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股价再创历史新高 72万散户“战胜”机构:工业富联1.6万亿市值的水位与暗涌 | 钛媒体

作者:周健 文章来源:钛媒体

2026-06-09 10:41

作者:周健 文章来源:钛媒体

2026-06-09 10:41

邦小白快读

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本文核心讲了2026年工业富联股价突破历史新高、市值达1.6万亿元,这场行情是72万散户接盘机构抛盘造就的,背后存在明显估值错配和风险,核心干货如下

1. 行情核心特征:机构资金从抱团重仓转为系统性出逃,两个季度内持仓市值累计减少超70%,散户逆势进场抱团,股东数半年从47.6万户增至72万户,托举股价创新高,散户心态分为坚定长期持有、浮盈但进退两难、落袋为安三类,心态分化暗藏抱团松动隐患

2. 实操风险提示:当前工业富联滚动市盈率达39.57倍,是电子制造行业平均估值的近4倍,但公司常年毛利率仅7%左右,净利率不足5%,仍属传统代工属性,AI业务尚未拉动毛利率提升,当前超六成市值属于题材溢价,若业绩不及预期很可能触发戴维斯双杀和散户踩踏,需警惕泡沫风险

本文以工业富联借AI风口实现估值跳升的案例,给科技制造领域品牌商带来以下干货参考

1. 资本与消费趋势:当前AI算力是全市场共识的长线景气赛道,只要绑定赛道叙事,就能获得资本追捧,传统代工企业也能获得比肩自研AI科创企业的估值水平

2. 品牌转型启示:工业富联脱胎于传统富士康代工体系,通过绑定AI算力赛道,打出AI服务器代工龙头、高速互联高市占、液冷技术领先三张牌,重新塑造了科技企业的品牌认知,成功获得资本和投资者的认可

3. 风险提示:品牌绑定赛道叙事需要实打实的业绩支撑,没有核心技术壁垒、盈利水平跟不上估值的话,最终必然会面临估值回归,损害品牌长期价值,需要避免单纯靠概念炒高估值的做法

本文围绕AI算力赛道下工业富联的行情变化,给涉足AI硬件领域的卖家带来以下干货参考

1. 市场机会层面:AI算力是未来十年确定性增长赛道,全球云计算巨头未来数年有万亿级别的算力资本开支刚需,AI服务器代工、高速互联、液冷技术相关业务都有明确的增量增长空间,头部玩家已经率先享受赛道红利

2. 风险提示层面:当前AI赛道存在明显炒作泡沫,上游核心芯片、元器件被海外厂商垄断,代工环节议价权薄弱,即便订单放量也很难跳出低毛利困局,当前估值已经明显高估,一旦AI大模型落地节奏放缓,订单增速下滑就会引发估值回调

3. 操作参考:不要被情绪性炒作带偏,布局赛道要锚定自身业绩兑现能力,不要过分依赖赛道叙事,同时要警惕散户抱团带来的大幅行情波动风险

本文关于工业富联的发展现状,给电子制造类工厂带来以下干货启示

1. 商业机会层面:当前AI算力产业热潮下,AI服务器、高速交换机、液冷相关硬件需求爆发,工业富联作为代工厂已经吃到红利,全球AI服务器代工市占率超40%,800G交换机市占率达73.8%,相关赛道给制造工厂带来明确的增量机会

2. 产品升级方向:传统制造工厂可以布局高附加值的AI相关新业务,比如高速互联产品、自研液冷技术方案,工业富联自研液冷技术可将机房PUE降至1.05-1.06,散热能力远超行业平均,已经构筑起差异化竞争壁垒

3. 转型启示:传统代工工厂可以依托AI风口实现价值升级,但要突破低毛利的代工宿命,必须掌握差异化核心技术,提升自身议价权,避免陷入只靠概念、没有业绩支撑的估值泡沫陷阱

