汇安成长优选A

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最高近190%!前三季度37只基金收益翻倍!AI主题表现领跑
Sou Hu Cai Jing· 2025-09-30 12:53
本文共1900 字 阅读完约7分钟 金融投资报记者 刘庆华 三季度行情即将收官。在经历了一季度的震荡上行,一季度末和二季度初的调整之后,A股市场和港股 市场自4月中旬以来持续走高,并在三季度迭创阶段新高,投向股票资产的基金也获得了不错的收益。 Wind数据显示,今年以来截至9月26日,在权益类基金和QDII基金中,合计共有37只基金收益率翻倍。 主动管理的A股权益类基金中,重仓AI的基金收益率领先,单只基金收益率最高接近190%。被动指数 型基金中,跟踪创新药、通信、人工智能等方向的基金收益率居前。 01 主动权益基金:31只基金收益翻倍 投向A股的主动权益类基金今年以来表现不俗,超额回报出色。截至9月26日,算术平均收益率为 30.32%(剔除年内成立的基金),超过98%的主动权益类基金取得正收益,收益率超50%的基金达到 684只,占比超15%。其中,收益率超过100%的基金有31只,单只基金最高收益率接近190%。 永赢科技智选A以189.58%的收益率领跑。二季度以来该基金净值涨幅明显,近半年的收益率超过了 164%。从基金季报可以看到,二季度末该基金有明显的调仓动作,前十大重仓股全部更换,将持仓重 ...
多家中小公募,业绩突出!
Zhong Guo Ji Jin Bao· 2025-09-29 06:31
其中,133只"翻倍基"来自中小型公募(以二季度末资产管理规模排名30名之后为界定标准),占比达 54.3%。近一年收益率排名前15位的基金中,中小公募产品占8席:中信建投(601066)北交所精选两 年定开A以240.22%的区间单位净值增长率位居榜首;德邦鑫星价值A以221.47%的涨幅位列第四;信澳 业绩驱动A、中航机遇领航A近一年单位净值增长率分别为198.45%、197.94%;华富科技动能A、汇安 成长优选A、红土创新新兴产业、长盛城镇化主题A等4只产品的区间涨幅均超过160%。 | 证券简称 | 中原地 | 基金规模 | 基金管理人 | | --- | --- | --- | --- | | | 增长率(%) | 合计(亿元) | | | 中信建投北交所精选两年定开A | 240.22 | 2.86 | 中信建投基金 | | 德邦鑫星价值A | 221.47 | 9.33 | 德邦基金 | | 永赢先进制造智选A | 205.63 | 138.45 | 永赢基金 | | 信澳业绩驱动A | 198.45 | 3.44 | 信达澳亚基金 | | 中航机遇领航A | 197.94 | 10.61 | ...
多家中小公募,业绩突出!
中国基金报· 2025-09-29 06:26
【导读】市场风格与竞争格局共振 中小公募业绩突出 中国基金报记者 张燕北 A 股 "9·24" 行情一周年,主动权益基金业绩显著回暖。中小公募旗下产品强势 " 逆袭 " , 在业绩涨幅榜上占据较多席位,一改以往大中型公募产品统治的格局。受访业内人士分析, 这一现象是市场行情演绎与行业竞争格局共同作用的结果。中小基金公司的赛道化、高锐度 布局成为 " 弯道超车 " 的可行路径。但立足长期价值创造才是行业发展的根本方向。 近一年 " 翻倍基 " 超 240 只 中小公募旗下产品占比过半 去年 9 月 24 日以来, A 股主要指数大幅上行,主动权益基金业绩大幅回暖。 Wind 数据显 示,截至 9 月 26 日,近一年主动权益基金平均单位净值增长率达 40.77%,245 只基金 (仅统计主代码)净值翻倍。 其中, 133 只 " 翻倍基 " 来自中小型公募(以二季度末资产管理规模排名 30 名之后为界 定标准),占比达 54.3% 。近一年收益率排名前 15 位的基金中,中小公募产品占 8 席: 中信建投北交所精选两年定开 A 以 240.22% 的区间单位净值增长率位居榜首;德邦鑫星价 值 A 以 221.4 ...
牛市里的新生代,是真猛啊!
