發(fā)布時間：2018-05-07 10:03

  本文選題：指數追蹤 + 折中路徑��； 參考：《數量經濟技術經濟研究》2017年05期

【摘要】：研究目標:構建了可以調節(jié)追蹤誤差和超額收益的增強型指數追蹤模型,并給出了廣義最小角度回歸算法(GLARS),用以計算調節(jié)參數作用下模型解的折中路徑。研究方法:通過模擬數據和五組世界主要股票市場指數的歷史數據,對本文提出的模型和算法與同類模型和算法進行了性能比較;同時追蹤上證50指數構建若干稀疏且穩(wěn)定的資產組合模型,通過信息比率等指標對投資組合進行評價。研究發(fā)現:本文構建的模型可用以構造權衡追蹤效果和超額收益,且稀疏的資產組合,GLARS算法相對傳統(tǒng)預設參數的算法具有良好的求解能力和計算速度。研究創(chuàng)新:引入調節(jié)參數平衡追蹤效果和超額收益,并針對中國股票市場的特點,在增強型指數追蹤模型施加非負約束;GLARS算法可遍歷所有折中意義下的最優(yōu)解。研究價值:本文提出的增強型指數追蹤模型在國內具有較強適用性,在保證資產稀疏性的前提下可以得到超額收益,同時豐富了目前投資組合中的方法論研究。
[Abstract]:Research objective: an enhanced exponential tracking model which can adjust the tracking error and excess return is constructed, and the generalized minimum angle regression algorithm is given to calculate the compromise path of the model under the action of adjusting parameters. Methods: through the simulation data and five groups of historical data of the world's major stock market indexes, the performance of the proposed model and algorithm is compared with that of the similar models and algorithms. At the same time, several sparse and stable portfolio models are constructed by tracking the Shanghai Stock Exchange 50 Index, and the portfolio is evaluated by information ratio and other indicators. It is found that the model constructed in this paper can be used to construct tradeoff between tracing effect and excess return, and the sparse portfolio GLARS algorithm has good solving ability and computing speed compared with the traditional algorithm with preset parameters. Research innovation: according to the characteristics of Chinese stock market and the characteristics of Chinese stock market, the GLARS algorithm can traverse the optimal solution in the sense of all compromises by introducing the adjusted parameter equilibrium tracking effect and excess return, and according to the characteristics of the Chinese stock market, applying non-negative constraints to the enhanced exponential tracking model. Research value: the enhanced index tracking model proposed in this paper has strong applicability in China, which can obtain excess returns on the premise of asset sparsity, and enriches the current research on portfolio methodology.
【作者單位】： 中央財經大學統(tǒng)計與數學學院;
【基金】：國家自然科學基金項目(71403310) 北京市社會科學基金項目(16LJB005) 中央財經大學青年科研創(chuàng)新團隊支持計劃;中央財經大學博士研究生重點選題支持計劃的資助 中央高校基本科研業(yè)務經費
【分類號】：F224.0
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本文編號：1856488