本文围绕AI算力产业发展下制造企业的资本表现,给相关To B服务商带来以下干货

1. 行业发展趋势:AI算力产业热潮已经带动大量传统电子制造企业启动升级转型,纷纷布局AI服务器、高速互联、液冷等相关新业务,产业升级需求旺盛,市场多空分歧也催生了投资服务、技术服务、咨询服务的大量新增需求

2. 核心客户痛点:传统代工企业转型AI硬件赛道,核心痛点是低毛利困局难以突破,上游核心元器件被海外厂商垄断,自身议价能力弱,靠赛道叙事获得高估值但缺乏业绩支撑,资本信心容易动摇,给企业经营带来很大不确定性

3. 业务方向参考:服务商可以围绕AI相关新技术提供配套技术研发服务,也可以为企业提供估值管理、投资者关系管理服务,帮助企业实现业绩和估值匹配,化解泡沫风险,把握产业升级红利

本文关于工业富联的估值拉锯行情,给资本市场平台商带来以下干货参考

1. 当前市场新特征:AI赛道炒作下,散户投资情绪高涨,对赛道共识的认可度很高,海量散户资金能够承接机构抛盘托举万亿市值,散户已经成为影响A股大盘股行情的核心力量,改变了以往机构主导大盘行情的格局

2. 需要防控的市场风险:散户抱团支撑的估值缺乏稳定的业绩锚点,且散户持仓心态分化,追涨杀跌属性强,一旦业绩不及预期很容易引发集体踩踏,诱发市场大幅波动,平台需要做好风险提示和行情波动监控

3. 运营招商方向:AI算力赛道相关标的对散户吸引力很强,平台可以围绕AI算力赛道引入转型中的优质制造企业,同时做好投资者教育工作,提示脱离基本面的炒作风险,维护市场稳定运行

本文呈现了AI产业热潮下A股市场的新动向与新问题,给产业研究者提供了丰富的鲜活研究素材,干货如下

1. 产业新动向:AI算力热潮已经从核心科创领域渗透到传统制造领域,传统代工企业可以借AI风口实现估值跳升,同时A股出现了散户抱团战胜机构的另类行情,海量散户资金足以主导万亿市值大盘股的走势,打破了原有市场格局

2. 需要研究的新问题:当前市场出现了严重的估值错配问题,传统代工企业依托赛道叙事获得了数倍于行业平均的估值,但业绩层面并未实现毛利率提升,这种错配对市场稳定性的影响,传统代工企业的估值逻辑重构等都是值得研究的新问题

3. 商业模式研究样本:工业富联尝试从低端组装代工厂逐步升级为AI整机柜系统方案商的转型路径,为传统制造企业转型AI硬件提供了全新的商业模式样本,其最终结局也为研究题材炒作和价值兑现提供了完整观测案例

声明:快读内容全程由AI生成,请注意甄别信息。如您发现问题,请发送邮件至 run@ebrun.com 。

我是 品牌商 卖家 工厂 服务商 平台商 研究者 帮我再读一遍。

Quick Summary

This article centers on the 2026 stock rally that pushed Foxconn Industrial Internet (FII) to an all-time high, with a market capitalization hitting 1.6 trillion yuan. The rally was fueled by 720,000 retail investors absorbing the shares that institutional investors offloaded, and the stock currently faces clear valuation misalignment and notable downside risks. Key takeaways are as follows:

1. Core characteristics of the rally: Institutional investors have shifted from concentrated heavy holdings to systematic capital flight, cutting their total position value by more than 70% over two quarters. Retail investors stepped in against the trend, pushing the stock to a new high; the total number of shareholders surged from 476,000 to 720,000 in half a year. Retail investor sentiment falls into three categories: firm long-term holders, investors sitting on unrealized gains but caught between holding and selling, and those who have cashed out profits. This divided sentiment hides the risk of the retail crowd breaking apart.

