本文選題：非線性壓縮 + 線性壓縮�。� 參考：《中國(guó)管理科學(xué)》2017年08期

【摘要】：本文將非線性壓縮方法運(yùn)用到DCC和BEKK模型中,用非線性的壓縮估計(jì)量代替MMLE估計(jì)中初始的樣本協(xié)方差矩陣,大大提高了高維DCC和BEKK模型的估計(jì)效率,并突破性地使得橫截面維度大于時(shí)間維度時(shí),DCC和BEKK模型的有效估計(jì)成為可能。蒙特卡洛模擬發(fā)現(xiàn):非線性壓縮方法對(duì)于DCC和BEKK模型估計(jì)的優(yōu)化作用顯著,且優(yōu)化程度隨著橫截面維度和時(shí)間維度的比值增大而增加。實(shí)證分析進(jìn)一步說(shuō)明了非線性壓縮方法對(duì)于準(zhǔn)確估計(jì)高維條件協(xié)方差矩陣、從而提高組合選擇效率的重要作用。
[Abstract]:In this paper, the nonlinear compression method is applied to the DCC and BEKK models. The initial sample covariance matrix in the MMLE estimation is replaced by the nonlinear compression estimator, which greatly improves the estimation efficiency of the high-dimensional DCC and BEKK models. It also makes it possible to estimate the BEKK and DCC models when the cross section dimension is larger than the time dimension. Monte Carlo simulation shows that the nonlinear compression method plays an important role in the estimation of DCC and BEKK models, and the degree of optimization increases with the ratio of cross section dimension to time dimension. The empirical analysis further illustrates the importance of nonlinear compression method in estimating the high dimensional conditional covariance matrix accurately and improving the efficiency of combination selection.
【作者單位】： 華中科技大學(xué)經(jīng)濟(jì)學(xué)院;
【基金】：國(guó)家自然科學(xué)基金面上資助項(xiàng)目(71671070)
【分類(lèi)號(hào)】：F830.59;O212.1

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