The Research Of Index Portfolio Based On Tracking Error

Indexing investment generates in the1970s, after40years of development, it has become one of the main investment strategies in the world. Indexing investment is a kind of passive investment pattern which achieves an average return of stock market through the full decentralization and passive management, for the purpose of replicating and tracking a stock market index. It has neither the excess risk nor timing restrictions, and has many advantages. So its rapid development provides investors with a variety of user-friendly investment opportunities. Therefore, there is an important theoretical and academic value to get an accurate understanding of the meaning of indexing investment and study its applicability in China’s capital markets.This paper elaborates the conception of the indexing investment, the advantages of indexing investment and the process of indexing development, then analyses the conception of tracking error and the traditional measure of tracking error. Then we choose50ingredients stocks of Shanghai Index180as the optimized objects, technically construct the optimal index investment portfolio by minimizing five kind of objective functions, and test the achievements of our portfolio by using out of the sample data. Finally we introduce the linear tracking error model--the mean absolute deviation model, and we build a linear programming model with the transactional costs. In the model, we talk about the rebalancing of tracking portfolio, the budgetary constraints and position constraints. Then according to different preferences on tracking error and transaction costs, we establish a multi-objective model of the index tracking problem. At last, we discusses the regular rebalancing and non-rebalancing of the tracking portfolio. The main conclusions are as follows.(1) By minimizing five kind of objective functions to extract the superiorly weight and the superiorly quantity of ingredient stocks, and test the achievements of our portfolio by using out of the sample data, we find the best index optimization methods that conform to the actual situation of China’s stock market is MAD Model. (2) In the process of rebalancing the tracking portfolio, investors need to consider the transaction costs, tracking error, adjusting frequency of the portfolio, and coordinate these factors. For regular adjustments of the portfolio, we need to weigh the transaction costs and the tracking error, and then choose the proper adjusting time interval to minimize the objective function. For non-regular adjustments of the portfolio, we will select a proper threshold in order to get a better tracking performance.