Santoli Says Big Tech AI Capex Keeps U.S. Bull Market Alive

Santoli：科技巨头AI资本开支维系美股牛市 企业盈利与激进的AI基础设施支出正保护美股免受高利率和不断膨胀的国债影响。 在本期节目中，主持人和Michael Santoli分析了尽管面临宏观逆风、高利率和不断攀升的政府债务，市场仍持续展现出韧性。他们深入剖析了程序化交易机制、散户资金流动行为，以及大规模AI基础设施支出如何改变超大型科技公司的股价与自由现金流比率指标。结合历史市场变迁，嘉宾们讨论了多空双方的不对称性、像Stripe收购OpenRouter这类备受瞩目的科技并购交易，以及为何在市场动态演变时调整旧规则至关重要。 关于交易的心理学研究表明，活跃交易者和赌徒往往更容易沉迷于结果揭晓前的期待状态，而非经济回报本身。 (2:08) 在信息过载的时代，现代财经记者或博主的专业技能已从获取一手消息渠道，转变为筛选、综合信息以及寻找历史类比。 (18:28) 真正的牛市往往只有在事后才能被辨识；身处其中的投资者通常会将其感受为充满不确定性的熊市反弹。 (18:28) 由于公众对市场预测和确定性有着强烈需求，尽管市场本质上具有不可预测性，华尔街仍持续不断地提供市场预测。 (23:04) 居高不下的美国政府债务负担和不断上升的债务利息成本构成了结构性宏观逆风，映射出类似20世纪90年代初的财政压力点。 (33:01)

CNBC senior markets commentator Michael Santoli and co-hosts Downtown Josh Brown and Michael Batnick analyze why structural shifts in corporate profitability, investor psychology, and algorithmic trading keep the current market resilient despite macroeconomic crosscurrents. Macro Mechanics and the Sovereign Debt Burden (29:47) The hosts distinguish between the commercial borrower mindset and macro bond mechanics. While former President Donald Trump argued that national economic health should earn lower interest rates like Switzerland's, market yields rise during strong economic growth because central banks tighten policy to control inflation. Long-term yields face upward pressure from multiple converging systems, including elevated corporate bond issuance of $1.7 trillion and persistent government debt issuance projected to add $2 trillion next year. Santoli compares the national debt, now near $40 trillion, to an autoimmune condition that worsens under market stress. Annual interest payments have climbed to roughly 3% of GDP, returning to early 1990s levels. However, unlike that era's temporary fiscal discipline and eventual budget surplus, current structural headwinds—especially worsening dependency ratios with fewer workers supporting retirees—make a return to budget balance significantly harder. Structural Resilience and the Rotation Dynamic (37:14) Despite high interest rates, geopolitical tensions, and cooling momentum among megacaps, the broader market remains elevated. Santoli explains that earnings growth is buoyed by nominal GDP running around 6% alongside an ongoing transfer of value from labor to corporate balance sheets. In addition, the modern S&P 500 is heavily concentrated in high-margin business-to-business and tech names; semiconductors comprise roughly 18% of the index, while four hyperscalers account for 16%. Market stability is reinforced by algorithmic factor-neutral positioning that produces rotations under the surface without full index drawdowns. Citing Bespoke data, the group notes the absence of an 'all-or-nothing' market breadth day since late December 2025, the longest streak since 2001. Santoli challenges the consensus view that broad participation is essential for a bull run, referencing Michael Mauboussin's research showing strong historical markets are naturally concentrated. Over the past 15 years, divergence has overwhelmingly resolved as lagging sectors catching up rather than market-wide collapses. Retail Flow Asymmetry and Options Infrastructure (45:03) The panel explores the structural behavioral differences between retail and institutional investors. Unlike multi-strategy hedge funds bound by strict drawdown limits and quarterly redemptions, individual retail accounts do not face forced liquidations during paper losses unless pressured by margin calls. Historical data from Vanguard during the COVID-19 crash and recent retail inflows into semiconductor ETFs illustrate that individual investors systematically accumulate shares through sharp pullbacks. Furthermore, the explosive growth of zero-dated options and options-income ETFs acts as a stabilizing mechanism. Younger retail traders consistently pay high premiums for speculative upside calls, which are supplied by covered-call ETFs owned by retirees seeking yield. This continuous options decay creates an automated, daily mean-reverting pressure that keeps the broader market range-bound and dampens volatility. AI Capex Hype and Cycle Clues (51:48) Examining market multiples, the group notes that the forward price-to-earnings ratio compressed from its 23x peak due to strong earnings execution. However, forward price-to-free-cash-flow stands at 30x because tech leaders have shifted from asset-light operations to aggressive, capital-intensive AI infrastructure spending. Emulating early Amazon strategies, management teams willingly sacrifice near-term free cash flow to establish strategic scale, though competing multi-billion-dollar outlays risk compressing aggregate return on investment. Skepticism emerges around late-cycle valuation extremes, exemplified by Stripe's reported acquisition of OpenRouter for $7 billion to $7.5 billion against just $13 million in revenue. Brown warns that market sentiment shows signs of top-heavy excess when Wall Street pivots from fundamental corporate analysis to obsessive supply-chain specialization—such as retail analysts pivoting to gas turbine power mechanics or firms issuing thematic single-supplier ETFs—repeating patterns observed in past tech cycle peaks. While corporate earnings power and algorithmic rotations have shielded equities from macro pressures, massive infrastructure expenditures and rapid speculative revaluations echo past tech cycles. The unresolved tension is whether elevated capital spending will produce durable productivity gains or compress aggregate corporate returns when market narratives inevitably cool.

资深财经评论员Michael Santoli与主持人探讨了当下美股在高利率与巨额国债压力下的韧性机制，指出指数繁荣由强劲的企业盈利与算法主导的“完美板块轮动”支撑，但AI资本开支扩张与华尔街的过度技术狂热也暗藏估值与周期见顶信号。 宏观利率分歧与国债利息负担 (29:47) 针对Donald Trump主张经济繁荣理应降低借贷成本并以瑞士约0.5%的低利率为例的言论，Michael Santoli与Josh Brown分析指出，这一逻辑源自房地产开发商的信贷资质思维，即优质借款人理应获得更低利率。然而债券市场依赖宏观供求与通胀机制运作，在经济高热与巨额国债供应压力下，美联储收紧流动性并推高收益率。目前美国国债总额约达40万亿美元，明年国债发售预计再增2万亿美元，债务利息成本占GDP比重已升至约3%，重返1990年代初的高位水平。高企的赡养比和老龄化使当下的财政压力远比当年更难通过预算盈余解决。 算法轮动与牛市广度迷思 (37:14) 尽管英伟达动能放缓且地缘政治风险频发，美股大盘仍展现出惊人韧性。Santoli解释称，约6%的名义GDP增长叠加经济价值从劳动力向资本的转移，推动标普500指数盈利持续强劲，且利润率维持在接近历史高点的15%。量化机构与做市商算法频繁执行“完美轮动”，在抛售半导体等热点板块的同时迅速吸纳医疗或苹果等权重股，使得标普500自2025年12月31日以来创下2001年以来未见全涨全跌日的持续记录。针对市场广度的争议，Santoli援引Michael Mauboussin的研究指出，历史上的强劲牛市本质上往往伴随高集中度而非普遍上涨；但历史数据显示，当超过70%的成分股站上200日均线时，极端的多头广度反而曾数次诱发15%至20%的深度回调。 散户结构优势与期权结构效应 (48:23) 在市场资金流向分析中，散户交易者展现出了不同于传统机构的结构性优势。散户投资者无需面对对冲基金每季度的强制赎回或严格的止损清仓规则，在半导体ETF等标的大幅回撤时仍持续净买入并承受浮亏。与此同时，零日到期（0DTE）期权与备兑开仓期权收益型ETF的兴起构建了独特的市场机制：退休人员通过买入期权收益型ETF卖出看涨期权以赚取高额收益，承接了年轻散户买入虚值看涨期权的投机溢价，期权每日的时间价值衰减促成了高频的均值回归，使大盘波动维持在特定区间内。 AI资本开支隐忧与估值天花板 (51:48) 标普500的远期市盈率在达到约23倍后随盈利扩张而出现估值压缩，但远期市现率已飙升至30倍附近。科技巨头正从轻资产、高自由现金流模式转向重度基建投资，每年近1万亿美元的股票回购在很大程度上仅用于对冲高额的股权激励稀释。各巨头在AI基建上仿效早期亚马逊不惜牺牲短期自由现金流以争夺战略制高点，然而全行业数十亿美元级同步扩张恐引发投资回报率（ROI）被稀释的风险。近期Stripe被曝拟以70亿至75亿美元收购年化收入仅1300万美元的OpenRouter，三微月内估值较5月份的13亿美元暴增，引发了市场对软件聚合层和API“零售店”估值脱离基本面的质疑。 华尔街过度微观化与周期见顶信号 (75:11) 历史经验显示，热点产业狂热往往以走向成熟平庸收场。从1960年代大型机租赁概念炒作，到如今围绕AI展开的军备竞赛，市场叙事常常惊人相似。Santoli和Brown警示称，当前华尔街分析师和财经媒体普遍呈现出一种做作的狂热，从以往分析Lululemon同店销售额突变为煞有介事地高谈阔论晶圆制造良率、代币定价以及航天发动机转燃气轮机的电力工程细节。每当金融市场开始发行针对单一科技龙头供应链的细分主题ETF，或者执着于拆解底层零部件时，往往标志着投机情绪已步入见顶阶段，类似于以往iPhone拆解概念或激光雷达/电动车供应链基金在回撤中迅速消亡的历程。 本期节目梳理了当前美股在高负债、高利率环境下仍能创下新高的内在动力，但同时指出，当机构分析师陷入过度微观的技术细节吹捧、企业估值彻底脱离现金流指标时，市场往往积累了脆弱性；如何在看似牢不可破的牛市共识中识别潜在估值修正，仍是投资者面临的核心未解难题。

