最近和发小在茶馆喝茶，聊起圈里的新鲜事，说公募基金的业绩比较基准新规，3月1日就要正式实施了，好多基金公司都在忙活着 调整产品基准，有的已经和监管沟通好几轮了。旁边坐的老陈听见了，赶紧凑过来问："这新规会不会影响我买的基金啊？是不是 要赶紧出手？"其实不止老陈，之前我也和大家一样，一有消息就慌得不行，直到认识了搞量化大数据的发小，才明白：从来不是 消息决定走势，而是消息背后的资金交易行为，才是关键。就像老陈去年买的一只基金，明明出了利好公告，结果反而走弱，后来 发小用量化数据一看，原来是早就有资金在悄悄兑现利润，借利好出货。 一、别被走势表象，蒙了你的眼 三、利空不慌，看资金真实意图 我们平时看投资品，总习惯盯着盘面的高低变化，觉得走高就是好，走弱就是坏，但其实这都是表象。发小给我看过一组量化数 据，有只投资品，那段时间盘面还在缓慢走高，势头虽然不如之前凌厉，但看起来依然稳得住，好多人都觉得是入场的好机会，甚 至有人追了进去。但量化数据却显示，连续五个交易日，主导交易的都是「获利回吐」行为。 这里的「获利回吐」，说大白话就是之前赚了钱的资金，开始慢慢兑现利润，不是说看空后续，只是落袋为安。但这种行为一旦持 续 ...

Group 1 - The core viewpoint of the article highlights the accelerated financing pace in the intelligent driving chip sector, with three companies successfully completing new rounds of equity financing, including NIO's chip subsidiary raising over 2.2 billion yuan [1] - The global automotive chip market is expected to exceed 170 billion yuan by 2030, with domestic manufacturers poised to leverage their leading position in the new energy vehicle sector [1] - Many market participants tend to rely on superficial indicators such as hot concepts, performance, and price trends, which can lead to misjudgments; a focus on quantitative big data is essential to understand the underlying market logic [1] Group 2 - A common misconception among market participants is that they primarily judge based on whether a sector is a hot area, performance quality, or price levels, which often leads to inaccuracies [3] - The core driver of price movements is the behavior of large institutional funds rather than superficial performance or concepts; when a stock enters a consolidation phase after adjustments, it may not signal a bottom if institutional participation is lacking [3] - Quantitative big data tools can capture the "institutional inventory" data, which reflects the trading activity of institutional funds, indicating their level of engagement in the market [3] Group 3 - Stocks that enter a consolidation phase after adjustments can have vastly different outcomes based on the activity level of institutional inventory; active institutional participation often indicates a long-term investment strategy [6] - Stocks experiencing wide fluctuations may mislead investors; if institutional inventory data declines during price oscillations, it suggests weakening institutional interest, making any price increases likely unsustainable [8] - The continuous tracking of institutional inventory data provides objective evidence of changes in core trading behaviors, helping to avoid common cognitive biases in market judgments [13] Group 4 - Some stocks may show clear signs of price breakdown, causing concern among participants; however, active institutional inventory data can indicate that such price movements are part of a broader trading strategy rather than a lack of interest [10] - The core value of institutional inventory data lies in its ability to reflect the trading intentions of large funds, with sustained activity signaling long-term planning rather than short-term fluctuations [10] - In the complex market landscape, focusing on the behavior of core trading entities is crucial for understanding market dynamics, with quantitative big data serving as a reliable alternative to subjective assessments [13]