2. Practical risk warning: FII currently has a trailing price-to-earnings ratio of 39.57x, nearly four times the average valuation of the electronics manufacturing sector. The company has maintained a long-term gross margin of around 7% and a net margin below 5%, and remains fundamentally a traditional contract manufacturer. Its AI business has yet to drive an increase in gross margin, and nearly 60% of its current market cap comes from thematic premium. If earnings fall short of expectations, a Davis Double Play and retail sell-off stampede are very likely, so investors should be alert to bubble risks.

This article uses FII's valuation surge on the AI hype tailwind as a case study to deliver key insights for brand owners in the technology manufacturing space:

1. Capital and consumer trends: AI computing power is widely recognized as a long-term high-growth track by the entire market. Any company that aligns itself with this narrative can attract capital enthusiasm, and even traditional contract manufacturers can reach valuation levels on par with independent AI innovation companies.

2. Brand transformation takeaways: Spun off from traditional Foxconn's contract manufacturing system, FII repositioned itself as a technology company by tying itself to the AI computing power track, highlighting three core strengths: leading AI server contract manufacturing, high market share in high-speed interconnect products, and advanced liquid cooling technology. This rebranding has successfully won recognition from capital and investors.

3. Risk warning: Aligning a brand with a hot track narrative requires solid earnings support. Without core technical barriers and profit growth that matches valuation, a valuation correction is inevitable in the end, which will damage a brand's long-term value. Companies should avoid driving up valuations purely through concept hype.

This article analyzes FII's price movement against the backdrop of the AI computing boom to deliver key insights for sellers active in the AI hardware space:

1. Market opportunities: AI computing power is a high-certainty growth track for the next decade. Global cloud giants have trillion-yuan capital expenditure needs for computing power expansion over the coming years, creating clear incremental growth for AI server contract manufacturing, high-speed interconnect, liquid cooling and related businesses. Leading players have already begun capturing first-mover benefits from the track.

2. Risk warnings: The current AI track is facing clear speculative bubbles. Upstream core chips and components are dominated by overseas players, leaving contract manufacturers with weak pricing power. Even with order growth, it remains difficult to escape the low-margin trap. Current valuations are clearly overstretched; if the deployment pace of large AI models slows and order growth decelerates, a major valuation correction will follow.

3. Operational guidance: Don't get led astray by emotional speculation. When positioning in the track, anchor strategies on your own ability to deliver earnings, don't over-rely on track narratives, and remain alert to the large price volatility risk created by retail investor crowding.

This article outlines key takeaways for electronics manufacturing factories based on FII's current development status:

1. Business opportunities: The AI computing boom has driven explosive demand for AI servers, high-speed switches, liquid cooling and related hardware, and FII as a contract manufacturer has already captured these benefits. It holds over 40% global market share in AI server contract manufacturing and a 73.8% share in 800G switches, creating clear incremental opportunities for manufacturing factories in related tracks.

2. Product upgrade directions: Traditional manufacturing factories can lay out high value-added AI-related new businesses, such as high-speed interconnect products and in-house developed liquid cooling solutions. FII's self-developed liquid cooling technology cuts data center PUE to 1.05–1.06, far outperforming the industry average in heat dissipation, and has built a differentiated competitive barrier.

3. Transformation insights: Traditional contract factories can leverage the AI boom for value upgrading. But to break free from the low-margin fate of contract manufacturing, they must master differentiated core technology to improve pricing power, and avoid falling into the valuation bubble trap of relying purely on hype without earnings backing.

This article analyzes the capital market performance of manufacturers amid the AI computing boom to deliver insights for relevant B2B service providers:

1. Industry development trends: The AI computing boom has driven a large number of traditional electronics manufacturers to launch transformation initiatives, laying out AI servers, high-speed interconnect, liquid cooling and other related new businesses. This creates strong demand for industrial upgrading, while divergent market outlooks have also generated substantial new demand for investment services, technical services, and consulting services.