## Background 本期视频由 YouTube 频道 The Compound 于 2026 年 8 月 21 日发布，为《The Compound and Friends》播客的第 256 期节目。主持人 Josh Brown 和 Michael Batnick 邀请到 CNBC 高级市场评论员 Michael Santoli，共同探讨美股惊人韧性的底层动力、美国债务与利率走势、企业强劲盈利背后的动因，以及 AI 资本开支热潮、市场轮动与数十年美股历史经验给投资者的启示。 ## TL;DR 三位嘉宾深入拆解了美股在面临地缘冲突、高利率与自由现金流承压等重重隐忧下依然屡创新高的核心逻辑，指出当前名义 GDP 与财政赤字率维持高位，且标普 500 指数成分股深度受益于资本对劳动力的倾斜。节目探讨了从‘科技七巨头’向更广泛板块的‘完美轮动’机制，批评了空头不断变换叙事与‘移动球门柱’的投机心态，并分析了散户逢低买入与备兑期权 ETF 盛行的心理根源。结合《金钱游戏》等经典投资历史，他们警示投资者不应在 AI 狂热与天价并购中陷入对个股的单向情感执念，要学会辨析历史剧本并摆脱过时规则的束缚。 ## Atmosphere & style 整场对话在轻松风趣的纽约老友闲聊与极具穿透力的专业深度之间无缝切换，既有关于洋基球场拥堵和长岛南北岸生活的爆笑调侃，也有对半个世纪宏观金融周期的严肃复盘。主持人与嘉宾展现出极高的默契与互相尊重，Michael Santoli 冷静超然的‘特别解说员’视角与 Josh Brown 充满激情的实战观察碰撞出密集火花。听感如同置身于曼哈顿收盘后的一场老派金融沙龙，既充斥着对市场狂热的清醒讽刺，又洋溢着对资本市场复杂人性的由衷敬畏与智性愉悦。 ## Bulletin - [37:14](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2234s) 美股当前在宏观逆风下创出新高，核心支撑在于名义 GDP 增速与财政赤字率均达到 6% 左右，且标普 500 指数成分股以 B2B 和资本品企业为主，深度承接了经济从劳动力端向资本端的财富转移。 - [51:48](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3108s) 标普 500 的远期市盈率虽从 23 倍高位略有消化，但远期市价与自由现金流比率高达 30 倍，科技巨头激进的 AI 资本开支正在压制短期自由现金流扩张与估值弹性。 - [39:07](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2347s) 市场广度并未如空头预期的那样以强势股补跌终结，反而多次呈现弱势板块向上补涨的良性轮动，高频做市商与多策略对冲基金的因子对冲制造了指数平稳的“完美轮动”。 - [49:27](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2967s) 期权收益型 ETF 规模爆发，实质上形成了年轻人支付高额期权费追逐暴涨、退休投资者通过备兑期权收割溢价的代际财富转移与“私人社保”机制。 ## Key takeaways - [18:21](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1101s) 在海量数据喷淋的信息过载时代，投资者的核心优势已从信息不对称转变为识别该忽略什么、选择聚焦什么。 - [21:12](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1272s) 熊市终点与新牛市起点在当下往往无法确知，2009 年多数人将其视为熊市反弹，唯有事后复盘才能真正定义拐点。 - [23:04](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1384s) 公众对“神秘经纪人”等精准预测的狂热迷信，本质是无法面对无人知晓未来的现实，市场供给预测只是在迎合大众的确定性渴望。 - [28:56](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1736s) 特朗普对“经济好利率反上升”的困惑源自地产借款人直觉，而宏观债券市场和央行调控则是基于经济过热与通胀风险来定价利率。 - [33:04](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1984s) 当前美债利息支出已占 GDP 的 3% 左右，回到 1990 年代初的高位水平，但如今美国缺乏当年下降的债务比率与年轻人口红利，AI 生产力繁荣面临更重宏观阻力。 - [36:02](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2162s) 认为国债是“左手倒右手欠自己钱”的观点过于简单化，债务失控终将引发资本挤出效应，侵蚀更具生产力的资本配置。 - [39:07](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2347s) 做市商采用一篮子交易与因子中性策略日内相互对冲，催生了半导体下跌但权重医疗上涨、指数整体波澜不惊的“完美轮动”。 - [47:40](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2860s) 401(k) 定投散户在历次回撤中展现出极强的持仓韧性，与多策略对冲基金亏损 5% 即被迫硬止损形成鲜明对手盘。 - [51:48](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3108s) 科技巨头高管深受贝索斯股东信再投资哲学熏陶，甘愿主动牺牲短期自由现金流全力下注 AI 基础设施。 - [54:52](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3292s) 空头往往在市场叙事上“不断移动球门柱”，从集中度过高转向国家债务危机，绝口不提原有崩盘借口已被市场通过补涨化解。 - [01:02:07](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3727s) 标普 500 企业高管经历过关税、疫情、高通胀与文化战争的连续锤炼，展现出极强的利润率防御与经营韧性。 - [01:05:18](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3918s) 拜伦·韦恩的经历证明死守旧经验是危险的；1958 年美股股息率首次跌破国债收益率时，固守旧教条做空的经理人悉数遭到淘汰。 - [01:10:29](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4229s) 《金钱游戏》道破股市核心本质——“股票根本不知道你拥有它”，投资者不应将买入成本等单向情感寄托在持仓之上。 - [01:15:11](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4511s) 散户与交易员硬背半导体良率和燃气轮机细节、抢发垂直生态 ETF，显现出资本狂热进入微观拆解的阶段性见顶信号。 ## Detailed walkthrough ### [00:00](https://www.youtube.com/watch?v=5GGUoaayVqE&t=0s) 洋基球场回忆与拥堵之夜 节目在一阵轻松的闲聊中开场。主持人与嘉宾聊起纽约洋基队（New York Yankees）最近连赢了几场比赛，虽然赢得磕磕绊绊，但总算稳住了局势。迈克尔·巴特尼克（Michael Batnick）提到自己以前曾买过球场季票套餐，但如今却很难对用了大约17年的新洋基体育场产生感情，总觉得它缺少了当年老球场的灵魂。 乔什·布朗（Josh Brown）随即分享了一段在洋基体育场看 Jay-Z 演唱会的“灾难级”经历。当时主办方没有使用洋基队自有的安保团队，而是外包给了第三方安保公司。现场售出了大约50,000张门票，但体育场外还聚集了大约50,000名没有票的人——有人以为能混进去，有人自称在贵宾名单上，还有大批人纯粹是因为周边是全球人口最密集的社区之一，专程跑来在场外听现场声浪凑热闹。 整场演出的人流组织混乱不堪： - 入场整整花了2个小时排队，出场同样耗费了2个小时，人挤人寸步难行。 - 巨大的洋基球场原本有6个大门，安保方却仅仅开放了2个大门，据推测是为了减少检查点以控制出场人流，结果反而造成了严重踩踏隐患级别的滞留。 - 乔什周六去的情况还算稍好，而周日场次 Jay-Z 甚至拖到凌晨12:30才登台。 三人感叹这场里程碑式的演职人员应该为此制作纪录片，并顺势聊到绿洲乐队（Oasis）即将登陆 IMAX 甚至可能进驻 Sphere 场馆的巡演。话题还带到了经常出没在洋基球场的 CNBC 同事乔·特拉诺瓦（Joe Terranova），随后以一段关于9月11日看球安排与犹太假期的打趣对话，自然切入了正题。 --- ### [02:08](https://www.youtube.com/watch?v=5GGUoaayVqE&t=128s) 首席市场评论员的自我修养：解说员而非操盘手 乔什以半开玩笑的调侃正式开启对嘉宾迈克尔·桑托利（Michael Santoli，CNBC 高级市场评论员）的访谈，直球发问：“你是否认为自己是有史以来最伟大的财经记者？”桑托利谦逊地笑着回应称自己尽量不这么自我膨胀，乔什则极为认真地解释道，在所有报道现代金融市场的记者中，桑托利是最像“实战从业者”（practitioner）的一位，他的洞察力绝非普通冷眼旁观的媒体人可比。 桑托利坦承并接受了这一赞美，但他把自己定位为一名“深谙比赛精髓的特别解说嘉宾”（color commentator）——他深知这场资本游戏是如何运转的，而非仅仅居高临下、刻板中立地播报新闻。然而，令人意外的是，桑托利表示自己从未对亲自下场交易或操盘产生过哪怕一丝兴趣： - **毫无操盘欲望**：尽管多年来无数次有买方（Buy-side）和卖方（Sell-side）机构向他抛出橄榄枝，力邀他加盟做策略师或合伙人，但他从未动心。 - **缺失投机天性**：他从未幻想过在平行宇宙里创办一家收取“2/20”（2%管理费+20%收益分成）的对冲基金去靠宏观预判赚大钱，他骨子里完全没有赌博的冲动。 - **裁判员视角**：乔什指出桑托利就像棒球场上的主裁判，只负责判定“好球与坏球”（balls and strikes），从不对市场走势妄下绝对的单边预测。 谈到赌徒心理时，几人探讨起一项行为学研究：赌徒真正上瘾的往往不是“赢钱”的瞬间，而是“结果揭晓前那一刻的悬念与战栗”。巴特尼克对此深有共鸣，并分享了他此前在底特律雄狮队对阵纽约巨人队的橄榄球赛中下注的经历——当跑卫贾米尔·吉布斯（Jahmyr Gibbs）完成突破长奔、胜券在握的前一秒，那种多巴胺狂飙的快感才是最强烈的。 --- ### [05:03](https://www.youtube.com/watch?v=5GGUoaayVqE&t=303s) 误打误撞入行与金融世界的无穷魅力 桑托利回顾了自己最初进入财经报道领域的机缘。他笑称自己虽然在合同续约谈判中把“去华尔街机构做策略师”当作抬高身价的假想底牌（stalking horse），但他最初对金融并没有与生俱来的执念。 大学毕业后，他的第一份工作是在金融行业刊物《投资交易商文摘》（*Investment Dealers' Digest*，IDD）担任撰稿人。去面试时，他甚至无法百分之百确定报纸上刊登的股票行情表到底是以美元计价还是某种指数点数（由于当时股市交易代码后面带有分数单位，且没有标注美元符号）。 ```mermaid flowchart TD accTitle: 金融观察者的认知演进流程 accDescr: 展现迈克尔·桑托利从初入职场对股票计价不确定，到最终领略金融包罗万象魅力的成长逻辑。 subgraph Phase1["入行摸索"] A["大学主修历史/人文学科"] --> B["初入《投资交易商文摘》 (IDD)"] B --> C["对股票报表基础规则尚存困惑"] end subgraph Phase2["顿悟与融合"] C --> D["意识到金融是观察世界的绝佳载体"] D --> E["融合地缘政治、商业胜负与人性系统"] end subgraph Phase3["核心价值"] E --> F["追求以凝练典雅的文字诠释复杂现实"] end ``` 然而真正深入之后，桑托利发现金融市场是世间最迷人的舞台——这里汇聚了成王败寇的残酷竞争、极其复杂的运行系统，以及解释真实世界运作规律的所有切口。乔什深表赞同，并举了前一天的例子：生物医药公司莫德纳（Moderna）公布了能够在6周内制造出针对特定肿瘤的个性化癌症 mRNA 疫苗的消息，股价单日暴涨，这促使完全不懂生物医药的乔什一头扎进专业知识的研究之中。金钱贯穿了科技、地缘政治与体育，成为连接所有人类活动的纽带。 桑托利提到自己大学主修历史学，选历史就是因为它是“一门包罗万象的学科”。在金融世界里同样如此：例如要谈论石油市场，就绕不开俄罗斯与乌克兰错综复杂的历史纠葛与地缘诉求。 当被问及职业生涯最大的满足感来源时，桑托利直言，比起碰巧预测对某个涨跌点位，更让他兴奋的是写出一篇约600字的精妙专栏：文字精炼优美，结构严丝合缝，能以极高的洞察力向读者阐明复杂的市场现象。乔什由衷赞叹，这正是为什么在所有人眼中，桑托利是无可替代、甚至是有史以来最出色的市场专栏作家。 ### [08:52](https://www.youtube.com/watch?v=5GGUoaayVqE&t=532s) 财经写作与新闻跑步机：从《巴伦周刊》到电视直播 三人开场聊起了 Michael Santoli 早年专栏中的冷知识与写作风格。Josh Brown 提起 Santoli 曾写过一篇专栏，解释为什么那么多保险公司总部都设在康涅狄格州的哈特福德（Hartford）。Santoli 当时得出的结论是那里是新英格兰海拔最高的地方（后补充实际也与宽阔的河流地势有关）。Josh 笑称这个故事自己听过无数次，大家到处引用却从来不给 Santoli 署名。Josh 盛赞 Santoli 在过去近 30 年里每周坚持写作，其文字散发出散文一般的优美质感，在财经新闻界独树一帜。 Santoli 谦虚地分享了他对财经新闻业的观察。他认为记者大致分两类：一类是文字功底扎实的写作者，擅长将复杂事物表达得通俗优雅；另一类是“新闻猎犬”（News hounds），他们极具侵略性，只专注于抢先拿到独家内幕（Scoops）。Santoli 很早就决定走下“抢头条”的无休止跑步机，专注于对市场的深度诠释。这很大程度上源于他在《巴伦周刊》（Barron's）度过的 15 年——那里的节奏允许记者用整整一周时间消化各种短期杂音，在周五晚上交稿，并让周六早晨捧着实体报纸的读者读到最有价值、最富趣味性的市场精华。Josh 对比道，如今 Santoli 站在 CNBC 的直播镜头前，常要应付诸如“道指最后 10 分钟涨了 25 点是为什么”这类即时性问题，但 Santoli 无论面对长文写作还是快节奏直播都能游刃有余。 ```mermaid flowchart TD accTitle: 财经记者核心路径对比 accDescr: 对比传统独家猛料型记者与深度分析型记者的工作模式与输出方式 subgraph Hunters["独家新闻猎手 (News Hounds)"] H1["核心诉求：抢先爆料 (Scoops)"] --> H2["高强度、高频追逐内幕"] H2 --> H3["输出：即时快讯与突发动态"] end subgraph Writers["深度剖析型作者 (Santoli 风格)"] W1["核心诉求：洞察、框架与文字表达"] --> W2["沉淀整周市场走势、过滤短期噪音"] W2 --> W3["输出：系统化逻辑、散文质感与深度解读"] end ``` --- ### [11:08](https://www.youtube.com/watch?v=5GGUoaayVqE&t=668s) 赞助播客与嘉宾登场：欢迎财经媒体界的“贵族” 在赞助商 DBMF（管理期货 ETF）的广告播报之后，节目正式拉开序幕。Josh 热情欢迎新老听众，并与联合主持人 Michael Batnick 一起郑重介绍了当期嘉宾——CNBC 的资深市场评论员兼《Closing Bell: Overtime》联合主播 Michael Santoli。 Josh 称 Santoli 是“财经媒体界的贵族”，并详细梳理了他的职业履历： - 早在 1990 年代初于道琼斯通讯社（Dow Jones Newswires）开启职业生涯，报道证券行业； - 随后在《巴伦周刊》担任了 15 年的专栏作家和特写作者，声名鹊起； - 后加入雅虎财经（Yahoo Finance）担任资深专栏作家； - 2015 年 10 月正式加盟 CNBC，长期负责大盘分析、撰写专栏并出镜解盘。 Santoli 调侃感谢邀请，Josh 则解释称自己一直想请他，但由于 Santoli 负责收盘节目录制，时间恰好与播客录制冲突，今天能够成行实属难得。 --- ### [13:53](https://www.youtube.com/watch?v=5GGUoaayVqE&t=833s) Josh 的入行启蒙：锅炉房里的神秘经纪人与三样学习法宝 Josh Brown 向 Santoli 坦承了一个从未在公开场合详述的秘密：“是你教会了我什么是股票市场。”Josh 回忆，自己入行时是在长岛的一家场外低端经纪行（Bucket Shop / 锅炉房）。当时父母并不懂金融，只是托熟人安排他进去，他自己也迷茫无措。但很快，Josh 发现周围的同事和老板几乎对市场一无所知。 某天下午 4 点收盘后，大部分经纪人都去花天酒地或吸食可卡因，办公室内空无一人。Josh 走向当时唯一一个会安静坐在工位上阅读《华尔街日报》的资深老员工，向他请教：“你是我唯一看到在认真看报纸的人，你似乎真正懂行。我只是个拉皮条的无证电话推销员（Cold Caller），我到底该怎么学习股票？”那位老员工给了年轻的 Josh 三条至关重要的指引： 1. **每天必读《华尔街日报》的 C 版**：即“金钱与投资”（Money and Investing）版块。跳过 A 版（宏观政治新闻）和 B 版（商业企业新闻），死磕 C 版。 2. **每周六精读《巴伦周刊》**：要想看懂市场走势的底层逻辑，必须阅读《巴伦周刊》，老员工特别叮嘱：“除了 Alan Abelson 的专栏不要读，其他人全都要读，因为读了 Abelson 的悲观言论你会彻底绝望离开这个行业。” 3. **阅读《商业周刊》（BusinessWeek）的 Gene Marcial**：要想学会如何向客户推荐和包装个股，就必须读 Gene Marcial 的“Inside Wall Street”专栏，他是当时全美顶级的个股叙事高手。 Josh 正式从那时起养成了周六读《巴伦周刊》的习惯，而 Santoli 独特的专栏风格兼具文学性与敏锐的市场嗅觉，成为了 Josh 认识股票市场的首要窗口。 --- ### [16:05](https://www.youtube.com/watch?v=5GGUoaayVqE&t=965s) 反身性逆向主义陷阱：传奇空头 Alan Abelson 与 1987 年崩盘记忆 听到 Josh 的真情吐露，Santoli 欣然接受这份赞誉，同时也反思了自己在《巴伦周刊》后期的心路历程。他坦言，在顶尖财经周刊写作面临巨大的同行压力：读者的专业水准往往远高于作者本人。在 2010 年代初，他感觉自己陷入了一个竭力要比市场专业玩家“多看两步”的疲惫怪圈中。更严重的是，周刊的生态很容易迫使作者走向一种“反身性的逆向主义”（Reflexive Contrarianism）——为了语出惊人而刻意站在主流趋势的对立面。 两人顺着话题探讨起《巴伦周刊》历史上标志性的传奇空头 Alan Abelson。在当今社交媒体被短平快言论占领的时代，Abelson 当年那种辞藻华丽、极具讽刺意味地痛斥“盲从羊群”和精准打压明星大盘股（如微软）的长文，甚至显得有些古典和古怪。Santoli 还分享了一个关于 Abelson 的圈内轶事： - 在 1987 年著名的“黑色星期一”（Black Monday）发生之前，美股已在当年 8 月见顶并连连下跌； - Abelson 一路死空，在暴跌前夕的那个周末，他似乎在专栏中稍微松动了口风，甚至有些得意地认为世界终于承认了他的先见之明，并暗示部分优质股已经跌出了性价比； - 结果紧接着在星期一，道琼斯指数单日惨烈暴跌 22.6%； - 此后，这种惨痛的历史阴影似乎将他彻底塑造成了一个在性情上“永远无法再转多”的永恒悲观主义者。 ### [18:21](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1101s) 信息洪流中的投资认知与“过滤”的价值 三人从没人能预料 1987 年股灾的荒诞感聊起，笑称这就像巨蟒剧团（Monty Python）的幽默短剧一样出人意料。随后话题转入各自是如何理解市场的：Josh Brown 调侃自己是在 Michael Santoli 的指导下学会了股市，接着又去教 Michael Batnick；而 Santoli 则坦言其实没有人真正系统地教过他，他的认知全靠广泛汲取各种智慧、研读聪明人的观点。Josh 指出，Santoli 与他们这些博客作者最大的不同在于“信源”——博客作者通常是通过综合公开数据、研读图表来形成观点，而 Santoli 在职业生涯中始终在与一线实际管理真金白银的从业者交流。 不过 Santoli 指出，即便接触一线操盘手，在当下这个时代大家面对的现实也很接近：没人真正确切知道未来会怎样。如今整个市场早已不是信息匮乏的年代，所有人都在面对海量信息的“高压水枪式喷淋”（drinking from the fire hose）。在这种环境下，投资者很难再凭借简单的信息不对称拥有宽客式的绝对优势。 现在的核心能力不再是获取更多数据，而是知道**该忽略什么、该聚焦什么**。这也是为什么像 Santoli 这样能提炼出 800 字精简观点、梳理出关键脉络的分析师依然不可替代——大众需要有人去辨析“究竟哪一段历史剧本适用于当下”。三人笑称自己是不折不扣的“每一次都不一样”派（It's always different），因为无论如何类比过往，当下的市场环境与上一次永远有着本质的不同。 --- ### [21:12](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1272s) 熊市终点与牛市起点的定义之争 Michael Batnick 分享了他本周与 Ben Carlson 发生的一场激烈争论：**熊市究竟在何时终结？