Core Viewpoint - The article emphasizes that market movements are influenced more by underlying trading behaviors rather than just news events, suggesting that a quantitative data approach can help investors understand the true market dynamics [1]. Group 1: Market Dynamics - Various smartphone brands are planning to adjust product prices due to rising costs from memory and storage chips, marking the largest price increase in the smartphone industry in five years [2]. - In the automotive sector, Chinese brand passenger car sales in January 2026 reached 1.329 million units, a decrease of 32.1% month-on-month and 8.9% year-on-year, with a market share drop of 1.5 percentage points [2]. Group 2: Shareholder Actions - Shareholders of Hongsheng Huayuan and Fangzheng Technology plan to reduce their stakes by up to 1% and 3% respectively [2]. - A significant share unlock is expected for several companies on March 2, including: - China Merchants Shipping with a 64.86% unlock, estimated at 81.94 billion [2]. - Weidian Physiotherapy with a 73.477% unlock, estimated at 14.12 billion [2]. - New Giant Hand with a 30.88% unlock, estimated at 11.53 billion [2]. - JuJiao Co. and HengLian Co. with unlocks of 21.7% and 21.32%, estimated at 8.84 billion and 17.5 billion respectively [2]. Group 3: Trading Behavior Insights - The article introduces four core trading behaviors identified through quantitative data: - "Bullish Dominance" indicates active buying [4]. - "Profit Taking" shows that previous investors are cashing out [4]. - "Bearish Dominance" reflects a tendency for investors to sell [4]. - "Short Covering" indicates that previously exited investors are re-entering the market [4]. Group 4: Behavioral Analysis - The article discusses how "Profit Taking" can mislead investors into thinking a stock is still on an upward trend when in fact, funds are exiting [6]. - Conversely, "Short Covering" can lead to price increases despite negative news, as funds may be entering the market during panic selling [10]. - Quantitative data can reveal these hidden behaviors, allowing investors to make more informed decisions and avoid emotional reactions to market fluctuations [13].

最近奢侈品圈的动作，把"主观偏见"和"量化事实"的鸿沟撕得明明白白——LVMH一边在考虑出售Make Up For Ever、Fresh等非核心美妆品牌，甚至评估 Fenty Beauty的股权，一边却让LV高调进军美妆，推出千元口红系列。不少人主观拍板"美妆板块不行了"，赶紧割肉避坑；也有人跟风喊"LV入场是风 口"，盲目追高。但真相是，这背后是巨头精准的资源聚焦，就像股市里的机构资金：表面动作迷惑人，真实意图藏在交易行为里。你以为看到的是全 部，其实只是想让你看到的部分，就像很多股民看股票走势，被反复震荡搞得晕头转向，根本摸不清趋势，这就是主观判断的致命缺陷。 你有没有过这种经历？一只股票反复震荡，前三次反弹都是"假动作"，套住一批追高的人；第四次反弹来了，你怕又是陷阱不敢进，结果它突然跳空上 涨，等你反应过来又开始下跌，完美错过机会。这就是主观偏见的坑——你用过去的经验判断未来，却不知道机构的真实意图早就藏在交易行为里，而这 些，是K线走势永远不会告诉你的。 看图1： 一、别被K线震荡，遮蔽交易本质 普通走势图只会让你在"进还是不进"的纠结里内耗，但量化大数据能直接拆解出两组关键数据：一组是红黄蓝绿的「 ...

Core Insights - The market is experiencing a structural change, with the balance of ETF margin trading in the Shanghai and Shenzhen markets exceeding 119 billion yuan, reflecting a nearly 10 billion yuan increase from the previous trading day [1] - Quantitative data is providing a new perspective on trading behaviors, focusing on the real participation characteristics of core funds rather than just price fluctuations [1] Group 1: Absence of Core Fund Participation - A rebound characterized by a double bottom pattern often leads to optimistic market sentiment, but quantitative data shows a lack of core fund participation during these rebounds, indicating a lack of sustained momentum [3][5] - The absence of core trading characteristics during price rebounds suggests that these movements are merely short-term fluctuations without long-term viability [5] Group 2: False Low Points in Downtrends - Investors often expect a rebound after significant declines, but quantitative data reveals that subsequent rebounds lack core fund activity, indicating they are driven by scattered short-term trading rather than sustained interest from core funds [8] - The absence of core fund participation during these rebounds leads to a continuous resetting of perceived low points, creating a "lower low" trend [8] Group 3: Resilience During Price Adjustments - During price adjustments following new highs, core fund trading characteristics remain active, suggesting that short-term price drops are more likely to be phase corrections rather than trend reversals [11] - Relying solely on price movements can lead investors to exit during consolidation phases, missing potential trend continuations [11] Group 4: Consistency in Behavior Amidst Fluctuations - In a fluctuating market, core fund participation remains active during multiple price adjustments, which can mislead investors into making premature exit decisions based on traditional price analysis [14] - The sustained involvement of core funds during price fluctuations indicates that traditional shape judgments may overlook the underlying funding behavior, leading to missed opportunities [14] Group 5: Value of Quantitative Data - The core value of quantitative data lies in its focus on changes in trading behavior rather than price movements, providing a more objective observation dimension for investors [15] - When core fund trading characteristics are present, short-term price fluctuations are unlikely to alter the overall trend, while their absence suggests that price changes may not be sustainable [15]

