{"data":{"cate":"post","html":"\n
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\n 全市场小市场择时策略<\/a>\n 2025-09-17<\/span>\n <\/div>\n
\n 273<\/span>\n 0<\/span>\n 1<\/span>\n <\/div>\n <\/div>\n
\n
\n ETF轮动策略V1.0（垃圾删了）<\/a>\n 2024-10-17<\/span>\n <\/div>\n
\n 1963<\/span>\n 22<\/span>\n 12<\/span>\n <\/div>\n <\/div>\n
\n
\n 基于先验的优质标的轮动策略V2.0<\/a>\n 2024-10-16<\/span>\n <\/div>\n
\n 752<\/span>\n 6<\/span>\n 5<\/span>\n <\/div>\n <\/div>\n
\n
\n 基于先验的优质标的轮动策略V1.0<\/a>\n 2024-10-15<\/span>\n <\/div>\n
\n 653<\/span>\n 5<\/span>\n 5<\/span>\n <\/div>\n <\/div>\n
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\n 熊市和牛市能在一个策略中兼容吗？<\/a>\n 2024-10-04<\/span>\n <\/div>\n
\n 219<\/span>\n 2<\/span>\n 0<\/span>\n <\/div>\n <\/div>\n
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\n 多模型集成策略<\/a>\n 2024-02-25<\/span>\n <\/div>\n
\n 498<\/span>\n 9<\/span>\n 4<\/span>\n <\/div>\n <\/div>\n
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\n 一个创新的抄底策略<\/a>\n 2024-02-24<\/span>\n <\/div>\n
\n 613<\/span>\n 22<\/span>\n 13<\/span>\n <\/div>\n <\/div>\n
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\n 较稳定的机器学习模型<\/a>\n 2024-02-23<\/span>\n <\/div>\n
\n 488<\/span>\n 19<\/span>\n 5<\/span>\n <\/div>\n <\/div>\n
\n
\n 基于机器学习的策略<\/a>\n 2024-02-22<\/span>\n <\/div>\n
\n 1568<\/span>\n 76<\/span>\n 22<\/span>\n <\/div>\n <\/div>\n
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\n 交易时间对收益的影响<\/a>\n 2024-01-15<\/span>\n <\/div>\n
\n 242<\/span>\n 13<\/span>\n 6<\/span>\n <\/div>\n <\/div>\n
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\n 在相同的选股模型下不同买点对比<\/a>\n 2024-01-10<\/span>\n <\/div>\n
\n 353<\/span>\n 36<\/span>\n 7<\/span>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n"},"status":"0","code":"00000","msg":""}