Core Viewpoint - The recent implementation of quantitative trading regulations aims to enhance the precision of high-frequency trading supervision and impose strict constraints on abnormal trading, reshaping the market ecology and promoting the standardized development of the quantitative industry [2] Group 1: Quantitative Long Strategy Performance - The article highlights the performance of quantitative long products in the first half of the year, focusing on those with assets under management exceeding 500 million [2] - The top-performing quantitative long products are categorized by strategies such as quantitative stock selection, CSI 500 index enhancement, CSI 1000 index enhancement, and CSI 300 index enhancement [2] Group 2: Quantitative Stock Selection - The quantitative stock selection strategy relies on mathematical models and statistical analysis to avoid subjective emotional interference, allowing for the processing of data from thousands of stocks [3] - As of June 30, 2025, the average excess return of 144 quantitative stock selection products was ***%, with the top three products being "Zeyuan Shen Sheng No. 7 A Class" from Shenzhen Zeyuan, "Jiuming Qianliang No. 1" from Jiuming Investment, and "Liangying Risheng Exclusive No. 1 A Class" from Liangying Investment [3][5] Group 3: CSI 500 Index Enhancement - The CSI 500 index enhancement products aim to seek additional returns beyond the index through quantitative methods [6] - As of June 30, 2025, the average excess return of 139 CSI 500 index enhancement products was ***%, with the top three being "Xinhong CSI 500 Index Enhancement No. 2 A Class" from Xinhong Tianhe, "Xiangmu Yongfu" from Xiangmu Asset, and "Abama Ruixue Fengnian Quantitative Selection" from Abama Investment [6][8] Group 4: CSI 1000 Index Enhancement - The CSI 1000 index enhancement products focus on actively managing investments to exceed the index benchmark [9] - As of June 30, 2025, the average excess return of 86 CSI 1000 index enhancement products was ***9%, with the top three being "Xiangmu Wangjiang No. 2" from Xiangmu Asset, "Anzi Geek CSI 1000 Enhancement No. 1 A Class" from Anzi Fund, and "Zizhu No. 2" from Tiange Investment [9][10] Group 5: CSI 300 Index Enhancement - The CSI 300 index enhancement products aim to achieve excess returns through quantitative stock selection and derivative tools [12] - As of June 30, 2025, the average excess return of 24 CSI 300 index enhancement products was ***%, with the top three being "Jiu Zhang Huan Fang CSI 300 Quantitative Multi-Strategy No. 1" from Ningbo Huan Fang, "Mingcong Stable Growth No. 2" from Mingcong Investment, and "Tote CSI 300 Index Enhancement No. 2" from Tote (Sanya) Private [12][16] Group 6: Other Index Enhancements - Other index enhancement products cater to high-net-worth individuals, including various indices such as the National Securities 2000, Sci-Tech Innovation Board Index, and others [17] - As of June 30, 2025, the average excess return of 52 other index enhancement products was ***%, with the top three being "Liangchuang Quantitative Beizheng Stock Selection No. 1 A Class" from Liangchuang Investment, "Shengguanda Stock Quantitative No. 2 C Class" from Shengguanda, and "Longqi Technology Innovation Selection No. 1 C Class" from Longqi Technology [17][20]

本文首发于公众号"私募排排网"。 （点击↑↑ 上图查看详情 ） 2025年上半年，受国内外多重因素交织影响，A股市场波动显著加剧，收益与风险的平衡成为投 资者甄选股票策略产品的重要考量维度之一。 夏普比率是衡量风险收益比的一个重要指标 ，计算公式为：夏普比率=（基金预期收益率-无风险 利率）/基金收益的波动率（标准差）。通常情况下，当基金收益相近时，夏普比率越高越好。 2025年上半年，有夏普比率展示的股票策略产品共有2891只，平均收益为12.4%，夏普比率均值 为1.57。 按公司规模划分，规模为 10-20亿的私募旗下股票策略产品平均收益最为突出，达到 16.39%。然而，从夏普比率来看，却呈现出公司规模越大，股票策略产品夏普比率均值越高的 特点。其中，百亿私募成为唯一一个股票策略产品夏普比率均值超过2的规模组。 | 公司规模 | 股票策略产品数量 | 股票策略产品总规 模(亿元) | 上半年收益均值 | 上半年夏普均值 | | --- | --- | --- | --- | --- | | 100亿以上 | 420 | 632.37 | 11.40% | 2.03 | | 50-100亿 | 196 ...

机州像不像呆企业管理 仇菲 合伙企业(有限合伙) 35.28% 23.84% 数据来源:协会公示信息 发展历程 2013~2017年 · 量化策略开发和优化 2018年 公司成立,基金业协会备案 · · 正式对外募集 2022年 获得投顾资格,革新交易逻辑 · 20 2 E ~ 至今 专注股票量化投资,深耕中高频 量价策略 本文首发于公众号"私募排排网"。 （点击↑↑ 上图查看详情 ） 橡木资产简介 杭州橡木私募基金管理有限公司 成立于2018年3月，是中国证券投资基金业协会登记备案的私募基金管理人（登记编号：P1068698），为符 合提供投资建议条件的第三方机构。公司一直专注于股票量化投资，深耕中高频量价策略。公司核心投研团队由浙江大学数学系博士与华为高 级工程师领衔，深度融合金融数学理论与工程实现能力，构建了具备持续迭代能力的策略体系，致力于成为中高频量化领域的特色化标杆管理 人。（点此查看 橡木资产旗下产品收益、核心团队及最新路演 ） 户 核心团队 # 4 目前,橡木资产投研团队共9位专业人士,由国内外知名大学硕 博和资深IT专家组成,投研成员平均从业年限8.5年,以创始人仲 引辉为核心,有序地开展策 ...