近期港股市场的IPO热度持续攀升，开年不到两个月，已有24家企业成功挂牌，募资规模较去年同期大增10倍还多。不管是内地各赛道的龙头企业，还是来 自东南亚、欧美等地区的国际公司，都纷纷选择赴港上市，港股作为全球资本枢纽的地位进一步凸显。不少人看到这股热潮，难免会想，这些新上市的企 业，或者沾边的相关标的，是不是值得关注？但我一直觉得，市场消息只是波动的诱因，真正决定表现的，还是背后资金的真实态度。之前有个朋友，看到 某热门赛道的利好消息就盲目跟进，结果始终没拿到预期的结果，后来通过量化大数据复盘才发现，问题出在资金参与度上。 面对这样的市场热潮，我们该怎么跳出消息的干扰，看清真实的市场逻辑？这就需要用量化大数据的思维，去拆解资金的真实行为。 一、「机构库存」：资金参与度的量化标尺 很多人会觉得，利好消息一定会带动相关标的的表现，但实际情况往往并非如此。就拿黄金相关标的来说，之前金价一路走高，市场普遍认为相关标的会迎 来机会，某标的业绩增长16%，市盈率仅8倍，从基本面看似乎具备不错的潜力，且此前一直处于调整状态，不存在利好提前消化的情况，很容易让人觉得 会有不错的表现。但实际却是该标的表现持续走弱，这背后的核心 ...

Group 1 - The article emphasizes the importance of not being swayed by news and emotional reactions in investment decisions, advocating for the use of quantitative data to guide actions [1][2][6] - It highlights that market movements are often influenced by underlying fund activities rather than surface-level news, suggesting that investors should focus on data to avoid making impulsive decisions [1][6] - The concept of "institutional inventory" is introduced, indicating that even during price declines, active institutional participation can signal a potential rebound, contrasting with situations where institutions withdraw [6][9] Group 2 - The article warns against the misconception that price rebounds are always reliable indicators of future performance, stressing the need to verify institutional involvement before making investment decisions [9][14] - It discusses the pitfalls of chasing rebounds without understanding the underlying support from institutional funds, which can lead to losses if the rebound lacks solid backing [14] - The narrative concludes by advocating for a disciplined investment approach that relies on quantitative data to maintain a stable mindset and avoid emotional trading [12][14]

近期A股IPO市场的回暖信号越来越清晰，在审项目数量较去年同期大幅增长超146%，终止审核数量却下滑超85%，新质生产力相关领域成了全年布局的核 心方向。很多普通投资者可能会问，这和我们日常投资有什么直接关联？其实市场的任何趋势变化，最终都会反映在资金的交易行为上。过去我们只能靠盘 面走势猜测资金意图，很容易被表象误导，现在随着量化大数据技术的成熟，资金的真实态度已经可以被精准捕捉。尤其是当不同类型的资金达成共识时， 相关标的往往会有超出市场平均的表现，而这正是我们可以借助量化工具去把握的核心逻辑。 | 序号 | | 2026年在車IPO情況 | 一览 | | | | --- | --- | --- | --- | --- | --- | | | 最新公告日 | 企业名称 | 保存机构 | 拟上市板 | 受理目期(交易所披露) | | 1 | 2月13日 | 上海珈凯生物股份有限公司 | 东吴证券 | 北交所 | 2025年6月30日 | | 2 | 2月13日 | 湖北龙辰科技股份有限公司 | 国泰海通证券 | 北交所 | 2025年6月30日 | | 3 | 2月13日 | 广州通则康威科技股份有限公司 ...

