AI大发展，有广告称可以让散户投资者使用AI炒股。但事实上，AI炒股并不简单，AI的交易策略需要 实时更新，固化的AI极易成为更高端AI的猎杀对象。对于一般散户而言，用AI炒股并不靠谱。 类似"AI一键炒股，轻松跑赢大盘"的广告语让散户投资者心动，无数散户投资者仿佛看到了打破信息壁 垒、实现财富跃迁的捷径。然而，现实却如同一盆冷水。散户用AI炒股，看似是站在技术风口上的智 慧选择，实则可能被算法裹挟。 AI炒股的宣传中，"智能""自动""高效"是高频词，但很少有人提及其背后的技术复杂性。真正的AI策略 构建，需要跨学科知识储备，从数学建模、机器学习到金融工程，每一步都充满专业壁垒。散户往往将 AI简化为输入数据、输出结果的成熟产品，却忽视了策略设计中的关键细节。诸如，如何选择特征变 量？如何应对市场风格的突变？这些问题的解决，需要深厚的理论功底与实战经验，远非普通散户投资 者所能驾驭。 例如，当大量散户AI同时执行突破买入策略时，机构AI可能通过高频交易制造虚假突破信号，诱使散 户AI集体入场后反向操作，而这种交易陷阱很多散户AI难以规避。 AI的崛起并非要取代人类，而是辅助人类更高效地处理信息。对于散户而言 ...

AI大发展，有广告称可以让散户投资者使用AI炒股。但事实上，AI炒股并不简单，AI的交易策略需要 实时更新，固化的AI极易成为更高端AI的猎杀对象。对于一般散户而言，用AI炒股并不靠谱。 例如，当大量散户AI同时执行突破买入策略时，机构AI可能通过高频交易制造虚假突破信号，诱使散 户AI集体入场后反向操作，而这种交易陷阱很多散户AI难以规避。 AI的崛起并非要取代人类，而是辅助人类更高效地处理信息。对于散户而言，真正的智慧不在于盲目 追逐技术，而在于认清自身局限，既不被AI万能论冲昏头脑，也不否定其技术价值。 更危险的是，部分广告将AI包装成稳赚不赔的法宝，诱导散户产生技术依赖。当投资者将交易决策完 全交给算法，却对策略逻辑一知半解时，市场的一次"黑天鹅"事件就可能让AI从提款机变成碎钞机。AI 交易对实时更新要求极高，是需要持续调试的精密策略，散户若将其视为一劳永逸的超级终端，显然太 过理想化。 实际上，AI炒股模型的建立和实时更新需要巨大的财力投入、技术研究，绝大多数散户很难做到。 AI炒股的本质是零和博弈，AI的普及正在将这场博弈推向更高维度的竞争。机构投资者凭借资源优 势，不断迭代更复杂的AI模型，这 ...

Group 1 - The core viewpoint of the articles highlights the significant impact of AI on stock trading, with a notable increase in retail investors entering the market, driven by AI tools that promise high returns [1][2] - AI trading, as an extension of quantitative trading, utilizes machine learning and natural language processing to analyze market data and make trading decisions, operating continuously to optimize strategies [2][3] - Major investment institutions have already integrated AI into their decision-making processes, with a consensus emerging on the importance of occupying the AI space in quantitative investment [2][3] Group 2 - Many brokerage platforms are adopting AI functionalities, making AI tools accessible to a wide range of retail investors, indicating a growing penetration of AI in investment practices [3] - Despite the advantages of AI, experts caution that the stock market's complexity and unpredictability mean that human oversight remains essential, and AI should be used as a supplementary tool rather than a standalone solution [3][4] - Legal uncertainties surrounding the use of AI in investment, including issues of compliance and responsibility, remain unresolved, highlighting the need for clarity in the regulatory framework [4] Group 3 - The future of AI in trading is seen as promising, with expectations for further evolution and integration of diverse data types, including social media sentiment analysis [4] - AI trading is not a guaranteed success or a scam; it requires users to have market knowledge and the ability to effectively utilize the tools available [4]

Core Viewpoint - The article discusses the rise of AI in stock trading, highlighting its advantages over traditional methods and the increasing integration of AI tools in investment processes [2][3][4]. Group 1: AI in Stock Trading - AI has become a significant player in stock trading, providing advantages such as 24/7 data analysis and decision-making capabilities, which help investors make informed choices based on technical, fundamental, news, and market sentiment analysis [2][3]. - The AI model DeepSeek, developed by a leading quantitative asset management firm, has gained popularity among retail investors, showcasing the trend of integrating AI into investment strategies [2][3]. - Major brokerage platforms are adopting AI functionalities, indicating a widespread acceptance and reliance on AI tools among retail investors [3]. Group 2: Limitations and Risks of AI - Despite the advantages, the stock market remains complex and unpredictable, and AI should be used as a supplementary tool rather than a standalone solution [3][4]. - There are concerns regarding the reliability of AI-generated data, potential biases, and the inability of AI to fully grasp market emotions or predict unforeseen events [3][4]. - The article warns of fraudulent practices in the market, where some entities misrepresent AI tools to lure retail investors, leading to regulatory scrutiny and actions against such practices [3][4]. Group 3: Future of AI in Investment - The future of AI in the investment sector is promising, with expectations of further evolution and integration of more diverse data sources, including social media sentiment analysis [4]. - AI in stock trading is not a myth or a scam; it is a tool that requires users to have a solid understanding of the market and the ability to utilize these tools effectively [4].