新一轮牛市又从何时开始？** Batnick 借用 NBA 球员文·贝克（Vin Baker）做比喻——你光看历史技术统计表会觉得他是个了不起的球星，但事后复盘与亲身经历完全是两码事。 从走势图上看，许多人（包括 Ben）会将 2009 年 3 月的最低点定义为牛市的开端。但 Batnick 强烈反对这一看法：在身处其中的当下，2009 年根本没人敢轻言牛市，市场经历了 2011 年的欧债危机与二次探底恐慌，真正的牛市体感直到 2012 至 2013 年才算确立。当时大家嘴里喊的不过是“熊市反弹”（Bear market rally）。 Santoli 赞同这个观点，并指出熊市终结与新牛市启动通常只能在事后复盘中被准确定义，在转折发生的当下，人们根本分不清这究竟是一轮强劲的熊市反弹还是趋势的根本扭转。当时像 Barry Ritholtz 在 The Big Picture 博客上撰写名为《熊市反弹》的文章之所以引发巨大关注甚至“骗愤怒流量”（rage bait），正是因为在 2009 年末，如果有谁胆敢公开宣称“新的长期大牛市（Secular bull market）已经到来”，旁人几乎会觉得这个人应该被关进疯人院。 --- ### [23:04](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1384s) “神秘经纪人”的传奇与公众对先知的狂热迷信 这场关于 2009 年能否看清大势的讨论，引出了 Santoli 当年在《巴伦周刊》（Barron's）工作时一个极具传奇色彩的故事——“神秘经纪人”（The Mystery Broker）。2007 年市场见顶前夕，一位默默无闻的财务顾问/经纪人曾给 Santoli 发信，精准预警市场行将崩塌；到了 2009 年夏末（大约 8、9 月），该经纪人再次来信，斩钉截铁地表示金融危机已经结束，必须将其作为全新牛市来布局。Santoli 在不透露对方姓名的情况下报道了这些观点，未料引起了读者的狂热追捧。 ```mermaid flowchart TD accTitle: "神秘经纪人"追踪现象分析 accDescr: 展现公众在面对不确定市场时，如何将普通顾问神化为拥有先知能力的偶像 subgraph Origin["事件起因"] A["2007 年来信预警见顶"] --> B["2009 年夏末断言危机结束并转向看多"] end subgraph Hype["大众迷信反应"] B --> C["Santoli 匿名撰写专栏"] C --> D["读者在 Twitter 狂热追更"] D --> E["公众臆想其为华尔街大佬或拥有魔法预测力"] end subgraph Reality["市场心理学本质"] E --> F["大众无法接受'无人知晓未来'的事实"] F --> G["'既然公众有需求，预测就必然会被供给'"] end ``` 在随后的岁月里，“神秘经纪人”几乎演变成了一个经久不衰的专栏 IP，读者们不断追问更新，甚至胡乱猜测他是不是大卫·泰珀（David Tepper）或道格·卡斯（Doug Kass）这种顶级大佬。然而 Santoli 始终强调，这只是一位公众根本没听说过的普通从业者。这一现象精准揭示了散户和公众的深层心理机制： - **迷信权威与魔法**：有调查显示多达 31% 的美国成年人相信魔法存在，公众潜意识里总幻想世界上存在某个能通过秘密信号未卜先知的“先知”。 - **供给迎合需求**：正如亚当·斯密（笔名，真名 George Goodman）在经典著作《金钱游戏》（*The Money Game*）中所写的那样——既然大众对预测有着无法遏制的需求，市场上就必然会源源不断地供给各类预测。 - **认知的固有执念**：Batnick 举例称，亲戚曾反复追问他 Josh Brown 现在还看不看好 CrowdStrike；即使解释了“长期看好网络安全赛道，但谁也无法断言个股短期走势”，对方依然执着地索求一个非黑即白的确定性答案。公众很难接受“专业人士其实同样不知道未来会怎样”的客观事实。 ### [26:43](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1603s) 财经与体育评论员的双重标准：从散户赌博潮到 Hertz 破产投机 三人就公众对各类“预测专家”的评价标准展开了调侃。Josh Brown 指出，周日 NFL 橄榄球节目的名宿解说员们围坐在一起预测比赛，无论说喜欢匹兹堡钢人队还是迈阿密海豚队，即使面对让分盘（against the spread）的胜率连抛硬币都不如，甚至输得一塌糊涂，也不会有观众在社交网络上人身攻击他们；因为大家都明白解说员只是表达偏好，受曾经效力的球队、喜欢的球员或教练影响，这无关紧要。然而，财经评论员的处境却截然不同：“我上了 CNBC，连续挑对三只股票，第四只表现不佳，就会有人骂‘Josh Brown 这个败类’。” 不过 Josh 也观察到，随着体育博彩全民化，以及体育分析正被越来越多人视为一种“金融活动”，体育解说员也开始尝到华尔街评论员的苦头——面对 Fantasy 梦幻体育和押注损失，球迷开始像痛骂 Jim Cramer 一样围攻退役球星 Howie Long。 当散户通过 Robinhood 参与零日到期期权和类赌博交易，或者在 Interactive Brokers（盈透证券）上参与预测市场时，体育竞猜与股市投机的边界彻底模糊了。Michael Santoli 回忆起疫情期间“散户抱团股”（Meme stocks）狂潮时《金融时报》（Financial Times）报道的一则轶事：记者采访了一位在俱乐部教球的高尔夫职业选手，询问他为何毫无研究就狂买已经申请破产的租车巨头 Hertz（赫兹）。对方轻描淡写地回答：“这比体育赌博强多了。如果我赌球输了，那就是彻底归零（Zero）；但如果我买进 Hertz，股价暴跌 30%，我手里好歹还剩下 70% 的钱。” 这种投机逻辑引来现场哄堂大笑，Batnick 随即调侃起自己常买的“十连串关”高赔率投注组合，称那样才能享受在多个环节同时猜错的折磨。 - **体育解说与财经评论的境遇反转**：Robinhood 等免佣券商和博彩平台的融合，让散户将体育预测视为投资工具，导致传统体育解说员承受与华尔街选股人类似的舆论压力。 - **Hertz 破产投机案例**：疫情期间散户涌入破产重组公司，散户投资者的心态演变为“至少不会像赌球那样一把输光全部本金”。 --- ### [28:56](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1736s) 特朗普的“借款人思维”：为何经济越好利率反而越高？ 节目录制现场播放了一段唐纳德·特朗普（Donald Trump）论述美国利率政策的言论。特朗普在片段中质疑道，多年前当国家公布亮眼数据时，因为国家变得更强大，利率反而会下降；而现在的体系完全扭曲了——公布的数据越好，利率反而被推得越高。特朗普抱怨称，国债利率每上升 1 个百分点（100 个基点），国家就要多承担 6000 亿美元的利息支出；如果利率下降 2 个点，国家就能大发横财；美国拥有最好的信用，甚至比瑞士更具经济统治力，却要支付远高于瑞士的借贷利率，这极为不公平。 ```mermaid flowchart TD accTitle: 利率机制认知冲突对比 accDescr: 对比地产借款人视角的信用逻辑与华尔街交易员视角的宏观调控逻辑 subgraph BorrowerLogic["特朗普/借款人逻辑 (地产开发商思维)"] B1["经济强劲 / 资产丰厚"] --> B2["企业信用评级处于最佳状态"] B2 --> B3["向银行索取更低借贷利率 / 减少利息支出"] end subgraph TraderLogic["宏观市场/交易员逻辑 (中央银行与债券市场)"] T1["经济强劲 / 消费与企业支出过热"] --> T2["潜在通胀失控风险上升"] T2 --> T3["美联储收紧货币供应 / 加息以平抑需求"] T3 --> T4["国债收益率与全社会借贷成本上升"] end ``` Josh Brown 认为，虽然特朗普口中的具体数字并不准确，但他击中了普通人的直觉痛点，其根本原因在于“特朗普是以一个纯粹借款人的视角在思考问题”。作为一名多次经历破产、被银行切断信贷的传统地产与赌场商人，特朗普的商业直觉是：只要生意向好、流水充裕、信用优良，银行就应该给予更低的贷款利率。然而，华尔街交易员和央行行长的思维完全相反：如果宏观经济持续强劲、消费和商业投资过热，决策者就必须收紧货币供应以防通胀失控，从而推升基准利率。Michael Santoli 补充道，决定美国国债收益率的并非所谓的“主权信用违约风险”，而是全球宏观资本供需；在当前美国名义 GDP 增速接近 6%、私营部门借贷投资旺盛的背景下，10 年期美债收益率维持在现有区间不仅毫不反常，而且完全符合市场规律。 --- ### [33:04](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1984s) 利率高企的“多重气象系统”与 90 年代债务历史的启示 针对当前居高不下的债券收益率，三人拆解了数股正在推高长期资金成本的合力。Josh Brown 归纳了当前的主要市场论点：其一是华盛顿长期的政治机能失调（但政治混乱早已成为常态）；其二是全球长端主权债收益率的共振上行；其三是高达 1.7 万亿美元的公司债天量发行（同比增长约 30%），大量优质高评级企业债直接与美国国债竞争有限的全球流动性；再加上地缘政治溢价和居高不下的粘性通胀。Santoli 用“多重气象系统交汇”来形容这一现象：全球对资本的渴求极为巨大，迫使债券市场必须通过提高收益率来重新定价并配给资金，以找到市场出清价（clearing price）。 Santoli 将市场对美国财政赤字的焦虑比作一种“潜在的自身免疫性疾病”：平时潜伏在体内，只有当外部压力急剧上升时才会引发急性发作，但它本身并不是瞬间暴发的单一诱因。目前的美国国债总额已接近 40 万亿美元，但市场并没有一个触发崩盘的绝对临界数字；更关键的硬指标在于，当前美国用于支付国债利息的支出已占到 GDP 的 3% 左右，这一水平上一次出现还是在 1990 年代初。 - **90 年代的财政历史镜像**：90 年代初利息占 GDP 达 3% 的局面直接催生了富商罗斯·佩罗（Ross Perot）以独立候选人身份角逐总统大选，其竞选主张完全聚焦于削减国债赤字和贸易改革。 - **政治僵局带来的意外盈余**：佩罗掀起的反赤字浪潮导致 90 年代国会与克林顿政府陷入政治制衡与僵局，阴差阳错地带来了持续的财政紧缩，最终使美国在 90 年代末实现了账面财政盈余。 - **当前 AI 繁荣面临的宏观逆风**：市场期盼当下的生成式 AI 能复制 90 年代个人电脑和互联网带来的全要素生产率跃升奇迹，但外部宏观环境已截然不同——90 年代拥有持续下降的债务与 GDP 之比，以及庞大劳动人口供养极少退休人员的人口红利；而当前高企的债务负担与劳动力老龄化，将对这场生产力奇迹构成深层的结构性阻力。 ### [36:02](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2162s) 美债总额与“左手倒右手”的逻辑 主持人和嘉宾讨论起一张关于美国未偿公共债务（Public Debt Outstanding）的图表。图表用两种颜色区分：一种是公众持有的债务（Debt held by the public），另一种是政府间债务（Intragovernmental debt）。Josh Brown 和 Michael Batnick 调侃道，市场上总有一种很轻松的说法——“我们只是欠自己的钱”，也就是说我们既是这些国债的投资者，又是最终的债务人，“拆东墙补西墙（Robbing Peter to pay Paul）”。至于政府间债务，很多时候就像社会保障信托基金（Social Security trust funds）之类的会计冲销机制，当信托基金有结余时，账面上就显示他们持有国债。 ```mermaid flowchart TD accTitle: 美国债务与持有者逻辑 accDescr: 展示美国国债的持有结构以及挤出效应的争议机制 subgraph DebtHolders ["美国国债持有结构"] A["美国未偿债务总量"] --> B["公众持有债务<br>(货币基金、401k、家庭投资)"] A --> C["政府间债务<br>(社保信托基金等会计冲销)"] end subgraph MacroRisk ["潜在风险机制"] B -. "自我安慰: 欠自己的钱".-> D["40万亿里欠自己30万亿?"] D --> E["资本挤出效应<br>(Crowding Out)"] E --> F["压制经济中更具生产力的资本用途"] end ``` 针对“反正都是我们自己在货币市场基金和 401(k) 账户里买美债，何必在意40万亿里有30万亿是欠自己”的观点，Michael Santoli 认为这种自我安慰过于简单化了。债务绝不可能无限膨胀而免受惩罚，即使是“欠自己的”，一旦跨过某个界限，它终究会产生资本挤出效应（Crowding out），剥夺经济中其他更有生产效率的资本用途，正如俗话所说，“往下全都是乌龟（Turtles all the way down）”，无法无限循环下去。 - 债务被拆解为公众持有债务与政府机构间债务两大部分。 - 普遍存在的自我安慰逻辑：“债务是我们欠自己的，我们通过养老金和货币基金持有”。 - 核心宏观隐患：过度发债最终会挤出原本可用于更高效领域的生产性资本。 --- ### [37:14](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2234s) 顽强的美股：地缘危机与AI退潮下的新高 面对美股几乎各大指数均位于或逼近历史新高，Josh Brown 提出了一个核心疑问：为什么在这么多潜在利空之下市场依然如此强劲？国际上战火未熄，霍尔木兹海峡地缘局势紧绷，按理说足以引发“能源涨停、股市跌停”的黑天鹅剧震；与此同时，高歌猛进的“科技七巨头（Magnificent 7）”并非都在拉动大盘，除了内存芯片等少数板块冲高外，英伟达走平、Meta 和微软走低，自由现金流承压，甚至有报道指出 OpenAI 的营收表现相当难堪。按照长周期牛市的正常规律，在当前的高利率环境下，标普500指数回调 12% 都不足为奇。 Michael Santoli 指出，尽管上述所有利空都可以成为大盘大幅下挫的“现成借口”，但宏观基本面为市场提供了坚实的下垫面。当前名义 GDP 增速在 6% 左右，财政赤字率同为 GDP 的 6%，企业盈利极其强劲，甚至到了需要担心“盈利透支（Overearning）”的程度。更重要的是，整个经济正在发生一场财富从劳动力端向资本端（Labor to capital）的大转移，而标普500指数的成分股恰好以企业级 B2B、资本品和批发型经济为主，最大程度捕获了这一时代红利。在这样的牛市环境中，即便偶尔发生 3% 到 7% 的跌幅，也往往只是一些随机杂音。 - 宏观韧性支撑：名义经济增速约 6%、财政赤字占 GDP 约 6%、企业盈利高度坚挺。 - 权重股分化：并非“科技七巨头”共同拉动，大厂自由现金流受巨额资本开支抑制，OpenAI 收入数据不及预期。 - 指数成分红利：标普500指数重度偏向 B2B 与资本利得型企业，直接受益于劳动力收益向资本收益的倾斜。 --- ### [39:07](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2347s) “完美轮动”与日内交易的量化机械性 几位主持人进一步剖析了市场参与者对经济的认知错位。普通大众判断经济状况时，直觉上会联想到迪士尼（Disney）、塔吉特（Target）或酒店连锁等消费端企业，但从大盘盈利和市值的角度看，类似美光（Micron）这样的半导体公司体量远超迪士尼，它们才是驱动指数的核心动力。Michael Santoli 回顾道，半导体板块占到标普500指数近 18%，四大超大规模云厂商（Hyperscalers）又占 16%；无论投资者按盈利修正、动量还是成长逻辑去选股，最终买到的都是同一批半导体股票。 随着资金在不同板块间腾挪，市场呈现出一种被 Santoli 称为“完美轮动（Immaculate Rotation）”的奇景：某一天半导体跌 2%，苹果便恰好涨 1.5%，医疗健康板块同时起飞，指数整体岿然不动。这种高度机械化的行情并非由关注新闻的人类交易员驱动，而是由 Jane Street、Susquehanna、Citadel 等量化做市商与多策略对冲基金主导。这些机构采用一篮子交易（Basket trading）和因子中性策略，日内对头条新闻毫无兴趣，主要在不同因子之间相互对冲，以求在不离开市场的前提下保持仓位风险中性。 - 行业集中度：半导体板块占标普500权重约 18%，四大云巨头占 16%。 - 认知错位：大众消费股（迪士尼、Target）在指数实际盈利权重上远低于美光等半导体硬科技。 - 算法机制：做市商与高频量化模型在因子之间相互对冲，导致板块轮动极为程式化。 --- ### [41:48](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2508s) 负贝塔资产、做市商逻辑与“程序化交易”的历史宿醉 Bespoke 的数据显示，市场经历了自 2001 年以来最长的一段没有出现“非赢即输日（All-or-nothing day，即全市场几乎所有股票单日全涨或全跌）”的时期，自 2025 年 12 月 31 日以来从未出现过大面积同向涨跌。造成这种极致离散度的原因除了极度集中的市值结构，还在于投资者对“负贝塔（Negative beta）”资产的追逐。以往公用事业股是典型的避险防御资产，但在 AI 浪潮下公用事业已变成电力概念的 AI 交易；如今由于传统债券无法像以往那样提供分散化保护，能源股在很大程度上接替了负贝塔对冲工具的角色。 Michael Santoli 特别澄清，将市场行为归结于“机器驱动”并不等于股市脱离了基本面。高频量化做市商的胜率通常仅有 51% 左右，靠海量微利交易生存；一旦发生不可预测的宏观系统性冲击（如同疫情暴发），程序的第一反应并非疯狂砸盘，而是直接关机退出流动性提供。Santoli 结合自己 1992 年入行的经历回忆道，彼时市场依然笼罩在 1987 年“黑色星期一”股灾、1990 年房地产与储贷危机（S&L crisis）的阴影中。当年股灾后官方归咎于“程序化交易（Program trading）”与投资组合保险（Portfolio insurance），纽交所甚至因此立规，每周四盘后都必须公布一份程序化交易活动报告——这与如今大众把一切市场异动怪罪给算法和高频交易的心理如出一辙。 - 极度分化的广度：自 2025 年底至该录制节点，市场创下 2001 年以来最长未出现“全涨或全跌日”的连续纪录。 - 资产角色重构：公用事业股被吸纳进 AI 用电主线，能源股则逐渐演化为抗波动的负贝塔配置工具。 - 历史对照：从 1987 年股灾对“程序化交易”的恐慌与监管周报，到 15 年前对高频交易（HFT）的迷思，市场对量化机器的恐惧与审视始终在周期性重演。 ### [45:03](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2703s) 程序化交易的演变与资金流向数据的意义 Michael Santoli 回顾起早年在电讯社（the wires）工作时，每周都会查看纽约证券交易所（NYSE）关于各家机构程序化交易（program trading）的执行量报告，比如指数套利等策略。