Sou Hu Cai Jing· 2025-09-19 10:37
风水轮流转,被毒打了几年后,主动权益基金今年终于爆发。 我去统计了下, 截至9月12日,年内翻倍的基金已经有43只,收益超过50%的有777只,连代表主动权益基金平均水平的"偏股混合型基金指数"都涨了30%+,实打实的权 益大年。 这样的市场环境也给了很多新生代基金经理出头的机会。挖一挖,还真能挖到不少后起之秀。 比如单柏霖,工程师出身的他将其独特的"技术原理 - 产业落地"逻辑框架运用到投资中,很早就预判了产业趋势,管理的"汇安成长优选A(005550)"过 去一年涨了196.87%,同类第3;今年以来涨了118.96%,同类第2(数据来源:Wind,截至2025年9月12日)。 | < w | 汇安成长优选A | | | | --- | --- | --- | --- | | | 005550.OF 中风险 混合型 | | | | 资料 | ਦਿ | 公告 | 资讯 | | 阶段回报 | | 年度回报 | | | 周期 | 涨跌幅 | 沪深300 | 同类排名 | | 近一周 | 7.64% | 1.38% | 37/2362 | | 近一月 | 29.97% | 9.13% | 77/2354 | | ...
历史罕见!最牛涨超175%
中国基金报· 2025-08-31 00:44
Core Viewpoint - The A-share market has shown significant strength in the first eight months of the year, leading to a strong performance of public equity funds, with many funds achieving over 100% returns [2][6][13]. Group 1: Market Performance - The main indices have experienced substantial gains, with the North Exchange 50 index rising by 51.49%, and several other indices, including the Sci-Tech Innovation 50 and the ChiNext index, increasing by over 30% [2][4]. - In August, the Shanghai Composite Index broke through the 3,800-point mark, reaching a 10-year high, with the Sci-Tech series indices showing strong performance, with increases of 32.25% and 28.00% respectively [4]. Group 2: Fund Performance - The average net value growth rate of active equity funds in the first eight months reached 23.83%, with the best-performing fund achieving a growth rate exceeding 175% [6][10][11]. - A total of 603 active equity funds have recorded a net value growth rate exceeding 50%, with 21 funds surpassing 100% [13][20]. - The average net value growth rates for ordinary stock funds and mixed equity funds were 28.38% and 28.79% respectively, indicating strong recovery in net values [9]. Group 3: Sector Opportunities - Structural opportunities have emerged in sectors such as the North Exchange, innovative pharmaceuticals, humanoid robots, AI, and semiconductors, contributing to the strong performance of funds managed by adept fund managers [12][20]. - The innovative pharmaceutical sector has been a standout performer, with the Hong Kong Stock Connect innovative pharmaceutical index showing a cumulative annual increase of 108.24% [24]. Group 4: Future Outlook - If the current market trends continue, 2025 is expected to be a breakout year for active equity fund performance [21]. - The market is experiencing a rebalancing of underlying funds, with indications of capital flowing from dollar assets to non-dollar assets, and from the bond market to the equity market [26].
逾300只量化基金净值创历史新高 小微盘“高光”背后有何风险?
Di Yi Cai Jing· 2025-07-30 03:22
Group 1 - The A-share market has recently rebounded, with small-cap stocks outperforming the broader market significantly, leading to a collective rise in the net value of quantitative public funds, with over 97% achieving positive returns this year [1][2][3] - The Wind data shows that as of July 28, 314 out of 652 quantitative public funds have refreshed their historical net value highs, representing over 48% of the total [2][3] - The small-cap stock index reached a historical high of 476,824.12 points on July 29, with a year-to-date return of 50.23%, significantly outperforming larger indices [2][3] Group 2 - Due to the limited capacity of small-cap stocks to absorb funds, several high-performing products have implemented purchase limits, with some reducing the daily purchase limit to as low as 1,000 yuan [3][4] - Approximately 28 quantitative products are currently under restrictions for large purchases, with some tightening their purchase limits further [4] - Fund managers indicate that maintaining a comfortable management scale around 20 billion yuan is crucial for effective strategy execution [4] Group 3 - Despite the strong performance of small-cap stocks, there are emerging risks, including high crowding in small-cap strategies, which could lead to significant downturns if market sentiment shifts [6][7][8] - Analysts have noted that the current rally in small-cap stocks is heavily reliant on sentiment and liquidity rather than solid performance fundamentals, raising concerns about potential valuation bubbles [6][7] - Fund managers have cautioned about the risks associated with high crowding and the need for careful monitoring of market volatility and external uncertainties [7][8]
逾300只量化基金净值创历史新高,小微盘“高光”背后有何风险?
