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The Stock Index Method Completely Copy And Its Rebalancing Strategy Research

Posted on:2013-06-10Degree:MasterType:Thesis
Country:ChinaCandidate:J ChenFull Text:PDF
GTID:2249330395450386Subject:Financial project management
Abstract/Summary:PDF Full Text Request
Because of the Chinese bear market and the recession of the global economic in recent years, Index funds are welcomed by more and more investors. The amounts of the Index funds increase as well as the varieties. At the same time index derivative products become important aspects in the financial market especially after the introduction of stock index futures, Investors and institutional investors often need to build a portfolio of indexation. The index tracking model is a foundation of the structural index portfolio. A good index-tracking model should minimize the tracking error respect to the target index. The main goal of this thesis is to use non-fully copy method to track a stock index. The target index is mainly CSI300stock index in the article. This paper wants to achieve two research objectives:firstly constructing index tracking portfolio with different methods. There are three index tracking methods introduced in this paper:linear tracking optimization method, cointegration optimized index tracking, index-tracking of the CVaR constraint optimization method. These three models have different objective functions and constraints. This paper discusses these three methods, and compares them with each other. ETF index tracking portfolio is widely used by Chinese financial institutions at present. This paper will also compare it with the previous three models. Secondly, this article will discuss the re-balancing strategy of index tracking portfolio, in order to gain the optimal time length of the index tracking portfolio rebalancing.
Keywords/Search Tags:Index Tracking, Linear Tracking Optimization Method, Cointegration OptimizedIndex Tracking, Index-tracking of the CVaR Constraint Optimization Method, Index TrackingPortfolio Rebalancing
PDF Full Text Request
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