本周募资情况 本周新登记股权投资基金管理人共计0家，取消备案登记3家，全年截至目前累计股权投 资基金管理人数量为11家。本周新增备案基金数量为 81只 ，规模总计 535.04亿元 ，本周备案基金募资最多的为北京经济技术开发区政府投资引导基金二期（有限合 伙），募集100.00亿人民币。全年截至目前累计股权投资备案基金数量为631只，规模 总计5558.75亿元。（2025年2月21日-2025年2月27日） 新备案基金地域分布TOP5 涉及总金额693.36亿元人民币。 作者 | 私募通 来源 | 决策投资圈 （ID：PEDATAMAX） 清科创业（01945.HK）旗下私募通统计：截至本周五下午，募资、投资、上市和并购 共 165起 事件，涉及总金额 693.36亿 人民币。从交易金额来看，本周金额较大事件 是：2025年2月25日，奉新时代新能源材料有限公司、江西飞宇新能源科技有限公司对 宜春盛源锂业有限责任公司进行增资，出资金额是26.00亿人民币。从交易事件地域分 布看，目前主要分布在广东省、江苏省和北京市，占比为广东省19.1%，江苏省 14.3%，北京市13.1%。 01 02 本周投资情况 清 ...

Market Sentiment Tracking - As of February 28, 2025, the proportion of rising stocks in the CSI 300 index has decreased to below 60%, indicating a decline in market sentiment [2] - The momentum sentiment indicators show a downward trend in the short-term line and an upward trend in the long-term line, suggesting a cautious outlook for the near future [2] - The short-term sentiment indicators for the CSI 300 index remain in a prosperous sentiment range [2] Fund Cohesion Tracking - As of February 28, 2025, the degree of fund cohesion remains low, with a high level of fund clustering observed [3] - There has been a slight decline in the excess returns of clustered stocks and funds over the past month [3] PB-ROE-50 Strategy Tracking - In February 2025, the PB-ROE-50 strategy experienced a pullback in excess returns across various stock pools [4] - The excess return for the CSI 500 stock pool was -3.34%, for the CSI 800 stock pool was -5.32%, and for the overall market stock pool was -2.54% [4] Institutional Research Strategy Tracking - The private equity research tracking strategy showed significant excess returns in February [5] - The public fund research selection strategy underperformed the CSI 800 with an excess return of -0.57%, while the private equity research tracking strategy outperformed with an excess return of 2.88% [5] Negative List - As of February 28, 2025, several stocks with high interest-bearing debt ratios ranked poorly, including Zhongyida, Guiding Compass, and others, with rankings of 100 or lower [6] - Stocks with high financial cost burden ratios include Ningbo Fangzheng, Ganfeng Lithium, and others, all with ratios exceeding 10 times [6]

米斯兹之子 成就新汽车人 l B 0 ala E L I 规 跨 实 战 জ 野 界 国 / 推 交通堵塞不仅耗费通勤者大量时间，还导致物流运输效率低下，环境污染加剧。为改变这一现状， 纽约市参考伦敦、斯德哥尔摩、新加坡等城市的成功经验，毅然开启拥堵收费的大胆尝试。 纽约拥堵收费计划划定了一个广泛的"拥堵缓解区"，几乎涵盖曼哈顿60街以南的全部区域，像林肯 隧道、荷兰隧道、休格·凯里隧道，以及连接布鲁克林和皇后区的桥梁等关键交通要道均囊括其 中。 该计划对通行车辆按不同时段和车辆类型收费。 编 译 / 阅 凡 设 计 / 赵昊然 来 源 / Fast Company 在全球城市纷纷探索交通优化策略的大背景下，美国纽约于2025年1月5日正式推行拥堵收费计划， 旨在缓解曼哈顿核心区域的交通顽疾，这一举措在美国尚属首次，一经推出便备受瞩目。 纽约市交通拥堵状况由来已久，曼哈顿作为城市的心脏地带，特别是60街以下区域，每日通勤高峰 时，街道上车水马龙，车辆寸步难行。 持有E-ZPass的客车，在工作日早5点至晚9点、周末早9点至晚9点的高峰时段，需缴纳9美元通行 费，通宵时段则为2.25美元。商业车辆收费更高，而没 ...

2024年是过去6年中国公司IPO项目数量最少的一年，但仍有不少机构收获颇丰。 本文为IPO早知道原创 作者｜Eric 微信公众号｜ipozaozhidao IPO早知道「年度IPO最佳投资机构TOP100」榜单已经来到第五年。在过去五年中， 入榜的机构总数共有284家，而连续5年进入TOP100的机构只有 18家 。 我们也很欣慰地看到，这一榜单为一级市场投资机构退出能力的判断提供了一些参考价值。 据IPO早知道统计，2024年市场共收获了228个中国企业的IPO，相较于2023年的417个，出现了明显的下降，这一数字甚至低于2018年的242个， 是 2018年以来中国公司IPO项目数量最少的一年。 2024年度，IPO早知道延续此前 五年的 的评选逻辑，「 年度IPO最佳投资机构TOP100」 最终排综合IPO项目数量、质量、机构过往表现以及机构自 主申报评的多个维度，五年以来，「TOP100」 排名 并非单纯从IPO数量的角度去对投资机构的成绩进行统计和评选， 我们希望能够突出那些在早期更 敢于下注、投出对行业和市场有更大影响力项目的投资机构 。 与「TOP100」一同发布的是「2024年度最佳投资机 ...