2. Core client pain points: For traditional contract manufacturers transforming into the AI hardware track, the core pain point is the difficulty of escaping the low-margin trap. Upstream core components are controlled by overseas players, leaving these manufacturers with weak pricing power. While they can win high valuations via track narratives, they lack underlying earnings support, leaving investor confidence fragile and creating great uncertainty for business operations.

3. Business direction guidance: Service providers can offer supporting R&D services for AI-related new technologies, as well as valuation management and investor relations services to help companies align earnings and valuation, deflate bubble risks, and capture industrial upgrading dividends.

This article extracts key insights for capital market platforms based on the tug-of-war valuation battle around FII:

1. New market characteristics: Hype around the AI track has sent retail investor sentiment soaring, with broad consensus on the AI narrative. Massive retail capital is now able to absorb institutional sell-offs to support a trillion-yuan market cap, making retail investors a core force driving large-cap stock moves in A-shares and upending the previous market structure where institutions dominated large-cap trends.

2. Market risks to mitigate: Valuations supported by retail crowding lack a stable earnings anchor, and divided retail holding sentiment paired with the crowd's tendency to chase rallies and cut losses means missed earnings targets can easily trigger a coordinated sell-off and large market swings. Platforms need to strengthen risk disclosures and monitor price volatility.

3. Operations and business development guidance: AI computing power-related stocks have strong appeal to retail investors. Platforms can onboard high-quality transforming manufacturing companies aligned with the AI track, while strengthening investor education to warn of hype risks detached from fundamentals and maintain stable market operation.

This article presents new dynamics and emerging issues in the A-share market amid the AI boom, offering rich, first-hand research material for industry researchers. Key takeaways are as follows:

1. New industrial dynamics: The AI computing boom has spread from core innovative sectors to traditional manufacturing, allowing traditional contract manufacturers to achieve valuation surges on the AI tailwind. Meanwhile, A-shares have seen an unconventional rally where retail crowding outperformed institutional positioning: massive retail capital is now sufficient to determine the trend of trillion-yuan large-cap stocks, breaking the original market structure.

2. New research questions: Severe valuation misalignment has emerged in the current market: traditional contract manufacturers have reached valuations multiple times the industry average based purely on track narratives, with no improvement in gross margins at the earnings level. Key topics worthy of further research include the impact of this misalignment on market stability and the valuation logic reconstruction for traditional contract manufacturers.

3. Business model research sample: FII's transformation path—gradually upgrading from a low-end assembly contract manufacturer to an AI integrated rack solution provider—offers a new business model sample for traditional manufacturers looking to enter AI hardware. Its ultimate outcome will also serve as a complete observational case study for thematic hype versus value realization.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

文|公司观察

作者|周健

编辑|曹晟源

本文首发于钛媒体APP

资本市场永远在泡沫与价值之间反复摇摆,2025至2026年席卷全市场的AI算力产业热潮,将这种估值悖论在工业富联身上演绎到极致。

2026年6月3日盘中,工业富联股价突破84.95元,超过10月创下的历史最高价83.42元,市值突破1.6万亿,成为A股电子代工板块有史以来市值天花板级标的。

缔造这份万亿估值奇迹的并非公募、社保等专业机构资金,而是超72万户散户投资者;在数百家机构接连减仓出逃、批量兑现筹码的背景下,散户资金逆势入场接盘流通盘,走出散户赢机构的另类行情。

但剥开1.6万亿市值的华丽外壳,公司底层经营数据却和科技属性的市值定价形成天壤之别:公司综合毛利率常年锁定在7%左右,净利率不足5%,营收增长高度依赖代工规模放量,盈利水平始终困在薄利多销的传统制造逻辑里,和市场对标纯正AI硬件企业的高成长属性完全脱节。

数据层面的错位直观体现在估值上:当前工业富联滚动市盈率(PE-TTM)39.57倍,是A股电子制造行业平均10倍PE的近4倍,估值水位比肩拥有自研芯片、核心软硬件技术的AI科创企业。