当时人们之所以紧盯这些数据，是因为大家认为“程序化交易曾经在1987年股灾中充当了摇动狗身的那条尾巴”，因此必须监控它以防重演。到了 2000 年代中期，一家大型投行的股票资本市场主管向 Santoli 透露，所谓的“程序化交易”其实定义极其主观、毫无科学性——早期交易所监察员如果在灰色地带，会指示“别把它报成程序化交易”，以免外界觉得市场全被机器人掌控；到了 2000 年代初风向一变，纽交所为了标榜高科技与时俱进，反而鼓励“都往程序化交易里塞”。 三人由此探讨起市场上各类“资金流向数据”（Fund Flows）的真实价值。Josh Brown 与 Michael Batnick 吐槽道，散户或机构常常看美林等大行发布的每周报告，例如“散户过去五周内买入最多科技股”这类标题，其实更多是提供“谈资”（content），实际操作中很难直接作为反向或顺向指标。不过，Santoli 指出，像 Strategas 的 Todd Sohn 建立的 ETF 行业资金流向区间分析，确实能抓出极端情绪点来指导交易。现在市场过度痴迷于追踪散户的净买入与净卖出；Citadel 的资金流向专家 Scott Rubner（曾就职于高盛）指出，散户极少出现净卖出，但每当他们净卖出时（如 3 月最后一周或 7 月最后一周），往往恰巧就是市场见底的时刻。然而 Josh 指出，这不过是恐慌指数（VIX）飙升、RSI 跌至 30 或超卖指标触底的另一种表述方式罢了，本质都是同一回事。 ### [47:40](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2860s) 散户是“聪明钱”吗？401(k) 定投与“永不割肉”的心理 针对近期金融媒体普遍将散户捧为“真正的聪明钱”（因为散户总是执着于逢低买入），三人展开了辩论。Santoli 反驳道，散户逢低买入往往只能维持在行情初跌期，一旦跌势延续数周、恐慌加剧，他们最终还是会离场。但 Josh 提出了一个关键的例外——401(k) 退休账户投资者。Josh 认为 401(k) 定投者才是全美最顶级的投资者，胜过任何对冲基金：在 2020 年疫情暴跌期间，先锋领航（Vanguard）的数据显示这些散户投资者完全“毫无反应”，在下跌过程中机械式地每一笔都坚定买入。 Batnick 提到了 John Authers 分享的一张图表：将半导体 ETF（如 DRAM 相关标的）的资金规模与费城半导体指数（SOXX）对比，尽管在近期平仓风暴中半导体板块遭到重创，散户却完全不为所动，持续逆势加仓。Santoli 总结了现代散户投资者的两大特质： 1. **不愿坐实亏损（Don't crystallize losses）**：散户持有的股票下跌时通常不会轻易割肉，总觉得“它早晚会涨回来”，因此他们的下一手操作几乎永远是“加仓买入”，除非遭遇追加保证金（margin call）。 2. **与多策略对冲基金的博弈**：像 Citadel、Millennium 这类多策略基金有着极其严苛的风控红线，只要头寸亏损达到 5%，无论基本面如何都必须强行平仓砍仓；而此时散户在另一侧开心接盘：“感谢你们便宜卖给我”。 ```mermaid flowchart LR accTitle: 对冲基金砍仓与散户逢低接盘机制 accDescr: 展示对冲基金触发止损卖出与散户逆向买入的资金流向互动。 subgraph HedgeFunds["对冲基金 (Citadel / Millennium)"] A["头寸亏损达到 5%"] --> B["严苛风控被触发: 强制止损卖出"] end subgraph RetailFlow["散户投资者 / 401(k) 账户"] C["坚信跌下去早晚会涨回来"] --> D["逢低加仓买入 (Buy the Dip)"] end B -->|"抛压释放 / 筹码转移"| D ``` ### [49:27](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2967s) 末日期权、备兑期权 ETF 与“私人社保”的代际转移 在谈及零日到期期权（0DTE）时，Santoli 认为这更多是日内均值回归的噪音——散户早盘买入看涨期权，华尔街做市商卖给他们，日内时间价值快速衰减（theta decay），从而把整天的行情锁定在一定震荡区间内。 更值得注意的是期权类收益型 ETF（Options-income ETFs）的爆发式增长。Santoli 提出了一个独到见解：**期权收益基金本质上就像一种“私人社会保障机制”（private social security）**。其底层的资金流动呈现出一种代际财富转移： - **年轻交易者与散户**：热衷于支付高昂的期权费（juice call premium）去博取标的资产的暴涨杠杆； - **退休与高收益投资者**：持有备兑看涨期权（Covered Call）ETF（如 NEOS、Innovator 以及高盛收购的期权 ETF），通过不断向年轻投机客卖出看涨期权来赚取丰厚溢价，作为退休现金流。 Batnick 回忆起 2018 或 2019 年与 Innovator ETFs 创始人 Bruce Bond 的访谈，当时他就预感定义型结果 ETF（Buffer / Defined-Outcome ETFs）必将成为超级赛道。传统的 60/40 股债组合在 2022 年股债双杀时无法提供足够的保护，而这类期权缓冲型产品允许散户精准定制风险偏好（例如“锁定最大回撤为 -10%、封顶收益为 +12%”或“+5% 到 +7%”），就像年金一样，满足了大众对投资确定性的心理渴望。 ### [51:48](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3108s) 估值顶部已现？自由现金流收缩与“贝索斯门徒”的资本开支大潮 话题转向当前牛市的估值问题。Santoli 在讨论文档中提出一个警示观点：“**谨慎的做法是假定当前估值（市盈率 PE）的顶部已经出现，如果未来估值还能继续扩张，就把它当成意外之喜**”。他解释说，标普 500 指数的远期市盈率在去年 10 月达到了 23 倍（而疫情期间的 23 倍是在极度压抑的盈利基数上产生的）。尽管指数在此后继续上涨，但市盈率却有所收缩，这是因为企业盈利增长的速度快于股价涨幅。 压制估值进一步扩张的核心瓶颈在于**自由现金流（Free Cash Flow）的恶化与巨额资本开支（Capex）**： - 目前标普 500 指数的远期市价与自由现金流比率（Forward P/FCF）高达 30 倍； - 当前驱动科技巨头增长的模式，已经从过去极其轻资产的“自由现金流机器”，转变为极其重资产、极度消耗资本的 AI 基础设施竞赛。 不过 Josh 和 Batnick 强调，这种自由现金流的收缩是企业“自愿且主动为之的”，完全在计划之内。Santoli 指出，当谷歌（Alphabet）等巨头在财报电话会上向华尔街安抚“别急，这依然处于极早期阶段（it's still early）”时，投资者其实已经开始对这种说辞感到疲惫并渴望看到变现终点。Josh 深刻地指出，掌管如今这批科技巨头的 CEO 和高管们，在斯坦福或商学院求学时，都是拜读杰夫·贝索斯（Jeff Bezos）的亚马逊致股东信与 S-1 招股书长大的；贝索斯那种“宁可牺牲当前利润、甚至不要自由现金流，也要将每一分钱疯狂再投资于长期未来”的哲学，早已深深烙印在他们的基因中，他们绝非浅薄的模仿者，而是在身体力行地重现亚马逊当年的扩张战略。 ### [53:27](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3207s) AI 资本开支与自由现金流的 ROI 疑问 讨论从科技巨头激进的资本开支（Capex）切入。华尔街并非看不懂底层逻辑，市场之所以能够忍受巨额支出，是因为投资者意识到这些大公司并非在盲目跟风，而是在响应真实的客户需求信号。然而，这种繁荣背后依然潜藏着隐忧——在正常的资本主义市场经济中，所有科技巨头在同一时间将全部自由现金流押注在同一个方向、建造同一种基础设施，且最终所有人都能获得超高投资回报率（ROI）的情况极其罕见。市场分析人士（如相关研报指出的逻辑）认为，虽然这项颠覆性技术毋庸置疑，巨头们也不是傻子，但最终的投资回报率很可能无法达到预期。 谈及公司如何创造价值，长期观察市场会让人对那些所谓的“铁律”产生怀疑。过去人们总认为股票回购是在人为推高大盘，但即便如今市场上有着上万亿美元的回购规模，相对于整体总市值而言其比例并未激增，且进行大规模回购的个股也并未因此全面跑赢。相反，现代经济在很大程度上是由基于股权的员工激励（Stock-based compensation, SBC）驱动的，巨头们的大量回购实质上只是在吸收并消化增发给员工的股权激励份额。 --- ### [54:52](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3292s) 看多与看空的较量：谁更不真诚？ Josh Brown 抛出了一个直击要害的问题：“总体来看，多头和空头究竟谁更不真诚（disingenuous）？”嘉宾们一致认为空头在这方面可谓“遥遥领先”。空头在利用信息时往往极其投机，其典型特征是“不断变换论据，却永远维持看空立场”。相比之下，多头通常会坦率承认下行风险的存在，表现出对风险的清醒认知；而空头则几乎从不承认潜在的上行可能，只会不断改变叙事、转移阵地。 ```mermaid flowchart TD accTitle: 空头论调转移路径 accDescr: 展示空头如何在市场环境发生变化时不断变换看空借口 subgraph S1["阶段一：高度集中"] A["市场仅由七巨头（Mag 7）领涨"] --> B["警告集中度过高是崩溃前兆<br/>类比50年代末与1960年暴跌"] end subgraph S2["阶段二：行情扩散"] B --> C["市场广度展开，部分巨头回调20%<br/>标普500指数依然创下历史新高"] end subgraph S3["阶段三：转移靶子"] C --> D["绝口不承认原有担忧已被化解"] --> E["迅速切换新叙事<br/>例如转向抨击巨额国家债务"] end ``` 这种“移动球门柱”的行为在近两年的行情中体现得淋漓尽致： - 2024 年初，空头大肆抨击市场过度集中在“科技七巨头”（Magnificent Seven）身上，将其类比为 1950 年代末或 1960 年代市场见顶前的极度集中风险。 - 随后市场广度（Breadth）显著扩散，即便部分七巨头成员自高点回撤达 20%，标普 500 指数依然刷新历史高点。 - 曾坚称集中度过高会导致崩溃的空头们，没有一个人站出来承认“该风险已被市场自身化解”，而是立刻将火力转移到诸如美国联邦政府债务等全新议题上。 --- ### [57:03](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3423s) 攀爬担忧之墙与市场回调周期 从统计概率来看，股市在历史上 70% 的年份是上涨的，55% 的交易日也在走高，执意长期做空无异于对抗整个资本市场的底层势能。然而在情绪层面上，市场参与者往往表现出微妙的心理分歧。在经历 7 月份的抛售与迅速修复后，媒体和受访嘉宾开始反复念叨“盈利是行情的北极星”、“盈利是牛市的生命线”，洋溢着一种“熬过去便证明自己站在真理一边”的道德自豪感。 Michael Santoli 借用美剧《广告狂人》（*Mad Men*）中费伊·米勒医生（Dr. Fay Miller）对唐·德雷珀（Don Draper）的经典台词来形容这种心境：“你只喜欢事物的开端（You only like the beginnings of things）。”当行情在重重挑战与质疑中展开时最令人兴奋，而当所有人都在为无可挑剔的亮眼财报欢呼时，上涨反而变得缺乏悬念。虽然这并不意味着牛市就此结束——市场仍旧在“攀爬担忧之墙”（Wall of worry），但如果一年之后大型科技企业仍然维持着负自由现金流、继续向市场画饼“回报终将到来”，届时投资者的耐心恐怕将受到严峻考验。健康的市场往往需要定期的惊吓与缓解循环（Scare and relief cycle）来出清杠杆与浮筹。 --- ### [59:34](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3574s) 市场广度迷思与“补涨而非补跌” 针对“市场广度扩大才代表健康”的传统观念，对话给出了反思。迈克尔·莫布森（Michael Mauboussin）在研究中通过数据证明，真正的牛市往往伴随着权重的不断集中，市场集中度高并不天然等同于危险，“追求广度要小心求仁得仁”。不过，在权重股调整期间，其他板块能够接棒走强、吸收回调压力，确实构成了良性的轮动过渡。 过去 15 年间，空头最大的认知盲区在于固执地假定“负背离必定以补跌（Catch-down）告终”： - 无论是小盘股长期跑输，还是价值股陷入 20% 的大幅回撤而成长股迭创新高，悲观者总预期强势板块最终会崩塌并拖垮整个大盘。 - 历史现实恰恰相反，行情通常是以弱势板块的“向上补涨（Catch-up）”来消除分歧。 - 尽管标普 500 成分股中站上 200 日均线的比例突破 70% 并不代表绝对的安全牌，历史上一旦达到该水平后也曾出现过 15% 至 20% 的回调，但市场的弹性屡屡粉碎了全面的崩盘论。 --- ### [01:01:17](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3677s) 早期震波还是虚惊一场？从 LTCM 到当下 主持人和嘉宾讨论了近期的市场扰动（如去杠杆风波）是否构成了某种深层危机的“先兆震波”（Tremor），就像 1998 年长期资本管理公司（LTCM）危机或 2007 年 8 月的量化震荡（Quant Quake）一样，预示着一到两年后系统性泡沫的破裂。 Santoli 认为不能简单地画等号： - 当年长期资本管理公司的倒闭并不能与 2000 年 3 月互联网泡沫的最终破裂直接连成因果线。 - LTCM 危机带来的真正影响是引发了全球金融条件的骤然收紧与经济衰退恐慌，迫使美联储降息救市；美联储随后向市场注入过量流动性，推高了 1999 年的经济过热与投机狂热，间接催生了后来的巨大泡沫。 - 因此，短期去杠杆造成的冲击本身并不必然是矿井里的金丝雀，不能将其直接套用为经济基本面全面溃败的推导依据。 ### [01:02:07](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3727s) 规则的失效与“身经百战”的企业高管 过去主导市场的许多经验法则正逐渐被打破。Michael Santoli 指出，以往投资者奉行“市场长期估值为15倍市盈率”等教条，那是因为当时的经济深陷于传统制造业周期，几乎每三年就会爆发一次衰退，利润率也总是遵循均值回归。然而，如今的宏观环境展现出前所未有的韧性，甚至有人开玩笑称节目应该直接命名为“利润永远不会下降——Michael Santoli 著”。市场对估值标准的讨论也从未停歇，过去大家严格锚定 GAAP（通用会计准则）盈利，而现在普遍接纳并以营业利润（Operating Earnings）为核心基准，这在老派空头看来不可思议。 Josh Brown 提出了一个极具说服力的观察：当前掌管标普500指数企业的首席执行官（CEO）和首席财务官（CFO），或许是商业史上最“身经百战”的一群管理精英。回看过去5到10年的考验，他们经历了常人难以想象的动荡： - **特朗普第一任期**：直接在 Twitter（现 X）上被美国总统点名怒骂与威胁。 - **贸易摩擦与供应链冲击**：2018年的关税壁垒、大豆与制造业混乱。 - **新冠疫情与社会事件**：全球疫情停摆、远程办公变革、国会山事件（1月6日）。 - **文化战争旋涡**：零售商因彩虹骄傲月陈列遭遇抵制、迪士尼陷入主题乐园的社会政治纷争。 - **宏观风暴**：新一轮关税威胁、地缘政治紧张（如伊朗战争风险）、创纪录的通胀海啸以及劳动力市场重构。 即使经历了这连番轰炸，当前标普500指数的整体净利润率依然维持在15%左右，季度营收同比增长达4%。Santoli 补充道，这种超强韧性很大程度上源于指数的成分构成——权重最大的巨头们拥有无可比拟的吸金能力，而传统企业的表现其实分化严重（例如星巴克困境重重，联合包裹（UPS）的盈利回落到三年前水平，耐克（Nike）甚至停滞在15年前的水准，赛默飞世尔（Thermo Fisher）的利润近几年也基本持平）。历史能与之勉强媲美的，或许只有1968至1972年恶性通胀、石油危机、尼克松时代与越战交织的动荡期。 ```mermaid flowchart TD accTitle: 过去十年企业高管面临的多重外部冲击 accDescr: 展示标普500指数管理层在政治、贸易、疫情、文化战争与宏观金融层面的连续考验 subgraph MacroShock["政治与贸易摩擦"] A["总统社交媒体公开施压"] B["2018年中美关税与大豆贸易战"] end subgraph CrisisShock["危机与社会撕裂"] C["2020年新冠疫情与WFH普及"] D["零售与娱乐业卷入文化战争争议"] end subgraph EconShock["通胀与地缘动荡"] E["四十年未见的恶性通胀与加息"] F["地缘冲突与新关税风险"] end MacroShock --> G["超强韧性的标普500企业"] CrisisShock --> G EconShock --> G G --> H["当前整体净利润率维持在15%"] ``` --- ### [01:05:18](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3918s) 拜伦·韦恩的启示：股息率倒挂打破了老前辈的脑子 谈及历史长河中规则的重塑，Santoli 回忆起华尔街传奇策略师拜伦·韦恩（Byron Wien，曾任摩根士丹利及黑石集团资深策略师）分享的一段经典往事。韦恩在1958年前后从商学院毕业进入资管机构，恰逢美股历史上一个划时代的拐点：美股股息率历史上首次持续跌破了美国国债收益率。 在1958年之前，华尔街有一条奉为圭臬的铁律：“一旦美股股息率低于美债收益率，就意味着美股严重高估，到了必须卖出的大顶”。韦恩亲眼目睹这一指标的失效如何“彻底击碎了老一辈基金经理的心智”（broke their brains）。老派经理人无法适应这种结构性巨变，盲目死守旧规则抛空股票，结果眼睁睁看着市场翻了数倍甚至更多。他们因长期看空做错而丢失客户，办公室从气派的转角大办公室（Corner Office）一步步搬迁到幽暗的内侧走廊隔间，最后只能靠大学室友拉点赞助资金勉强维生。 这个震撼的经历塑造了韦恩日后的投资哲学，促使他创立了每年闻名遐迩的“十大意外预测”（10 Surprises）。他深知盲从旧经验会导致盲区，必须时刻主动测试极端场景。当被问及若韦恩和巴顿·比格斯（Barton Biggs）活在今天会如何看待当下市场时，Santoli 认为他们一方面会拥抱并庆祝 AI 所带来的长期经济潜力与社会效益（如大幅扩充生产力容量、加速可再生能源建设），另一方面也会对局部的盲目狂热保持警惕，比如难以认同三倍杠杆的单一股票 ETF 等极度投机工具。 --- ### [01:07:38](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4058s) 《金钱游戏》的宿命论与老派动量股的复活 主持人聊到了“亚当·斯密”（笔名，真名为乔治·J·W·古德曼 / George J. W. Goodman）在1968年出版的经典著作《金钱游戏》（*The Money Game*）。书中生动记录了1960年代末大牛市中年轻一代交易员的狂热心态。Santoli 念了一段关于“计算机租赁股票”的精彩选段： > “计算机租赁股票，长官！”