基于分形视角下的沪港股市投资组合策略

针对已有研究的不足,为满足不同交易周期投资者的实际需求,将分形研究方法与传统投资组合模型相结合,考虑多时间标度和不同波动幅度因素,构建了单分形投资组合模型(MeanDCCA)和多重分形投资组合模型(Mean-MF-DCCA).依托"沪港通"平台,采用构建的模型,进行沪港股市组合投资,并对样本外效果进行检验和分析.结果表明:沪港股市间结构存在着标度效应和长记忆性,且具有多重分形特征;与传统的投资策略相比,单分形投资组合策略能够取得更佳的组合效果;多重分形投资组合策略通过选择合适的q阶,实证表明将会明显改善单分形投资组合策略,增强投资方案的盈利能力、提高夏普比率以及为不同风险偏好投资者创造额外效用.此研究对资产优化配置、风险管理以及沪港股市间相依结构刻画等方面具有重要的实际意义.

Portfolio strategies of Shanghai & Hong Kong stock markets from the perspective of fractal theory

In consideration of the deficiency of existing research, Mean-DCCA and Mean-MF-DCCA models are proposed by combining fractal research method with traditional portfolio theory in order to meet the actual demand of investors in different transaction cycles. The factors of time scales and different fluctuation ranges are taken into account in these models. The models are used to conduct portfolio strategies in Shanghai & Hong Kong stock markets by means of Shanghai-Hong Kong stock connect program, after which the effects of out-of-sample are tested and analyzed. The empirical results show that, first, the market structure of Shanghai-Hong Kong presents scales effect, long memory and multifractal characteristics; second, compared with the traditional strategies, the Mean-DCCA portfolio strategies are proved to achieve better effects; finally, the Mean-MF-DCCA portfolio strategies, by choosing an appropriate multifractal q-order, will significantly improve the single fractal portfolio strategies, enhance investment project profitability and Sharp Ratios, and create additional utility for investors with different risk preferences. This study is of great practical significance to the optimal allocation of assets, risk measurement and management, as well as the delineation of dependence structure of Shanghai & Hong Kong stock markets.