Di Yi Cai Jing· 2025-07-30 03:09
Group 1 - The core viewpoint of the articles highlights the strong performance of small-cap stocks in the A-share market, significantly outperforming larger indices, leading to a surge in public quantitative fund net values, with over 97% of these funds achieving positive returns this year [1][2][3] - The Wind data indicates that as of July 28, 314 out of 652 public quantitative funds have reached historical net value highs, representing over 48% of the total [2][3] - The small-cap stock index reached a historical high of 476,824.12 points on July 29, with a year-to-date return of 50.23%, while the mid-cap indices also showed substantial gains compared to larger indices [2][3] Group 2 - Due to the limited capacity of small-cap stocks to absorb funds, several high-performing products have implemented purchase limits, with some reducing daily purchase limits to as low as 1,000 yuan [3][4] - Approximately 28 quantitative products, including the CITIC Prudential Multi-Strategy Fund, have suspended large purchases, indicating a trend towards tighter purchase limits across the sector [4] - Fund managers suggest that a comfortable management scale for small-cap products is around 20 billion yuan, with a target position maintained between 60% to 80% to manage risks effectively [4] Group 3 - Analysts express concerns about the high "crowding" in small-cap stocks, which could lead to significant risks if market sentiment shifts, although the likelihood of extreme adjustments similar to early 2024 is considered low [6][7][8] - The reliance on sentiment and liquidity in small-cap stocks has raised concerns about their underlying fragility, with many stocks driven by themes rather than solid performance, leading to potential valuation bubbles [6][7] - Fund managers have cautioned about the need to monitor market volatility closely and prepare for potential risks, emphasizing that the current high levels of investment in small-cap stocks may not be sustainable [7][8]
因子周报20250606 :本周Beta与小市值风格强劲-20250607
CMS· 2025-06-07 14:13
Quantitative Models and Construction Methods - **Model Name**: Neutral Constraint Maximum Factor Exposure Portfolio **Model Construction Idea**: The model aims to maximize the exposure of a target factor in the portfolio while maintaining neutrality in industry and style exposures relative to the benchmark index[59][60][61] **Model Construction Process**: 1. Objective Function: Maximize the portfolio's exposure to the target factor $Max \ w^{\prime} X_{target}$ 2. Constraints: - Industry neutrality: $(w-w_{b})^{\prime} X_{ind}=0$ - Style neutrality (size, valuation, growth): $(w-w_{b})^{\prime} X_{Beta}=0$ - Stock weight deviation from benchmark: $|w-w_{b}|\leq1\%$ - No short selling: $w\geq0$ - Full investment: $w^{\prime} 1=1$ - Stocks must belong to the benchmark: $w^{\prime} B=1$ 3. Factor neutralization: Before constructing the portfolio, factors are neutralized to remove correlations with industry and style factors, and all factor directions are adjusted to be positive[59][60][61] **Model Evaluation**: The model effectively balances factor exposure maximization with risk control through constraints, ensuring robustness in various market conditions[59][60][61] --- Model Backtesting Results - **Neutral Constraint Maximum Factor Exposure Portfolio** - **CSI 300 Enhanced Portfolio**: Weekly excess return 0.35%, monthly excess return 0.33%, annual excess return 0.40%[56] - **CSI 500 Enhanced Portfolio**: Weekly excess return -0.52%, monthly excess return 1.34%, annual excess return -0.05%[56] - **CSI 800 Enhanced Portfolio**: Weekly excess return 0.29%, monthly excess return 1.59%, annual excess return 0.74%[56] - **CSI 1000 Enhanced Portfolio**: Weekly excess return 0.25%, monthly excess return 2.83%, annual excess return 15.68%[57] - **CSI 300 ESG Enhanced Portfolio**: Weekly excess return 0.14%, monthly excess return 0.62%, annual excess return 5.94%[57] --- Quantitative Factors and Construction Methods - **Factor Name**: Beta Factor **Factor Construction