他说得就像一位正在接受学长盘问的军校学员。“对计算机的需求实际上是无限的，”‘小子比利’说，“租赁被证明是卖出它们的唯一方式，而计算机公司自己没有足够的资本。因此，今年的收益将增长100%，明年再翻倍，后年继续翻一番。我们目前才刚刚触及皮毛，上涨才刚刚开始！” 这番话与今天市场上鼓吹 AI 与基础设施算力需求的言论如出一辙。但 Santoli 提出了自己的一项长期原则：“一切事物最终都会归于平淡”（Everything ends in a boring place）。无论当前一家企业有多么令人心潮澎湃，只要它顺利发展壮大，最终都难免沦为某种公用事业型、成熟型或基础运作构件式的低速增长企业。 - **典型案例**：eBay 曾是估值冲天的超级成长股，如今是成熟平庸的存量平台；发行稳定币的 Circle 如果上市并宣称自己颠覆金融，本质上也是在吃国债利差做托管，而纽约梅隆银行（BNY Mellon）管理着数万亿美元资产，市盈率只有12倍。 Josh Brown 认为埃隆·马斯克（Elon Musk）是个罕见的例外，因为马斯克敢于亲手残食自己的业务来持续自我革命——比如直接放弃 Model S 和 Model X 的重心，转头押注具身机器人。然而对大部分公司而言，这种周期性宿命无法逃脱。 令 Josh 深感有趣的是，在近期的行情中，许多当年因互联网泡沫破裂而沉寂的老派巨头竟再度“重拾当年的动量股光环”： - **经典动量股的重生**：如希娜（Ciena）、戴尔（Dell）和思科（Cisco），这些世纪之交备受追捧的通信与硬件明星，如今在 AI 浪潮的驱动下再度走强。 - Josh 甚至开玩笑说自己曾想去搜寻当年著名的光纤网络股 MFNX（Metromedia Fiber Network），如果它还在世，自己肯定也会买入，引发了一阵关于投机周期的欢笑与感慨。 ### [01:10:29](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4229s) 股票不知道你拥有它：克服沉没成本与单相思心理 节目中重温了 1968 年投资经典著作《金钱游戏》（*The Money Game*）中的一段精妙名言，这段话尤其值得个人投资者在市场动量受挫时反复铭记。书中写道：从现实意义来看，股票不过是锁在银行保险库里的一张纸，你大概率永远也不会亲眼见到它；它或许有内在价值，或许没有，但它在任何特定交易日的价值，完全取决于当天买家与卖家的汇聚博弈。最关键的事实极为朴素——“股票根本不知道你拥有它”（The stock doesn't know you own it）。无论你对某只股票、一篮子持仓或背后代表的金钱寄托了多么美妙憧憬或恐惧厌恶，这一切全都是单向的情感。你可以深陷爱河，但那张纸绝不会爱你；而在市场中，这种“单相思”最终往往会异化为受虐倾向、自恋妄想，甚至演变成真金白银的惨痛亏损与反噬的仇恨。 嘉宾们感叹这段话的精炼与透彻，并指出其最直接的推论就是“买入成本锚定心理”：股票完全不在乎你的持仓买入价是多少，坚信股价必然会“回归”到自己成本线的想法纯属一厢情愿。虽然理智上人人都懂，但克服这种心理极其违背人性，许多人依然会陷入这种思维惯性。随后大家以特斯拉（Tesla）为例：回顾特斯拉相对于标普 500 指数的全部历史表现，其累计超额收益高达惊人的 3600% 左右，然而这所有超额收益的每一个基点，竟然全部是在 2020 年这短短一个日历年内实现的（当年股价翻了 10 倍）。尽管此后特斯拉基本守住了这部分涨幅、并未彻底崩溃，但这也直观展现了市场狂热时“天时地利人和”完美契合所释放出的非理性爆发力，以及投资者对特定股票近乎盲目的狂热信仰。 ### [01:12:08](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4328s) “是我太蠢，还是他们太疯？”：疯狂的 AI 估值与并购热潮 在本轮牛市中，市场上频繁出现的夸张估值让投资人几乎每天都在心里发问：“究竟是我太蠢，还是他们太疯？”（Am I dumb or are they dumb?）。以 AI 领域的聚合平台 OpenRouter 为例，它的角色就像是 AI 时代的 Google 搜索入口——过去用户打开 Google 寻找海量网页链接，如今用户有 AI 项目需求时打开 OpenRouter，作为一个“AI 线束”（AI harness），用户可以便捷地从数百个大语言模型（LLM）中自由挑选或组合调用，免去了单独对接 Anthropic、Claude 等各个独立模型的繁琐。 然而令人咋舌的是随之而来的并购传闻：据外媒报道，支付巨头 Stripe 正洽谈收购 OpenRouter。这家公司刚刚公布其年收入增长两倍达到了区区 1300 万美元，然而 Stripe 给出的收购意向估值竟高达 70 亿至 75 亿美元。更夸张的是，就在三个月前的 5 月份，该公司的估值还仅为 13 亿美元。换言之，短短三个月内，在营收只有 1300 万美元规模的背景下，身价直接暴涨数倍跨入 70 多亿美元门槛。 面对这种看似荒诞的天价交易，主持人们也承认历史经常充满颠覆：当年扎克伯格以 110 亿美元天价收购 WhatsApp、Google 早期买下 YouTube、Facebook 以 10 亿美元收购仅有 11 名员工的 Instagram，以及苹果斥资 30 亿美元收购 Beats 耳机时，市场无一不惊呼“疯了”，但日后回头看往往证明是极具战略价值的一笔投资。买家之所以愿意付出如此离谱的溢价，根本原因在于对错失战略要塞的极度恐慌与焦虑，急于拿到通往下一个技术周期的“万能钥匙”（skeleton key）。OpenRouter 背后汇集的海量 AI Agent 交互数据与调用流量，或许正是买家不惜一切代价想要夺取的战略资源。 - **标的定位**：OpenRouter 充当 AI 模型分发与路由的超级入口，支持集成包括 Anthropic 在内的数百种 LLM。 - **财务数据与估值跳涨**：年收入仅约 1300 万美元，三个月前估值为 13 亿美元，Stripe 洽谈收购估值达 70 亿至 75 亿美元。 - **历史对照案例**： - Meta/Facebook 以 10 亿美元收购 11 人团队的 Instagram； - Meta 以逾百亿美元收购 WhatsApp； - 苹果斥资 30 亿美元收购 Beats。 ### [01:15:11](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4511s) 满嘴芯片工艺的交易员，与市场见顶的狂热信号 当前市场上还出现了一个极具讽刺意味的怪相：无论是短线交易员还是华尔街宏观配资经理，人人都开始假装自己是半导体与前沿工程领域的绝对专家。大家甚至连晶圆（wafer）掉在地上都会以为是华夫饼铁模，如今却能毫无障碍地把芯片良率（chip yields）、先进封装、存储制造工艺以及单 token 推理成本挂在嘴边。哪怕是行业顶级的分析博客（如 Ben Thompson 与相关播客），普通投资者听了一个多小时也往往一头雾水，但市场上所有人都不得不被迫硬塞进这一套复杂的技术行话，因为当前最热门、波动最大的股票全部都在围绕这些概念定价。 这种技术术语的泛滥甚至蔓延到了电力与能源领域。在一次小型晚餐聚会上，有投资者能头头是道地详尽分析将淘汰的喷气式飞机引擎改装为燃气轮发电机以供应 AI 数据中心电力的每一个技术细节——而就在两年前，这位投资者还在苦苦拆解 Lululemon 的同店销售额数据。如今市场上甚至开始蜂拥发行专门跟踪某一家特定 AI 巨头生态系统的定制化一篮子 ETF。这种将行业拆解到极致微观零部件的做法，像极了当年智能手机狂潮时拆解 iPhone 供应链概念股，或是自动驾驶热潮中疯狂炒作激光雷达（LiDAR）概念的时期。 这种群体性的技术狂热与叙事泛滥，往往是行情进入过热乃至阶段性见顶（toppy behavior）的经典特征，这类狂欢通常只需经历一次像样的市场回调便会迅速烟消云散。这种行业预判的脆弱性在老牌科技硬件公司上也体现得淋漓尽致：美光（Micron）与西部数据（Western Digital）等传统存储巨头如今借着 AI 东风迎来第二春，然而就在一年半前，西部数据因市场无人问津、股东极力施压而分拆了闪迪（SanDisk）业务，谁知闪迪随后暴涨数倍。这恰恰印证了即使是浸淫行业一生的内部高管，也根本无法精准预知下一轮技术浪潮的方向。 ```mermaid flowchart TD accTitle: AI狂热演进与见顶特征 accDescr: 展示从AI底层硬件技术狂热到市场情绪过热的扩散传导机制 subgraph TechHype["技术狂热与叙事扩散"] A["生成式AI模型爆发"] --> B["算力与基建焦虑"] B --> C["概念下沉: 晶圆良率/存储架构/燃气轮机"] end subgraph MarketBehavior["市场极端行为特征"] C --> D["散户与交易员硬背专业工程术语"] C --> E["机构抢发垂直生态ETF (类似iPhone/LiDAR供应链)"] D --> F["估值脱轨: 极低营收匹配数十亿美元天价并购"] E --> F end subgraph TopSignal["周期特征"] F --> G["典型见顶行为 (Toppy Behavior)"] G --> H["等待下一次市场深度回调完成洗牌"] end ``` ### [01:18:04](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4684s) 节目收尾与《Closing Bell: Overtime》趣事 在节目接近尾声的轻松寒暄中，Josh Brown 邀请 Michael Santoli 向听众介绍他目前在 CNBC 担纲的全新旗舰盘后节目《Closing Bell: Overtime》。Santoli 正式出任该节目的联合主播，与著名财经主持人 Melissa Lee 搭档。 Josh 调侃道，Santoli 多年作为王牌代班主播，几乎主持过 CNBC 整个电视网旗下的所有招牌栏目（包括早间的《Squawk Box》等）。两人还愉快地回忆起早年曾共同搭档主持过一档节目，但播出仅短短六周便宣告停播。两人打趣说，当年节目开播前台里其实就已经通知了停播计划，因此绝不能算“被砍”，而应该像 Netflix 那样高端地称之为精心策划的“限定剧集”（limited series）。两人在欢快的笑谈中结束了当期的正式对谈。 ### [01:18:51](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4731s) 主持《Closing Bell: Overtime》的体验与平衡之道 Josh Brown 询问 Michael Santoli 关于他主持的 CNBC 节目《Closing Bell: Overtime》（收盘钟加时赛）的细节，包括他最喜欢节目的哪一点，以及该节目与电视台其他节目的区别。Santoli 介绍道，该节目在美东时间每个交易日的下午 4:00 到 5:00 播出。最贴切的类比就是体育赛事的“赛后分析”（postgame show）：不仅第一时间复盘当天盘面上究竟发生了什么，还会提炼出真正关键的核心主题，而绝不仅是干瘪的数字涨跌，始终紧扣市场脉搏。 Batnick 指出这个时段极其优越，因为正好能撞上盘后财报发布。Santoli 赞同并打趣道，一年里大概有七个月的时间都处于密集的财报季，内容非常充实。Josh 则开玩笑说难以置信 Scott Wapner 居然把 4 点档让给了 Santoli，自己选了 3 点档（虽然 Wapner 能早一点下班）。谈到财报报道的难点，Santoli 表示最棘手的是在“速度与深度”之间寻找平衡。你不可能跑得比抓取新闻标题的量化算法还要快，但电视直播依然需要具备时效性和紧迫感，迅速拿到第一手财报数据，同时还要通过挑选合适的嘉宾来提供深度解读。该节目从 1 月开播以来，他觉得整体非常有趣且体验极佳。 - 节目播出时间：每个交易日美东时间下午 4:00 至 5:00。 - 核心定位：类似体育比赛的赛后复盘节目（postgame show），提炼核心主题，深挖盘后财报。 - 核心挑战：在机器算法主导的新闻速度与电视深度的解读之间达成平衡。 --- ### [01:20:05](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4805s) CNBC 专栏与全新通讯《Market Memo》 Josh 提到 Santoli 一直在坚持写作，并询问观众可以在哪里读到他的文字。Santoli 解释说，自加入 CNBC 以来，他每周都会在 CNBC Pro 上撰写专栏。目前该内容正在重新打包升级为一份名为《Market Memo》（市场备忘录）的 Newsletter。其主体部分仍是他标志性的市场观察与走势梳理，但整体风格会更加聚焦、更有针对性。 除了严肃的市场分析外，这份通讯还会包含许多零散观察（stray observations），类似于社交媒体上讨论度极高的话题、引人入胜的特色图表，以及流行文化吐槽和 X 世代（Gen X）的牢骚。Josh 开玩笑说这些流行文化和牢骚才是他最期待的部分，因为当天的行情大家早就一清二楚了；Santoli 则笑着附和说自己已经“压抑这些想法很多年了”。Josh 随后调侃节目的命名，建议专栏可以改叫“Santoli 说了什么”（Sam told me / Santoli 谐音梗），Santoli 笑着回忆说小时候别人给他起的外号都没能留存下来，除了五年级有个同学在黑板上把他的姓氏拼错，让他顶着“沙马桶”（sand toilet）的外号过了一小阵子，幸好没变成终身昵称。 - 专栏产品：原 CNBC Pro 每周专栏重新打包升级为 Newsletter，定名为《Mike's Market Memo》（或《Mike Santoli's Market Memo》）。 - 内容构成：市场走势核心梳理、特色图表与本周爆发讨论的话题、流行文化琐谈与 X 世代观点。 --- ### [01:21:20](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4880s) 纽约长岛的南北岸大辩论 访谈临近尾声，Josh 抛出了一个长岛（Long Island）本地人的经典争论：北岸（North Shore）与南岸（South Shore）到底哪边更好。Santoli 透露自己最初来自北岸的华盛顿港（Port Washington），整个大家族长期定居在那里。两人逐一对比了两岸的生活方式与风貌特点： 南岸坐拥辽阔的大洋和白沙滩，海景与海滩体验明显胜过长岛海峡（Long Island Sound）遍布礁石的北岸水域——Josh 吐槽在北岸玩摩托艇（jet ski）容易撞到岩石；但北岸在人文自然风貌上显然更为优越，拥有更多优质餐厅、稍高一筹的学区，以及树林、丘陵和类似《了不起的盖茨比》（The Great Gatsby）小说中描绘的豪宅风情。最终大家一致认为，这纯粹取决于个人偏好。Josh 戏称在“长岛中部”骑自行车两头都能跑的人才是赢家，而 Santoli 则笑称自己现在已经搬到了“另一座岛”（曼哈顿岛）居住。 ```mermaid flowchart TD accTitle: 长岛南北岸特征对比 accDescr: 对比纽约长岛北岸与南岸在自然环境、生活配套与海滩资源等方面的核心差异。 subgraph NorthShore["北岸 (North Shore)"] N1["自然风貌：树林、丘陵、盖茨比式风情"] N2["生活教育：优质餐厅集中、学区略胜一筹"] N3["海岸特征：长岛海峡、礁石较多"] end subgraph SouthShore["南岸 (South Shore)"] S1["自然风貌：地势平缓"] S2["海岸特征：大西洋海景、优质白沙滩"] S3["水上活动：更适合水上运动与出海"] end ``` --- ### [01:22:46](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4966s) 结语与致谢 在节目尾声，Josh Brown 和 Michael Batnick 对 Michael Santoli 本期的做客表达了由衷的感谢，盛赞他的分享极其精彩、不负众望。Josh 呼吁所有观众关注 Santoli 的工作： - 美东时间每周一至周五下午 4:00 收看 CNBC 播出的《Closing Bell: Overtime》； - 前往 CNBC.com 订阅并阅读《Mike's Market Memo》。 Santoli 对主持人的邀请表示感谢，节目在现场热烈的掌声与两人的互相打趣中圆满结束。 ## Notable quotes > [13:53](https://www.youtube.com/watch?v=5GGUoaayVqE&t=833s) 你是我唯一看到在认真看报纸的人，你似乎真正懂行。我只是个拉皮条的无证电话推销员，我到底该怎么学习股票？ — Josh Brown > [23:04](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1384s) 既然大众对预测有着无法遏制的需求，市场上就必然会源源不断地供给各类预测。 — Michael Santoli > [26:43](https://www.youtube.com/watch?v=5GGUoaayVqE&t=1603s) 这比体育赌博强多了。如果我赌球输了，那就是彻底归零；但如果我买进 Hertz，股价暴跌 30%，我手里好歹还剩下 70% 的钱。 — Michael Santoli > [49:27](https://www.youtube.com/watch?v=5GGUoaayVqE&t=2967s) 期权收益基金本质上就像一种“私人社会保障机制”。 — Michael Santoli > [51:48](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3108s) 谨慎的做法是假定当前估值的顶部已经出现，如果未来估值还能继续扩张，就把它当成意外之喜。 — Michael Santoli > [57:03](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3423s) 你只喜欢事物的开端。 — Michael Santoli > [01:05:18](https://www.youtube.com/watch?v=5GGUoaayVqE&t=3918s) 一旦美股股息率低于美债收益率，就意味着美股严重高估，到了必须卖出的大顶。 — Michael Santoli > [01:07:38](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4058s) 对计算机的需求实际上是无限的，租赁被证明是卖出它们的唯一方式，而计算机公司自己没有足够的资本。因此，今年的收益将增长100%，明年再翻倍，后年继续翻一番。我们目前才刚刚触及皮毛，上涨才刚刚开始！ — Michael Santoli > [01:07:38](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4058s) 一切事物最终都会归于平淡。 — Michael Santoli > [01:10:29](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4229s) 股票根本不知道你拥有它。 — Michael Santoli > [01:12:08](https://www.youtube.com/watch?v=5GGUoaayVqE&t=4328s) 究竟是我太蠢，还是他们太疯？ — Josh Brown ## Mentioned Josh Brown, Michael Batnick, Michael Santoli, CNBC, Closing Bell: Overtime, Barron's, The Wall Street Journal, Alan Abelson, Gene Marcial, The Money Game, Adam Smith (George Goodman), Donald Trump, Ross Perot, Hertz, Robinhood, Interactive Brokers, Jane Street, Susquehanna, Citadel, Millennium, Scott Rubner, Todd Sohn, Innovator ETFs, Bruce Bond, Jeff Bezos, Amazon, OpenAI, Nvidia, Meta, Microsoft, Google (Alphabet), Apple, Micron, Western Digital, SanDisk, Ciena, Dell, Cisco, OpenRouter, Stripe, Anthropic, Claude, Byron Wien, Barton Biggs, Michael Mauboussin, Long-Term Capital Management (LTCM), DBMF, Melissa Lee, Scott Wapner ## Video description On episode 256 of The Compound and Friends, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Downtown Josh Brown⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and Michael Batnick are joined by⁠⁠ Michael Santoli ⁠⁠ to discuss: the surprising strength of the stock market, what’s keeping the bull market alive, interest rates and the growing U.S. debt load, why corporate earnings remain so powerful, and whether today’s valuations can keep climbing. They also get into AI spending and the return on massive tech capex, market breadth and rotation, the rise of retail investors, options-income ETFs, why bears keep moving the goalposts, and what decades of market history can teach investors about adapting when the old rules stop working. This episode is sponsored by DBMF. To learn more about the world’s largest managed futures ETF visit ⁠https://www.dbmf.com/TCF⁠ ►00:00 - Cold Open ►12:11 - Intro ►13:53 - How Josh Learned The Market ►21:12 - Market Interpretations ►23:04 - The Mystery Broker ►28:56 - Interest Rates ►33:01 - Government Debt ►37:14 - The Strength of The Market ►54:49 - Bulls vs. Bears ►01:07:34 - The Money Game Anecdote ►01:12:08 - “Am I Dumb? Or are They Dumb?” ►01:18:04 - Closing Bell 👕 Check out The Compound shop: https://www.idontshop.com 🎙️Listen to our podcasts: TCAF: https://podcasts.thecompoundnews.com/show/TCAF/ Animal Spirits: https://podcasts.thecompoundnews.com/show/animalspirits/ Ask The Compound: https://podcasts.thecompoundnews.com/show/ATC/ The Compound Newsletter: https://www.thecompoundnews.com/subscribe Linkedin: https://www.linkedin.com/company/the-compound-media/ Instagram: https://instagram.com/thecompoundnews Twitter: https://twitter.com/thecompoundnews Tik Tok: https://www.tiktok.com/@thecompoundnews Investing involves the risk of loss. This podcast is for informational purposes only and should not be or regarded as personalized investment advice or relied upon for investment decisions. Josh Brown and Michael Batnick are employees of Ritholtz Wealth Management and may maintain positions in the securities discussed in this video. All opinions expressed by them are solely their own opinion and do not reflect the opinion of Ritholtz Wealth Management. See our disclosures here: https://ritholtzwealth.com/podcast-youtube-disclosures/ The Compound Media, Incorporated, an affiliate of Ritholtz Wealth Management, receives payment from various entities for advertisements in affiliated podcasts, blogs and emails. Inclusion of such advertisements does not constitute or imply endorsement, sponsorship or recommendation thereof, or any affiliation therewith, by the Content Creator or by Ritholtz Wealth Management or any of its employees. For additional advertisement disclaimers see here https://ritholtzwealth.com/advertising-disclaimers. #thecompound #investing #stockmarket #stocks [Source](https://www.youtube.com/watch?v=5GGUoaayVqE)

[13:53] Josh Brown: 你是我唯一看到在认真看报纸的人，你似乎真正懂行。我只是个拉皮条的无证电话推销员，我到底该怎么学习股票？ [23:04] Michael Santoli: 既然大众对预测有着无法遏制的需求，市场上就必然会源源不断地供给各类预测。 [26:43] Michael Santoli: 这比体育赌博强多了。如果我赌球输了，那就是彻底归零；但如果我买进 Hertz，股价暴跌 30%，我手里好歹还剩下 70% 的钱。 [49:27] Michael Santoli: 期权收益基金本质上就像一种“私人社会保障机制”。 [51:48] Michael Santoli: 谨慎的做法是假定当前估值的顶部已经出现，如果未来估值还能继续扩张，就把它当成意外之喜。 [57:03] Michael Santoli: 你只喜欢事物的开端。 [65:18] Michael Santoli: 一旦美股股息率低于美债收益率，就意味着美股严重高估，到了必须卖出的大顶。 [67:38] Michael Santoli: 对计算机的需求实际上是无限的，租赁被证明是卖出它们的唯一方式，而计算机公司自己没有足够的资本。因此，今年的收益将增长100%，明年再翻倍，后年继续翻一番。我们目前才刚刚触及皮毛，上涨才刚刚开始！ [67:38] Michael Santoli: 一切事物最终都会归于平淡。 [70:29] Michael Santoli: 股票根本不知道你拥有它。 [72:08] Josh Brown: 究竟是我太蠢，还是他们太疯？

[26:28] if I'm wrong on a game, I lose everything (zero) [33:01] Michael Santoli: multiple weather systems all interacting [37:14] immaculate rotations [54:49] Bears will change the argument but maintain the stance almost no matter what... Bulls will always concede that there is a bearish case out there. [54:49] Fay Miller: You only like the beginnings of things. [59:21] catch-down [59:21] catch-up [60:17] Josh Brown: the most battle-tested group of executives collectively ever to run the S&P 500 [67:38] Michael Santoli: Everything ends in a boring place. [67:38] Adam Smith: The stock doesn't know you own it. [72:08] Josh Brown: Am I dumb or are they dumb? [73:31] Michael Batnick: Am I dumb? Are they dumb? I don't know. [73:31] Josh Brown: skeleton key [75:11] Michael Santoli: actively ignorant [78:04] Josh Brown: Santoli Told Me

[0:00] Yankees won a few in a row. [0:02] >> They did. They're squeaking them out. [0:04] >> You go to You go to the stadium a lot. [0:05] >> I don't go a lot. I used to go I used to [0:07] have like a little mini plan. Um I'm so [0:10] old I [0:12] can't warm up to the new stadium. I know [0:14] it's been there like 17 years or [0:16] whatever, but it's like not the place I [0:18] walked into when I was [0:19] >> Oh, you should have come with me to [0:21] Jay-Z. You would have loved it that [0:22] night. Oh, yeah. [0:23] >> Oh my god. [0:24] >> They So, they didn't have Yankee [0:25] security there. They had they had an [0:27] outsourced security and uh [0:30] >> I I think there's like 50,000 tickets [0:32] sold [0:33] >> and then maybe another 50,000 people who [0:35] thought either somehow they'd get in or [0:38] >> I'm on the list. Yeah. [0:39] >> Or if you're right outside the stadium, [0:41] you can listen and just hang out. [0:43] >> And it's in one of the most popular like [0:45] population dense neighborhoods maybe in [0:47] the world. [0:47] >> Yeah. [0:48] >> And it was just like it was impossible. [0:51] And um I went Saturday night, so it [0:54] wasn't quite as bad as the next night, [0:56] Sunday night, where he didn't go on [0:57] stage till 12:30. [0:58] >> Oh my god. [0:59] >> But it took us uh 2 hours to get in. Um [1:02] we planned for that. And then it took us [1:04] 2 hours to leave. No kidding. [1:05] >> Which is the worst. [1:06] >> Yes. [1:07] >> And everybody's like standing [1:08] shoulder-to-shoulder. They just [1:10] >> Yeah. [1:10] >> They had two It's six gates. Yankee [1:12] Stadium. They had two gates open, [1:15] >> which I don't understand. [1:16] >> A nightmare. I know. I think what they [1:18] thought is that they'd be be able to [1:20] better control the flow out of [1:22] >> fewer checkpoints. Yeah. [1:24] >> But it did. [laughter] [1:25] >> So is this this is the thing where they [1:27] like cut it into a dock or something. [1:28] The four nights or whatever it was. [1:30] >> They're going to have to make a movie. [1:31] >> I think they did. Yeah. [1:32] >> They're going to have to because uh it [1:35] was an it was a true like milestone [1:38] event. Oasis is coming out of IMAX their [1:40] their tour. [1:41] >> There you go. Probably the Sphere. Who [1:44] knows? [1:44] >> That'd be sick. Um [1:45] >> I saw them at the Rose Bowl last year [1:47] before future proof. Amazing. Amazing. [1:49] >> You know he's at Yankee Stadium a lot. [1:51] Teranova's there. [1:52] >> I know it. [1:52] >> Like almost every game. [1:53] >> I know. [1:54] >> He just loves it so much. [1:55] >> That's a plan. I'm going with him. Um [1:57] >> you're going to go to the 911. [1:58] >> Oh, with you? Yeah. [1:59] >> I was going to go. [2:00] >> Yeah. Oh, you're not going? [2:01] >> It's Jewish holiday. [2:02] >> Oh, what does it fall on? [2:04] >> Uh what's 911? Uh September 11th. [2:06] >> Probably. [2:08] >> Do you consider yourself the greatest [2:10] financial journalist of all [laughter] [2:11] time? [2:12] >> Oh my god. [2:13] >> No, I don't. I try not to. consider [2:15] myself at all. [2:16] >> Start the interview. I'm [2:17] >> just asking. [2:18] >> Why are you so awesome? [2:19] >> I mean, come on. Uh, [2:20] >> we are going to make you We are going to [2:21] make you blush. [2:22] >> I've aged into it. [2:23] >> No, but you know what? I I