（原标题：当A股遇上AI，股神的诞生？） 21世纪经济报道记者 章驰 沪指创十年新高，但比大盘更疯的是，朋友圈的AI股神！ AI模型和技术虽然可以用于金融数据分析，但它具体有没有构成违规荐股及投顾服务，甚至一旦AI大 模型涉及投资领域的合规问题时，责任权属该如何界定？这些问题目前法律界还没有统一的定论，责任 人类炒股太容易受贪婪与恐惧影响，而AI完全基于数据逻辑操作。可以说在这个赛道里，AI真是赢麻 了！ 实际上，不少大型投资机构早已开始将AI纳入投资决策流程。今年初爆火的DeepSeek，本身就是国内 头部量化资管幻方量化旗下公司的AI大模型。国内多家百亿级量化私募多年以前就已经纷纷开始布局 AI领域，量化投资的技术迭代基本上与AI的技术迭代同步，抢占AI高地已成为共识。 目前，多数券商平台也纷纷接入DeepSeek部署，加码AI功能。股民们用的软件基本都有一个AI入口， 所以AI其实已经渗透到了广大股民的投资过程中。 不过专业人士们都知道，股市是一个复杂且不确定的系统，并不具备规律性，单纯靠AI来战胜市场是 很难的。尽管有了AI，还是必须"以人为主，机器为辅"，把AI作为辅助工具来提高信息获取、分析和 决 ...

抖音账号"侃哥说财经""落叶巅峰"、微信公众号"小海豚大梦想""风清扬大侠"、微博账号"浪沙淘金 侠""牛遍天下-"、快手账号"财经老韭菜""金叶子财经"等，通过煽动性或暗示性话语，引导投资者付费 加群跟投买入个股、暗示预测个股走势、宣扬买某些股票稳赚不赔，进行非法荐股。涉及的账号已被依 法依约关闭。 5月24日，国家网信办披露，近期，国家网信办会同金融管理部门依法处置一批账号、网站。具体来 看，这些账号、网站涉及散布资本市场不实信息、开展非法荐股、炒作虚拟货币交易、散布金融领域黑 灰产信息等。 此前，南都·湾财社曾就非法荐股、金融黑灰产等乱象进行报道，揭发行业背后的"吸粉—引流—拉群— 收费"等灰色产业链，助广大投资者对此提高警惕。 发布资本市场不实信息、非法荐股等 国家网信办：关闭！ 据国家网信办，部分典型案例如下： "爱股票APP"等账号发布资本市场不实信息。 微博账号"爱股票APP"、抖音账号"价值发现者"发布转融通、融资融券有关制度安排等不实信息。微信 公众号"杰克船长宏观策略"散布有关量化基金监管政策谣言。百度百家号"北熊喵"发布资本市场交易时 间调整等虚假信息。涉及的账号已被依法依约关闭。 "侃 ...

Core Viewpoint - The rise of AI-driven investment advisory services is reshaping the traditional investment consulting landscape, driven by regulatory changes and evolving investor demands for personalized and efficient services [5][6][7][9]. Group 1: Industry Background - The investment advisory industry in China faced significant challenges from 2010 to 2016, leading to a proliferation of licensed institutions, which resulted in regulatory scrutiny and the eventual cessation of new advisory licenses in 2016 [5][6]. - As of April 2024, only 78 institutions hold the Securities Investment Consulting Business Qualification Certificate, indicating a shift to a stock competition phase in the industry [6][7]. - Traditional advisory services are characterized by a high client-to-advisor ratio, with an average of 2,750 clients per advisor in China compared to 156 in the U.S., highlighting inefficiencies in personalized service delivery [8][21]. Group 2: AI and Smart Advisory - The emergence of AI models presents a new approach to investment advisory, allowing for real-time analysis and personalized recommendations, which traditional methods struggle to provide [10][17]. - Smart advisory services are increasingly integrating real-time data and personalized insights, enhancing the overall user experience compared to traditional models [17][19]. - The ability to access timely information, such as earnings call transcripts, significantly improves the efficiency of smart advisory services, addressing the information gap between individual investors and institutions [18]. Group 3: Market Opportunities - The traditional advisory model's limitations create opportunities for smart advisory services to capture the "long-tail market," which consists of clients that are not effectively served by conventional methods [23][25]. - The growing interest in smart advisory services among retail investors is evident, with significant subscription numbers reported for platforms like Tonghuashun, indicating a potential revenue stream for these services [24]. - The projected revenue from smart advisory services for Tonghuashun could reach between 384 million to 745 million yuan annually, showcasing the financial viability of this market segment [24].