标题： 基于聚类方法的动态投资组合策略 显示英文标题

标题： Dynamic portfolio strategy using clustering approach

摘要： 投资组合优化问题是资产管理中最重要的问题之一。 本文提出了一种新的动态投资组合策略，该策略基于中国股市中MST网络的时间变化结构，在使用最优投资组合进行投资时进一步考虑了市场状况。 一种投资组合策略包括两个阶段：在选择期内通过选择中心股票和外围股票，利用五个拓扑参数（即度数、介数中心性、基于度数准则的距离、基于相关性准则的距离和基于距离准则的距离）来选择投资组合，然后在投资期内使用这些投资组合进行投资。 最优投资组合是通过在选择期和投资期的不同市场状况组合下比较中心投资组合和外围投资组合来选择的。 我们论文中的市场状况是通过上涨指数的交易日数量或上涨指数交易日幅度之和与总交易日数量的比率来识别的。 我们发现，当市场处于上涨条件时，或者当选择期内市场稳定或上涨且投资期内市场处于稳定条件时，中心投资组合的表现优于外围投资组合。 我们还发现，当选择期内市场稳定而投资期内市场下跌时，外围投资组合的表现优于中心投资组合。 实证测试是基于最优投资组合策略进行的。 在所有可能的基于不同参数选择投资组合和不同标准识别市场状况的最优投资组合策略中，我们最优投资组合策略中的$65\%$在上海证券市场中表现优于随机策略，其比例为$70\%$在深圳证券市场。 显示英文摘要

摘要： The problem of portfolio optimization is one of the most important issues in asset management. This paper proposes a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: selecting the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, i.e., degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion, then using the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index or the sum of the amplitudes of the trading days with rising index to the total number of trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that the peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all the possible optimal portfolio strategy based on different parameters to select portfolios and different criteria to identify market conditions, $65\%$ of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market and the proportion is $70\%$ for the Shenzhen A-Share market.