其实昨天中国选手里，真正掉大分的是覃海洋的100米蛙泳决赛。这位25岁的新晋蛙王去年世锦赛拿了50米、100米、200米三个冠军，被寄予了厚望。这 次决赛的前50米排名第一，但后50米游崩了，竟然掉到了第7，看的人莫名其妙。 …… 今天的a股.......乏善可陈，成交量连6000亿都没有了，中位数小跌0.12%，北上的外资又抛了50亿，单单计算2024年的话，外资对a股已经快变成净流出 了。 我听到个小道消息，8月中旬后北上数据会进一步限制发布，可能是觉得这个比较负面，不希望外资的持续流出打击大家对a股的信心。这不禁让我又想起 费翔老师的著名台词，啊啊啊啊啊啊，嗯嗯嗯嗯嗯。 现在的a股真是一筹莫展，昨晚有读者问我如果去当证监会主席，有什么措施救市。我老实说救不了一点，我能想到的点子其实监管层都已经落实了，现 在最大的问题是市场信心进入了负面螺旋，这是行政力量无法逆转的。之前最大的利好印花税都减半了，结果也是高开低走吃了个大阴棒，你们说还能如 何呢... 现在只能耐心等市场自身构筑一个信心的底部，也许三五个月，也许好几年，这种玄而又玄的东西谁也没有时间表。我是经历过两次熊市的，所以心态还 算平和，但陆陆续续有 ...

- The report discusses the application of stock pair trading ideas in factor strategies, specifically focusing on reversal factors which have historically shown strong performance[1] - Traditional reversal factors include "N-month price reversal," "highest price length," and "volume ratio," which capture the trend that stocks with low past returns tend to perform better in the future and vice versa[1][2] - The report introduces a pair reversal factor that captures reversal opportunities between individual stocks within the same industry, differing from traditional pair trading by using periodic closing instead of stop-loss conditions[2][3] - The pair reversal factor is tested using a hedging strategy with a monthly rebalancing frequency, using the CSI 800 index constituents as the stock pool, and achieving an annualized excess return of 8% from 2007 to 2016[3][4] - The pair reversal factor is also applied to enhance multi-factor portfolios with weekly rebalancing, showing improved returns even after considering transaction costs, with a benchmark multi-factor portfolio return of 424.40% and a pair rebalancing portfolio return of 501.59% during the sample period from 2007 to 2016[4][5] Quantitative Models and Construction Methods 1. **Model Name**: Pair Reversal Factor - **Construction Idea**: Capture reversal opportunities between individual stocks within the same industry, similar to pair trading but with periodic closing instead of stop-loss conditions[2][3] - **Construction Process**: 1. Perform cointegration regression on the log prices of two assets to check for cointegration relationship[43][44] 2. Calculate the spread and standard deviation of the spread during the learning period[45][46] 3. Use the spread and standard deviation to determine the opening threshold and execute trades accordingly[46][49] 4. Rebalance the portfolio monthly by closing all positions and reopening new ones based on the updated spread and standard deviation[51][53] - **Evaluation**: The pair reversal factor effectively captures stock price reversals and mean reversion of price spreads, providing significant excess returns at the individual stock level[69] Model Backtest Results 1. **Pair Reversal Factor**: - **Annualized Return**: 31.17% (2007), 50.85% (2008), 51.19% (2009), 21.39% (2010), 14.26% (2011), 14.75% (2012), 25.75% (2013), 9.10% (2014), 59.01% (2015), 17.05% (2016), 1246.06% (full sample)[63] - **Maximum Drawdown**: 4.44% (2007), 4.62% (2008), 4.61% (2009), 2.97% (2010), 2.64% (2011), 2.23% (2012), 2.57% (2013), 4.99% (2014), 5.48% (2015), 4.07% (2016), 5.48% (full sample)[63] - **Win Rate**: 58.38% (2007), 60.57% (2008), 59.02% (2009), 58.26% (2010), 58.20% (2011), 59.66% (2012), 59.66% (2013), 51.02% (2014), 59.84% (2015), 59.43% (2016), 58.27% (full sample)[63] Quantitative Factors and Construction Methods 1. **Factor Name**: N-month Price Reversal - **Construction Idea**: Measure the price change over a fixed time window to capture the reversal effect[30][33] - **Construction Process**: 1. Calculate the price change over the past N months: $(\text{Current Price} - \text{Price N months ago}) / \text{Price N months ago}$[33] - **Evaluation**: Reversal factors have shown strong performance in historical studies, with high IC values and good performance in various metrics such as LS return, LS win rate, LS IR, IC IR, and IC P[33][35] Factor Backtest Results 1. **N-month Price Reversal**: - **IC**: -5.72% (1-month), -4.75% (3-month), -4.10% (6-month), -3.55% (12-month)[35] - **LS Return**: 21.84% (1-month), 20.33% (3-month), 18.13% (6-month), 17.66% (12-month)[35] - **LS Win Rate**: 64.41% (1-month), 59.32% (3-month), 56.78% (6-month), 61.02% (12-month)[35] - **LS IR**: 0.99 (1-month), 0.81 (3-month), 0.77 (6-month), 0.83 (12-month)[35] - **IC IR**: 0.72 (1-month), 0.92 (3-month), 0.78 (6-month), 0.83 (12-month)[35] - **IC P**: 0.0% (1-month), 0.2% (3-month), 0.5% (6-month), 1.1% (12-month)[35]