从脱胎于富士康代工体系登陆A股,到借AI风口摇身变为算力核心标的,工业富联的资本故事已经持续两年。市场分歧从未平息:多头坚信AI服务器代工放量将倒逼公司毛利率抬升,代工龙头完成向科技企业的价值蜕变;空头笃定组装代工无核心技术壁垒、盈利天花板固化,万亿市值大半由概念炒作催生。

万亿估值的拉锯背后,72万持仓散户的资产命运,被绑在AI行业景气周期与制造业基本面的天平两端,一旦预期落空,戴维斯双杀将显示出威力。

72万散户信仰支撑股价创新高

股价冲高回落、机构持续兑现离场,散户逆势大举进场锁仓,是本轮工业富联估值逆势走高最反常的市场特征,也是万亿市值能够顶住机构抛压的底层支柱,更是72万散户实现“战胜数百家机构”的核心由来。

回溯2025年10月至2026年3月的完整行情周期,能够清晰看见散户资金从观望到集体抱团、接下机构抛盘的全过程。

2025年10月底,工业富联股价摸至83.42元阶段性历史高点,算力题材炒作迎来首轮兑现窗口,在全球AI短期降温、海外云厂商资本开支预期微调的利空催化下,股价开启断崖式回调,短短5个月时间一路下行至47.35元低位,最大回撤超43%。

彼时全市场卖方研报集体转向谨慎,多数券商预判算力题材泡沫破裂、工业富联估值将向传统代工估值中枢回归,机构资金加速离场,市场一度看空情绪拉满。但出乎全市场意料,下跌没有带来崩盘,反倒成为散户批量进场的黄金窗口,用真金白银接住机构抛出的流通筹码。

股东户数变化是散户抱团最直观的数据佐证:2025年三季度末,工业富联在册股东仅47.6万户,筹码高度集中在公募、社保、券商自营等机构手中;伴随股价腰斩级回调,从2025年年末到2026年3月末,短短半年新增25万持仓账户,股东总数一举突破72万户。横向对比全A股,72万股东户数位列全市场第十五位,远超多数万亿市值蓝筹标的。

笔者梳理雪球、东方财富股吧、同花顺圈子等投资者社区留言,并对话三名不同持仓逻辑的个人投资者,三种心态勾勒出72万散户群体的分化缩影,也埋下抱团松动的隐患。

投资者A是深耕电子板块五年的个人股民,他在2025年年底股价回落至60元附近率先底仓布局,在股价下探48元关键支撑位时选择重仓加仓,本轮股价反弹后整体持仓浮盈突破40%。“当时市场全在唱空算力泡沫,但我认准工业富联是A股稀缺的AI服务器核心代工龙头,大跌就是错杀,算力是未来十年确定性赛道,回调就是黄金上车机会。”该投资者坦言,目前仍保留七成仓位,坚定长期持有算力成长逻辑。

与之形成鲜明对比的是投资者B,同样在49元附近抄底入场,如今账面浮盈超30%,却始终处在持仓焦虑之中:“股价涨速远超行业基本面改善速度,明明财报毛利率没有太多提升,估值却蹭着算力概念一路走高,理智告诉我股价已经高估,但又害怕过早卖出踏空后续行情,进退两难。”

还有一批偏稳健的保守型散户,在持仓浮盈达到20%-30%区间便陆续减仓、甚至清仓离场,选择落袋为安。在他们看来,依靠题材炒作催生的股价上涨,高位回调风险难以预判,落袋收益远比纸面浮盈更加稳妥。

形形色色的普通投资者依托全网传播的算力赛道叙事,在股价低位达成统一持仓共识,分散在72万个账户中的海量流通筹码,牢牢锁定二级市场可交易股份,成为托举工业富联万亿市值的底层支柱,并让股价再创历史新高。

但分化严重的持仓心态也暗藏隐忧:72万散户抱团并非基于统一的业绩兑现预期,而是依靠全网流传的“AI算力长线景气”叙事凝聚共识,贪婪与恐慌两种情绪长期在散户群体内部拉扯。