Core Insights - The article emphasizes the importance of understanding real trading behaviors rather than just surface-level market trends, highlighting that true investment success relies on analyzing quantitative data instead of relying on intuition or popular news [1][17]. Group 1: Market Trends and Investment Behavior - The film industry is experiencing trends such as the rise of IP sequels, the use of AI technology for cost reduction, and diversification in cinema experiences, with projections indicating that the box office for the 2026 Spring Festival will exceed 55.3 billion [1]. - The article warns against being misled by superficial market excitement, using the example of the solid-state battery concept stock that saw a 6.9% increase in one day, followed by a two-month period of only a 10% gain, illustrating the volatility and potential pitfalls of emotional trading [3][6]. Group 2: Quantitative Analysis - Quantitative data can reveal the underlying dynamics of market movements, with two key indicators: "dominant momentum" reflecting various trading behaviors and "institutional inventory" indicating the level of institutional participation in trading [6][11]. - Identifying key trading signals through quantitative analysis can help investors distinguish between genuine market declines and "shakeouts," where weak hands are removed from the market to facilitate future price increases [7][11]. Group 3: Trading Logic and Market Psychology - Stocks that perform well often require repeated "shakeouts" to clear out less committed investors, allowing for smoother upward movements. Recognizing these signals can help investors stay aligned with market trends [14]. - The article suggests that many investors struggle in the current market not due to its inherent difficulty, but because they continue to rely on outdated methods such as following news and price movements, which can lead to emotional decision-making [17][18]. Group 4: Building Investment Confidence - The use of objective data can help investors maintain a rational mindset, reducing the influence of emotions on decision-making. This approach allows for a clearer understanding of market dynamics beyond just price movements [18]. - The article concludes that successful investing does not require extensive expertise but rather the ability to utilize tools that eliminate emotional biases, emphasizing the importance of understanding the true nature of trading behaviors [18].

Core Viewpoint - The article emphasizes the importance of understanding the true trading intentions of funds, particularly institutional investors, rather than relying solely on personal intuition or market trends when making investment decisions [1]. Group 1: Misjudging Market Trends - Investors often rely on personal feelings to determine market highs and lows, leading to premature selling or buying decisions [3]. - The article illustrates that stock price movements are dictated by the trading intentions of funds, especially institutional participation, rather than mere price trends [3]. - An example is provided where a stock doubled in price within three months, and despite price corrections, institutional inventory data indicated continued participation, suggesting that these corrections were normal rather than signals of a market peak [3]. Group 2: Misinterpretation of Price Corrections - A common mistake is to sell off stocks after they reach new highs and begin to correct, assuming the market has peaked [5]. - The article highlights that during price corrections, institutional inventory data remained active, indicating ongoing institutional interest and suggesting that these corrections were merely consolidations for future gains [5]. - Investors who sell during these corrections may miss out on significant future profits [5]. Group 3: Risks of Bottom Fishing - The belief that a stock must rebound after a significant drop leads many investors to attempt bottom fishing, often resulting in losses [7]. - The article notes that many rebounds are not supported by institutional buying, making them unreliable and prone to further declines [7]. - An example is given of a stock that continued to decline despite apparent short-term rebounds, illustrating the dangers of following market sentiment without institutional backing [7]. Group 4: Misreading Rebounds After Declines - Investors often mistake short-term rebounds following significant declines as signs of a market reversal, leading to hasty buying decisions [9]. - The article points out that during these rebounds, institutional inventory data showed no signs of active participation, indicating that these movements were merely emotional responses rather than genuine reversals [9]. - This misinterpretation can result in investors being trapped in further downtrends after buying into these false signals [9]. Group 5: Establishing Probability-Based Thinking - The article advocates for a shift from intuitive decision-making to a data-driven approach that focuses on the participation of institutional investors [12]. - By utilizing quantitative data, investors can better understand the true market dynamics and improve their decision-making processes [12]. - The emphasis is on developing a systematic investment strategy based on objective data rather than subjective feelings, which can enhance long-term investment success [12].