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基于分位数随机森林的科技类ETF配置策略
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ETF量化配置策略更新(250829)
Yin He Zheng Quan· 2025-09-02 11:35
Group 1 - The macro timing strategy has an annualized return of 7.08% and a Sharpe ratio of 1.34 as of August 29, 2025, with the latest portfolio including various ETFs such as the CSI 500 ETF (8.35%) and government bond ETFs (38.21%) [2][4][8] - The momentum strategy has an annualized return of 20.22% since 2020, with a recent portfolio allocation including the CSI Digital Economy Theme ETF (19.51%) and the Shanghai Stock Exchange Sci-Tech Innovation Board Chip ETF (20.37%) [10][14] - The industry rotation strategy has achieved an annualized return of 9.34% since 2020, with the latest holdings including non-ferrous metals ETFs and green power ETFs [19][16] Group 2 - The Copula-based second-order stochastic dominance strategy has an annualized return of 15.52% since 2020, with the latest portfolio including the Huaxia CSI Agricultural Theme ETF (6.71%) and the Guangfa CSI Major Consumption ETF (69.79%) [21][24] - The technology ETF allocation strategy based on quantile random forests has an annualized return of 12.33% since 2020, with a significant portion allocated to the Guangfa CSI All-Index Information Technology ETF (4.78%) and the Huatai-PineBridge CSI Photovoltaic Industry ETF (76.51%) [27][31]