一旦后续算力订单落地不及预期、财报数据持续走弱,原本稳固的筹码结构随时会出现集体松动,集中抛售极易诱发踩踏行情。

机构态度反转

如果说散户是工业富联超高估值的托底力量,那么机构资金从极致抱团到系统性出逃的态度转向,是全市场多空分歧最具象的体现。

同花顺iFinD基金持仓数据显示,短短两个季度,公募机构完成从重仓锁仓到批量清仓的极致反转,持仓规模近乎腰斩,用资金流向印证对公司估值逻辑的分歧。

2025年9月末,也就是工业富联冲击83.42元股价高点前夕,全市场重仓布局的公募基金数量创下历史峰值659只,头部公募、全国社保、头部券商自营扎堆持仓,基金合计持仓市值高达425.77亿元,机构抱团成为本轮股价冲高的核心推手。

彼时机构统一的买入逻辑落脚于:AI服务器规模化量产将打破工业富联常年低毛利困局,算力业务占比抬升推动公司从低端组装代工厂向高附加值硬件科技企业转型,估值有望对标纯正AI硬件上市公司。

转折紧随10月股价见顶如期而至,基金开启持续性、大面积减仓:截至2025年12月末,持有工业富联的基金数量骤降至471只,环比降幅28.53%,基金持仓市值减少至233.63亿元,单季度账面减少45.15%;进入2026年一季度,减持趋势进一步加剧,在册基金仅剩318只,环比再度下滑32.48%,基金持仓总市值滑落至123.47亿元,对比历史峰值,机构持仓市值累计减少超70%。数据背后既有大批量基金产品全额清仓离场,留存持仓的机构也在持续减仓,用实际操作推翻此前重仓逻辑。

笔者联络了多位不便具名的业内投研从业者,两类机构观点呈现泾渭分明的对立格局。一名此前深度重仓、后续逐步清仓的公募电子行业研究员向笔者坦言:“当初重仓布局,核心逻辑是预判AI服务器规模化落地能够打破富联常年低毛利桎梏。连续几份财报毛利率变化不明显,此前的成长预期彻底落空,居高不下的PE已经不符合产品风控标准,只能陆续清仓避险。”

与之形成鲜明反差,一位手握大额底仓的券商自营业务从业者坚持长期持仓逻辑:“不能简单套用传统代工估值标尺衡量工业富联,全球云计算巨头未来数年算力资本开支是万亿级别长线刚需,短期毛利率低迷是代工行业阶段性特征,后续海量订单落地带来的营收高速增长,足以慢慢消化当下偏高的估值,阶段性股价下跌只是市场短期情绪扰动。”

机构多空博弈带来股价宽幅震荡,一边是专业资金持续撤离,一边是散户源源不断接盘,这种错位的资金持仓结构,不断放大工业富联估值的不稳定性,也是万亿市值始终摇摆不定的关键诱因。

7%毛利率与40倍PE的价值错配

工业富联所有市场争议的核心落点,最终汇聚在一组无法调和的数据矛盾:7%上下的制造业毛利率,对标接近40倍的科技赛道市盈率,传统代工盈利底色与AI概念估值形成根本性错配,也是万亿市值背后泡沫争议的源头。

从财报硬数据看,工业富联代工底色毫无遮掩:2025年全年营收突破9000亿元,营收规模稳居国内电子制造行业首位,但全年综合毛利率仅6.98%,归母净利率不足4%;2026年一季度财报继续低于市场一致预期,当期实现营收2510.78亿元,同比增长56.52%,低于机构此前预判的3035亿元;归母净利润105.95亿元,同比增102.55%,同样不及124亿元的市场预期,叠加当期经营现金流净额同比下滑,盈利质量进一步承压。

横向同业对标更能凸显估值畸形:传统消费电子代工头部企业行业平均PE仅10倍,行业平均毛利率维持在10%—15%区间,工业富联盈利质量低于行业均值,估值却是行业平均水平的近4倍;