feel this way [2:25] and I think I speak for the fans. You [2:27] feel as much like a practitioner [2:30] >> as anybody in modern times that has [2:32] reported on the financial markets. [2:35] >> I guess I'll take that as a compliment. [2:37] I You're saying you feel that way about [2:40] him or he feels that way? [2:41] >> That's how I feel. [2:43] >> Oh, because you said you [2:45] Whatever I said, I said how I feel. [2:46] >> I know what you meant. [2:47] >> I was there. [2:48] >> That's how I feel. [2:50] >> Um, [2:50] >> you'll take it or you take that at comp. [2:52] >> I will take that. Although, um, [2:54] >> you feel like you're more than just an [2:55] observer. I'm saying I feel that. I just [2:57] said it again. I Right. Go ahead. [2:58] >> I feel like I I always view it as like [3:00] kind of color commentator, but maybe [3:03] sounding a little more like the color [3:05] commentator who has a good feel for how [3:07] the game is played as opposed to just [3:09] like covering it in a neutral way. But [3:12] the funny thing about it is I have zero [3:14] interest and never have had an interest [3:16] in actually doing this stuff. [3:18] >> Like I've never wanted to trade. I've ne [3:21] I've multiple times I've been like, [3:22] "Hey, come on over. Sell side by side, [3:24] you know, try it out." And I've never [3:26] been tempted. [3:27] >> You've never like been so right on [3:29] something that ends up happening where [3:30] you were like, you know, in an alternate [3:33] universe, I'm a two and 20 and I [3:35] capitalize on this thing that I saw [3:38] coming before anyone else. only in the [3:40] most like abstract hypothetical way. Not [3:43] in a way where I legitimately [3:46] like crave that feeling. [3:48] >> Okay. [3:48] >> And I just think it's honestly a [3:49] temperament thing. Like I don't have the [3:50] gambling thing. Um and the more I've [3:53] I've kind of covered markets and learned [3:55] about it. [3:55] >> You don't have you don't get the the [3:57] satisfaction out of a winning bet. [3:59] >> Not really. [4:00] >> Is that what you mean when you say don't [4:01] I don't have [4:01] >> you know what because you're an umpire. [4:03] You call balls and strikes. You don't [4:04] really make predictions. [4:05] >> It could be that. Yeah. Um that's true. [4:07] I don't actually go out and say this [4:08] stock's going to here, uh, or I think [4:11] the market's going to have a, you know, [4:12] 15% drop or anything like that, but I [4:14] just feel like, and by the way, I love [4:16] the research on gamblers where they I [4:18] don't I don't know if it's be been [4:20] debunked yet, but they say the thing [4:21] that gamblers are chasing is not the [4:24] winning. It's the moment right before [4:27] you find out whether you won or lost. [4:29] >> Really, it's like that suspense of like [4:32] it might happen. [4:33] >> It's like Christmas morning right before [4:35] you pull the wrapping paper off the [4:36] gift. No, you're right. Happy when [4:37] you're happy. [4:38] >> I remember last year I bet I money the [4:40] Lions in game. I think against the [4:41] Giants last year and when Gibbs broke [4:43] that run and you knew that you were [4:44] about to hit the bed. It's the best [4:45] feeling. [4:46] >> Yeah. Well, yeah. Exactly. Right before. [4:48] But um I mean in terms of being a [4:50] practitioner like I never would pretend [4:51] that I could actually, you know, I could [4:53] like fake it. I could [4:55] >> Have people come along Have people come [4:56] along and said, "Why don't you join Why [4:58] don't you join my firm? We need a smart [4:59] guy that understands markets who could [5:01] communicate to clients." I'm sure you've [5:03] been tempted [5:03] >> over the years that's happened. Yeah. [5:05] And um you know, I'm not going to say [5:07] that I haven't um in a contract [5:10] negotiation floated that prospect out [5:12] there as a stalking horse. Um they [5:14] didn't bite, but you know um I I do [5:17] think that it's a it's a analogous role [5:20] to be kind of a strategist as you guys [5:22] you know anything like you guys are. But [5:24] um for me it's been much more about like [5:27] like I didn't come into this with some [5:28] innate love or interest in financial [5:32] stuff. Like my first job out of college [5:34] was at this financial trade rag as [5:36] publisher of like a lot of newsletters [5:38] in a a trade magazine called Investment [5:39] Dealers Digest. And when I was going for [5:42] the interviews, I was pretty sure but [5:46] not 100% sure certain that the stock [5:48] tables in the newspaper were in dollars. [5:52] [laughter] [5:53] Like I pretty I was pretty sure but like [5:55] they don't put the dollar sign. Maybe [5:56] it's points of some sort. Uh and plus [5:58] the the fractions and everything at the [6:00] time. So, you know, I kind of came into [6:03] it and then I realized that it's a great [6:05] forum for all the things you would ever [6:06] want to write about and talk about, [6:08] which is like winners and losers and [6:10] these complex systems and trying to [6:11] explain how the world works. And you [6:13] know, I think I also have looked up to [6:15] people who've done this type of thing, [6:17] whether it's a strategist or a writer, [6:18] who um [6:21] they utilize everything they know, [6:23] right? I mean, what kind of job? So, [6:25] wait, I I I totally identify with that. [6:28] Like yesterday, I don't know anything [6:30] about science. [6:31] >> Yeah. Yesterday, I just happened to have [6:34] personally found the news about Mona [6:37] effectively being able to in six weeks [6:40] create a personalized cancer vaccine [6:44] specifically tuned in to like your type [6:48] of tumor and thereby injecting that mRNA [6:53] into a person and having it go to work [6:56] on any potential risks because it's and [6:59] then and then the stock went [7:02] 170% or something on the day. [7:05] >> I just went down this whole rabbit hole [7:06] of like why is this such huge news? [7:09] Because I'm not like a biotech trader, [7:11] but I agree with you like every day you [7:14] get an opportunity to learn something [7:16] new and talk about something completely [7:18] new. And maybe people in other [7:20] disciplines can say that, but finance [7:22] touches money touches everything in the [7:25] whole world. So I sports like anything [7:28] that you could possibly be interested [7:29] in. There's a a monetary angle to [7:32] >> I was a history major. I was like a [7:33] liberal arts guy and I always joke that [7:34] I majored in history because it included [7:36] everything, [7:37] >> right? [7:37] >> Like you know and so it's like the [7:39] decision of not making a decision. So [7:40] like if we're talking about oil, you [7:42] want to know about the history of Russia [7:44] wanting to have some kind of a domain [7:46] over that part of the world through [7:48] Ukraine. That's relevant. [7:50] >> But do you So where do you get your most [7:52] satisfaction from then? It's so it's [7:54] obviously not about being right and most [7:56] of the time you're not like make writing [7:57] predictions anyway, [7:58] >> right? [7:59] >> Is it I wrote this beautifully like I [8:02] did I I did a 600word column. I [8:05] perfectly explained everything the [8:08] reader could need. It was a little bit [8:10] literary and it's just it was like a [8:12] flawless piece. Is that for you? [8:14] >> Something close to that [8:14] >> more so than being right about something [8:16] or being [8:18] >> Yeah, I mean obviously both are great [8:20] but um it's much more the former. It's [8:22] much more I I captured what's happening [8:26] or what seems to be happening in a way [8:28] that is efficient, eloquent, and it [8:33] actually illuminates it for somebody [8:35] reading it. It was looking at it from a [8:37] way where it feels like, yeah, that [8:38] feels right. [8:38] >> So, I think that's why you're my [8:40] favorite um investment [clears throat] [8:42] writer, markets, like markets columnist, [8:44] because [8:45] >> you're the best at that. [8:46] >> You're the best at that I think. I think [8:48] ever. And I could cite specific columns [8:52] that you've done with the history thing [8:54] that you're like you must have written [8:57] this 25 years ago. Um you're talking [8:59] about the Hartford Insurance Group. [9:01] >> Oh yeah. [9:02] >> And you do a column and you explain why [9:04] are the insurance companies