幻方量化2025年以56.6%的平均回报率跻身中国百亿级量化基金业绩榜第二，其强劲业绩正为其孵化的 AI公司DeepSeek提供强大的资金后盾。 据私募排排网数据，幻方量化在管理规模超100亿元人民币的中国量化基金中排名第二，仅次于宁波灵 均投资70%多的收益率。梁文锋仍持有这家资产管理公司的多数股权，该公司几年前已停止接受外部资 金。 幻方量化的出色业绩可能为DeepSeek带来更多资金支持。DeepSeek由梁文锋控股，于2023年由幻方量 化孵化。根据业内人士估算，假设1%的管理费和20%的业绩提成，该基金去年的强劲表现可能为其带 来超过7亿美元的收入。这一潜在资金规模，远超DeepSeek此前公布的开发其核心AI模型所需的不到 600万美元预算。 尽管业内部分竞争对手对该成本声明的真实性持保留态度，但母公司的雄厚财力无疑为其提供了远超行 业寻常水平的资源保障。 量化策略全面转型推动业绩 中国量化行业迎来丰收年 幻方量化的优异业绩并非孤例，它折射出中国量化行业在2025年的整体丰收。数据显示，中国量化基金 去年实现了平均30.5% 的回报率，这一数字是全球同行平均水平的两倍以上。 策略分化明显，其中纯多 ...

梁文锋 梁文锋此前曾表示，DeepSeek的研究经费来源于幻方量化的研发预算。(作者/箫雨) 幻方量化已成为梁文锋的"摇钱树"。他仍然持有这家资产管理公司的多数股权，并且在几年前就已停止 为旗下基金引入外部资金。幻方量化的强劲业绩表现有望为DeepSeek提供更多资金支持。DeepSeek是 由幻方量化在2023年孵化出来的AI公司，其多数股权同样由梁文锋持有。 "梁文锋现在无疑拥有更多资金来扩大团队规模，并为DeepSeek购置更多算力和硬件。当你的第一个创 业项目进展顺利时，你就能更好地孵化第二个项目。"上海弈泰私募基金管理有限公司投资总监李明鸿 表示。 李明鸿估算，若按1%的管理费和20%的绩效费计算，该基金去年的亮眼表现可能为其创造了超过7亿美 元的收入。这一数字比DeepSeek据称用于开发其震撼市场的AI模型的不足600万美元预算高出几个数量 级。 凤凰网科技讯北京时间1月12日，据彭博社报道，DeepSeek创始人梁文锋旗下量化对冲基金去年取得了 超过50%的收益率，进一步充实了DeepSeek的潜在资金储备。尽管DeepSeek的支出远低于竞争对手，但 它已撼动了全球科技格局。 根据深圳市排排 ...

文 ｜ 陆茗 编辑 ｜ 向现 来源｜ 南风窗(ID:SouthReviews) 封面来源 ｜ unplash 曾在小红书上炫富1.67亿年薪的清华学霸吴舰，如今正面临两起诉讼。 南风窗 . 冷静地思考，热情地生活。 清华学霸涉欺诈遭美通缉， 1.67亿年薪致赔2.55亿。 以下文章来源于南风窗 ，作者陆茗 2025年9月， 一起来自美国纽约南区联邦地区法院发起的刑事诉讼，指控吴舰犯有电信欺诈罪、证券欺诈罪和洗钱罪；另一起来自美国证券交易委员会 （下称"SEC"）发起的民事诉讼，主张判决吴舰归还不义之财、支付罚款、终身禁业。 事件要追溯到2023年1月，小红书上出现一条题为《不敢发朋友圈的》的匿名帖称："工作5年赚到了刚毕业时候想不到的数字……想找个没人的地方偷偷 炫耀下。" 帖子配了一张摄屏照，显示发帖人2022年的薪资收入达到2350万美元，约合人民币1.67亿元，是上一年的10倍——发帖人称，原也想过此举可能被同事认 出来，但很快打消了顾虑，直言："感觉我也不需要那么在意。" 社交平台上的帖子显示， 发帖人2022年的薪资收入达到2350万美元，约合人民币1.67亿元，是上一年的10倍 戏剧化的是，SEC ...

Core Insights - The article discusses three core strategies for achieving non-labor income (windfall) through legal and compliant means: information asymmetry, regulatory gaps, and resource reconfiguration [1][2][5] Information Asymmetry - Information asymmetry is defined as "I know what you don't know," where investors capture value by obtaining and interpreting key information before the market reacts [1] - Specific methods include accessing policy drafts, expert meetings, and industry research to gain insights on future events, such as technological breakthroughs or financial disclosures [1] - Examples include investors profiting from early knowledge of new energy technology breakthroughs or cross-border e-commerce leveraging price differences between markets [1][2] Regulatory Gaps - Regulatory gaps refer to the "unrefined areas" within regulatory frameworks, where investors can capture benefits by exploiting time, space, and cognitive differences in rule-making and enforcement [2] - Examples include early investments in cryptocurrencies during regulatory voids or utilizing tax incentives in free trade zones to reduce operational costs [2] - The article emphasizes the importance of understanding the fine line between legal tax optimization and illegal tax evasion [2] Resource Reconfiguration - Resource reconfiguration focuses on optimizing and creatively combining resources to unlock hidden or new value, breaking the "inefficient equilibrium" of existing resource allocation [3] - Strategies include vertical integration to control supply chains, horizontal integration through mergers, and creating platform ecosystems to enhance industry competitiveness [3] - Notable examples include Tesla's vertical integration in battery production and energy solutions, which reduces costs and enhances delivery efficiency [3] Sustainable Wealth Growth - The article stresses that the sustainability of wealth growth through these strategies relies on building systemic capabilities rather than relying on luck [5] - Key capabilities include information acquisition, regulatory interpretation, resource integration, and risk control [7] - The successful application of these strategies requires deep insight, rapid response, strict risk management, and adherence to legal compliance [5][7]