Idea**: Measures the sensitivity of a stock's returns to the market's returns, capturing risk preferences in the market[15][16] **Factor Construction Process**: - Calculate the stock's daily returns over the past 252 trading days - Perform an exponentially weighted regression of the stock's returns against the market index (CSI All Share Index) with a half-life of 63 days - Use the regression coefficient as the Beta value[15][16] **Factor Evaluation**: The Beta factor effectively captures market risk preferences, as evidenced by its strong performance in high-risk environments[15][16] - **Factor Name**: Size Factor **Factor Construction Idea**: Captures the size effect, where smaller-cap stocks tend to outperform larger-cap stocks[15][16] **Factor Construction Process**: - Compute the natural logarithm of the total market capitalization of each stock[15][16] **Factor Evaluation**: The size factor consistently demonstrates the small-cap effect, particularly in high-volatility markets[15][16] - **Factor Name**: Momentum Factor **Factor Construction Idea**: Identifies stocks with strong past performance, assuming trends persist in the short term[15][16] **Factor Construction Process**: - Calculate cumulative returns over the past 504 trading days, excluding the most recent 21 days - Apply an exponentially weighted average with a half-life of 126 days to the return series[15][16] **Factor Evaluation**: The momentum factor is effective in trending markets but may underperform during reversals[15][16] --- Factor Backtesting Results - **Beta Factor**: Weekly long-short return 2.61%, monthly long-short return -1.82%[18] - **Size Factor**: Weekly long-short return -2.11%, monthly long-short return -8.87%[18] - **Momentum Factor**: Weekly long-short return 0.58%, monthly long-short return -1.85%[18] --- Stock Selection Factors and Performance - **Factor Name**: Single Quarter ROE **Factor Construction Idea**: Measures profitability by comparing net income to shareholder equity for a single quarter[20][21] **Factor Construction Process**: - Calculate the ratio of net income attributable to shareholders to total shareholder equity for the most recent quarter[20][21] **Factor Backtesting Results**: - CSI 300: Weekly excess return 0.72%, monthly excess return 1.90%, annual excess return 5.43%[23] - CSI 500: Weekly excess return 0.85%, monthly excess return 0.91%, annual excess return 5.90%[29] - CSI 800: Weekly excess return 1.02%, monthly excess return 2.06%, annual excess return 3.95%[32] - CSI 1000: Weekly excess return 1.09%, monthly excess return 2.44%, annual excess return -3.47%[36] - **Factor Name**: Single Quarter EP **Factor Construction Idea**: Measures earnings yield by comparing net income to market capitalization for a single quarter[20][21] **Factor Construction Process**: - Calculate the ratio of net income attributable to shareholders to total market capitalization for the most recent quarter[20][21] **Factor Backtesting Results**: - CSI 300: Weekly excess return 0.89%, monthly excess return 1.65%, annual excess return 0.86%[23] - CSI 500: Weekly excess return 0.50%, monthly excess return 1.87%, annual excess return -4.22%[29] - CSI 800: Weekly excess return 1.06%, monthly excess return 2.04%, annual excess return -1.54%[32] - CSI 1000: Weekly excess return 0.38%, monthly excess return 1.69%, annual excess return -5.99%[36] - **Factor Name**: 20-Day Reversal **Factor Construction Idea**: Captures short-term mean reversion by focusing on stocks with recent underperformance[20][21] **Factor Construction Process**: - Calculate cumulative returns over the past 20 trading days[20][21] **Factor Backtesting Results**: - CSI 300: Weekly excess return 0.11%, monthly excess return -0.15%, annual excess return 8.90%[23] - CSI 500: Weekly excess return 0.80%, monthly excess return 1.57%, annual excess return 3.33%[29] - CSI 800: Weekly excess return 0.39%, monthly excess return 0.59%, annual excess return 8.27%[32] - CSI 1000: Weekly excess return 0.64%, monthly excess return 1.38%, annual excess return -6.69%[36]