放眼纯正AI算力硬件赛道,手握自研芯片、核心零部件自主技术的上市公司普遍毛利率突破20%,业绩增速稳健,市场给予的合理PE也仅在20—30倍。无自研核心技术、以整机组装加工为主的工业富联,独享近40倍科技股估值,在A股制造板块实属罕见。

市场愿意为工业富联支付超高估值,唯一支撑逻辑落脚于AI服务器、高速互联等新业务的成长性,投资者普遍预期高附加值算力业务放量后,能够拉动整体毛利率跳出代工瓶颈。

多头给出三大产业逻辑支撑自身判断:

其一,AI服务器代工龙头地位稳固,工业富联全球AI服务器代工市占率超40%,是英伟达GB200/GB300系列核心代工厂;

其二,高速互联业务迎来爆发,800G以上高速交换机2025年营收同比暴涨13倍,1.6T CPO交换机实现量产落地,800G交换机全球市占率高达73.8%;

其三,自研液冷技术构筑差异化壁垒,自研超流体液冷方案可将机房PUE降至1.05—1.06,相较行业平均1.25大幅优化,散热效率远超行业平均水准,单芯片散热能力可达1500W,而行业普遍水平仅800W。

多头畅想公司发展路径是,从单纯GPU板卡组装、赚取微薄加工费的底层代工厂,升级为AI服务器整机代工,未来进一步向AI整机柜系统方案商转型,业务附加值逐级抬升带动毛利率稳步上行。

但空头反驳观点直指痛点,服务器代工本质仍是组装环节,上游芯片、核心元器件被英伟达、博通等海外厂商垄断,代工环节议价权薄弱,即便订单放量,也很难跳出低毛利代工的行业宿命,高速互联、液冷业务短期营收体量偏小,难以撬动千亿级大盘营收的毛利率拐点。一多一空的产业预判,持续拉扯着公司的估值中枢。

万亿估值隐忧

在AI赛道热度、万亿市值、散户抱团三重光环包裹之下,工业富联潜在的经营与估值风险被市场刻意淡化,对于72万持仓散户而言,短期股价涨跌并非最大风险,业绩增速放缓叠加估值中枢下移带来的戴维斯双杀,才是悬在万亿市值之上的最大隐患。

戴维斯双杀的触发条件正在逐步集齐。首先,公司营收高增长依赖全球算力资本开支的阶段性红利,伴随全球AI大模型落地节奏放缓,海外云厂商逐步收紧资本预算,AI服务器新增订单增速大概率逐年回落。

其次是估值回归的刚性逻辑,从电子代工行业历史估值测算,工业富联合理PE区间仅10-12倍,对应公允市值5000亿-6000亿元,这意味着当前1.6万亿总市值中,超六成市值由题材溢价催生。一旦后续财报验证算力业务增长不及预期,市场乐观情绪快速降温,估值向制造业合理区间回落将成为必然。

更危险的是公司的市值支撑结构。万亿估值没有长线机构资金兜底,完全依托情绪化特征显著的散户抱团。散户资金追涨杀跌属性突出,一旦股价开启持续下跌通道,极易出现集体恐慌抛售、踩踏出逃,进一步加速股价下行。

回望A股过往赛道炒作周期,从2021年新能源题材泡沫出清,到2025年人形机器人概念股估值回归,所有脱离基本面的题材溢价最终都会通过股价下跌完成风险释放。

多头仍在等待算力订单落地兑现成长,空头持续看空代工属性锁死盈利,多空博弈还在继续。

但资本市场亘古不变的规律是:题材与信仰无法永久锚定估值,唯有实打实的业绩,才能终结这场横跨万亿市值的估值拉锯,72万散户最终的盈亏结局,终将交给后续财报逐一验证。

(本文首发钛媒体APP)

注:文/周健,文章来源:钛媒体(公众号ID:taimeiti),本文为作者独立观点,不代表亿邦动力立场。

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