Group 1 - The emergence of AI models like DeepSeek in China reflects a significant trend where top AI companies are targeting quantitative fund firms on Wall Street for commercialization opportunities [1] - AI companies such as Anthropic are actively recruiting quantitative researchers, indicating a shift in talent acquisition strategies within the AI sector [1][2] - The competition for quantitative talent is intensifying, with AI firms offering attractive compensation packages that rival or exceed those in traditional finance [2][4] Group 2 - Wall Street's entry-level quantitative analysts earn around $300,000, excluding bonuses, while AI companies offer comparable or higher base salaries with equity-based compensation [4] - Companies like Anthropic are seeking quantitative analysts for their analytical skills, which are crucial for developing advanced AI systems [4] - The competition between Silicon Valley and Wall Street is escalating, with AI companies gaining an advantage due to the absence of non-compete agreements in California [5] Group 3 - The trend of AI companies recruiting from Wall Street signifies a potential shift in the financial services landscape, as these firms may begin to directly compete in financial markets [4][5] - The rise of AI models like DeepSeek suggests that the battle for talent and innovation in technology will become increasingly fierce among major tech players [5]

Core Insights - The article discusses the increasing competition between AI companies and traditional financial firms, particularly in the recruitment of talent from quantitative finance backgrounds [1][2][3][4][5] Group 1: AI Companies' Recruitment Strategies - AI companies like Anthropic are actively recruiting quantitative researchers, indicating a shift in focus towards Wall Street talent [1][2] - OpenAI and Perplexity AI have also engaged in similar recruitment efforts, highlighting a trend among leading AI firms to attract talent from the finance sector [2] - The financial incentives in AI, including higher salaries and equity compensation, are drawing talent away from traditional finance roles [2][3] Group 2: Talent Competition Dynamics - The competition for quantitative talent has intensified, with AI companies increasing their hiring by 12-18% over the past 12-18 months [3] - Entry-level quantitative professionals on Wall Street can earn up to $300,000 in base salary, excluding bonuses, while AI firms offer comparable salaries supported by equity [3] - Notable quantitative firms like Jane Street are losing their appeal to top talent, who are more excited about contributing to groundbreaking AI projects [3][4] Group 3: Skills Overlap and Industry Trends - The skills required in quantitative trading, such as analyzing large datasets and reducing algorithmic latency, are highly relevant to AI development [4] - Anthropic emphasizes the importance of rigorous analytical thinking and empirical research methods, which align with the challenges of developing advanced AI systems [4][5] - The ongoing recruitment of finance professionals by AI companies suggests a potential future where these firms may expand into financial services products [5]

Market Overview - The A-share market showed a strong weekly performance, with the Shanghai Composite Index rising by 2% and breaking last week's high, indicating a bullish trend [1] - Despite the positive weekly performance, daily indicators suggest some weakness, particularly with the appearance of a small bullish candle with a lower shadow on Thursday, indicating potential fatigue in the upward movement [1] - The regulatory authorities clarified that there will not be a large-scale expansion of IPOs and encouraged long-term capital to enter the market, signaling support for the current market conditions [1] Sector Opportunities - The robotics sector has shown strong performance, but the company has exited positions due to perceived high valuations and anticipates a divergence in performance among different robotics concepts [2] - The innovative pharmaceutical sector is viewed as having significant future opportunities despite current high valuations, driven by a fundamental shift in the market's interest [2] - The STAR Market Index is expected to benefit from a bullish trend, with a focus on long-term opportunities in artificial intelligence and technology stocks [2] Fund Management Trends - There is a noticeable trend of funds implementing purchase limits, with notable examples including the healthcare fund managed by Guo Lan, which limited single accounts to 100,000 yuan, reflecting a more cautious approach among fund managers [3] - The increase in fund sizes is seen as a potential challenge for performance, as larger scales can complicate management and lead to underperformance [3] - The trend of fund limits is not necessarily indicative of a market peak, and the future development of public funds is expected to be more sustainable [3]

Core Viewpoint - The current A-share market is experiencing a significant adjustment due to high crowding in small-cap stocks, leading to a breakdown of the "barbell strategy" among investors [2][5][14]. Market Sentiment - Recent market sentiment has turned negative, with a sharp decline observed on Friday, causing anxiety among investors [2]. - The lack of catalysts since May has contributed to the current market conditions, with the market's upward momentum being limited [6][7]. Historical Context - Historically, small-cap indices have experienced significant pullbacks, with the frequency of these pullbacks increasing from once a year to multiple times a year since 2022 [3][4]. - The volatility in the market has been exacerbated by quantitative funds outperforming subjective funds, leading to increased fluctuations [4]. External Factors - The current geopolitical climate, particularly the uncertainty surrounding U.S.-China negotiations, is causing unease in the market [8][11]. - Despite some positive economic data, structural issues remain, particularly in consumer spending, which is heavily reliant on subsidies [9][10]. Market Dynamics - The A-share market is currently in a typical oscillation phase, with resistance at 3400 points and support from policy measures and liquidity [13]. - The market is expected to remain in this oscillation until a significant catalyst emerges [18]. Potential Catalysts - Three potential catalysts could lead to a market breakthrough: 1. Positive developments in U.S.-China negotiations, such as the cancellation of fentanyl tariffs [15]. 2. Major technological advancements that enhance productivity across domestic industries [16]. 3. Unexpected stimulus policies in real estate, consumption, social security, and finance to boost domestic demand [17]. Investment Strategy - The focus remains on technology as the main investment theme, with current adjustments in the tech sector presenting attractive value opportunities [20][21].