Translated Title
Portfolio strategies of Shanghai ＆ Hong Kong stock markets from the perspective of fractal theory
Translated Abstract
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.
Translated Keyword
fractal
Mean-DCCA model
Mean-MF-DCCA model
portfolio
