進利率在現場方程,反之亦然。

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  • Thomas
    Lv 4
    1 decade ago

    6.自回歸和傳送平均值部分的落後長度被選擇使(SBC的施瓦茨Bayesian 標準減到最小; 施瓦茨,1978) .

    7.全部ARIMA 模型好像被指定得好,象相關的診斷測試對於autocorrelation 和heteroskedasticity 表明的那樣。

    8.它可以被注意到在全部路線的那, 與期貨匯率相比較,在即期匯率方面,被調整的在即期匯率方面的變化的確定系數比期貨匯率的高,表明潛在高的可預測性。

    9.在表格3.1的下一套專欄。 2一存在變量模式的系數的估計。 這些就使用的適當的落後長度的數量和診斷測試而言類似於ARIMA 模型。

    10.象期望的那樣, 變量模型的被調整的確定系數稍微有點高, 由於使用額外的訊息的ARIMA 模型的,即,在點方程式裡的被落後的期貨匯率反之亦然。

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