in Hartford. [9:05] It turns out [9:06] >> it's the highest elevation in New [9:08] England. [9:08] >> That's where you got that. [9:09] >> I found out I found out because he cuz [9:11] he's told us [9:12] >> he never gave you credit. I've heard [9:13] that story a million times. [9:14] >> I never gave credit to the person I [9:16] heard it from. And it it what it really [9:17] actually was I believe it's like a very [9:20] wide part of the river. So I almost [9:21] misstated it. [9:22] >> But but you've done that every week for [9:25] 30 years. It's unbelie. [9:35] You're doing you're doing pros. It's it [9:38] stands out and I just I think it's [9:40] brilliant. [9:40] >> Well, thanks. I mean, and and you know, [9:42] look, a lot of it goes back to I came at [9:44] it, I always say people do what I do, [9:47] roughly, financial journalism, uh, any [9:49] kind of journalism. Some people come at [9:51] it because they're writers and they're [9:53] they're good at articulating a thing or [9:55] they feel like that's their edge. Other [9:57] people are just like news hounds. They [9:59] just want scoops, just want to crack [10:01] heads and find the information first. [10:03] Um, and I like to speak authoritatively [10:05] about things and all that, but but I I [10:07] kind of got off the scoop treadmill at a [10:08] very young age and was like, let me just [10:10] try and describe. But also that goes [10:12] back to Barons where I spent 15 years [10:14] and you had a whole week of kind of like [10:17] absorbing I digesting what's going on, [10:19] seeing all the other short-term [10:21] storylines play out in a given week on [10:23] Friday night. filing on Friday night and [10:25] then on Saturday morning at the time, [10:28] you know, physical newspaper arriving on [10:30] Saturday morning, you had a way of [10:32] trying to just distill it into what [10:35] mattered most or was most entertaining [10:36] to read about the market. So now you're [10:38] on TV. Michael, why did the Dow just go [10:41] up um 25 points in the last 10 minutes? [10:44] >> Not a joke. [laughter] [10:45] >> That's exactly what it is. [10:46] >> Well, I think you do both uh equally [10:48] well. And uh All right. Uh did we do the [10:51] show? [10:51] >> The show's over. Sorry. All right, guys. [10:53] This is [applause] [10:55] >> do do your thing. [11:03] [music] [11:08] [music] This podcast is brought to you [11:10] by DBMF, the world's largest managed [11:13] [music] futures ETF. Feel like the [11:15] world's changing fast? [11:16] >> Sure do. Imagine a strategy built to [11:18] move when everyone else is standing [11:19] still. Going long or short across global [11:21] markets is a trend shift. DBMF is made [11:24] to move differently. A single lowcost [11:26] ETF offering genuine [music] [11:28] diversification even when stocks and [11:31] bonds move together. Discover why DBMF's [11:33] liquid uncorrelated managed future [11:35] strategy could be what your alts [11:36] allocation [music] is missing at [11:38] www.dbmf.com/tcf. [11:41] DBMF made to move differently. The IMGP [11:44] [music] DBI managed future strategy [11:46] ETFs. Investment objectives, risk, [11:48] charges, and expenses must be considered [11:50] [music] carefully before investing. The [11:51] statutory and summary perspectuses [11:53] contain this and other important [11:54] information about the [music] investment [11:55] company and may be obtained by visiting [11:57] www.imgp.com. [11:59] The fund is distributed by Alps [12:01] Distributors, Inc. DBMF is the world's [12:04] largest managed futures ETF as of July [12:06] 31st, 2026 with 4.16 [12:10] billion AUM. [12:15] What do you think? What's with the [12:17] glasses? Is that paparazzi? [12:20] Are we laying low, Nicole? [12:22] All right, ladies and gentlemen, welcome [12:24] to the world's greatest investing [12:26] podcast. My name is Downtown Josh Brown. [12:28] First time listeners, [12:31] welcome. You're in for a treat. [12:33] [applause] [12:33] Last time listeners, I'm sorry. We [12:35] tried. We did our best. With me today, [12:38] as always, my co-host, Mr. Michael [12:40] Badnick. Michael, say hello. Hello. [12:41] Hello. We [applause and cheering] have [12:44] Financial Media Royalty in the house. [12:47] Michael Sani is co-anchor of CNBC's [12:50] Closing [music] Bell, Overtime, and [12:53] serves as the network's senior markets [12:55] commentator. He also writes regular [12:57] columns [music] and produces original [12:59] video for CNBC.com [13:01] and CNBC Pro. Sani joined CNBC in [13:04] October 2015 from Yahoo Finance where he [13:08] was a senior columnist and before that [13:11] of course a legendary run at Baronss. 15 [13:14] years as a columnist and feature writer, [13:16] having begun his career in the early 90s [13:19] covering the securities industry for Dow [13:21] Jones Newswires. Mr. Sani, thank you so [13:24] much for being here. [13:25] >> So great to be here. I uh [13:27] >> the crowd is going absolutely fanatic. [13:30] >> Thanks for accepting my invitation to be [13:31] invited. [13:32] >> All right. Um I'm telling you that I'm [13:35] telling you that I have always wanted to [13:36] have you on, but you're on closing bell [13:39] overtime and we tape the show exactly at [13:41] 3:00. [13:41] >> Josh is too nice. I've asked you a [13:42] million times and he always says he [13:44] can't do it. [13:44] >> I always say that guy every time. [13:46] [laughter] [13:47] >> I appreciate being being considered and [13:50] just left in a waiting room. [13:51] >> I was a little nervous to ask you [13:52] because I know you're you're on TV. Um [13:54] but I I did want to tell you you taught [13:56] me the stock market. This is a true [13:57] story and I I've told you this before, [13:59] but I want the audience to understand. [14:00] >> You have and you make it sound like I'm [14:01] 30 years older than you, which is fine. [14:03] It's okay. [14:04] >> But but you really did because so I [14:07] started I started my career at [14:09] Liberbound Blue Chip firm. Yeah. [14:11] >> [laughter] [14:11] >> Uh it was a bucket shop on Long Island, [14:13] but my parents didn't know better. They [14:15] knew somebody that worked there and [14:16] they're like, "Go work go work for him." [14:18] I was a aimless uh uh idiot. But I was [14:22] smart enough to realize that the people [14:23] I worked for didn't know anything. Like [14:25] literally nothing except one guy and [14:28] I'll never forget this. I went up to him [14:31] after 4:00. All the brokers were doing [14:33] cocaine or whatever they were doing. Um [14:35] the room was empty and I walked up to [14:37] him and I said, "You are the only person [14:38] that I see reading the Wall Street [14:40] Journal. you seem to sort of know what's [14:42] going on. How do I learn about stocks? [14:45] And I'm a cold caller. I'm not even [14:46] licensed. And he said this exactly. He [14:50] said, very important, the C-section of [14:53] the Wall Street Journal every single [14:55] day. It's Was that the money and [14:57] investing? [14:58] >> Money and investing. Read the C-section. [15:01] Don't worry about B. It's politics. [15:02] Don't worry about A. It's It's like New [15:04] York Times. Read the C-section. Okay, [15:06] I'll do that. What else? If you want to [15:08] learn how to if you want to learn why [15:10] the market's doing what it's doing every [15:12] Saturday read Baronss except for Abson. [15:16] [laughter] [15:16] >> Yeah, exactly. [15:17] >> He said Ablesson you will leave the [15:18] business everybody else. [15:21] >> He didn't say you but you were the best [15:23] columnist at Barrens at that time. And [15:25] then the third thing he said which is [15:26] maybe where I learned the second most [15:28] from he said business week Gene [15:30] Marshall. [15:31] >> Yeah. If you want to learn how to pitch [15:32] stocks, Jean Marshall is the best stock [15:37] individual stock storyteller in the [15:39] world. [15:39] >> Yeah. [15:40] >> And his column was called Inside Wall [15:42] Street. And so I did it. I listened to [15:44] this guy. Y [15:45] >> and that's how I learned the stock [15:47] market. And [15:48] >> yours was the first column I'd read [15:50] because of everything that we just [15:51] talked about. I just felt like this [15:53] guy's not just saying what's happening. [15:56] He's a writer. And I read novels. I read [15:59] literature. So it just it resonated with [16:01] me. Anyway, that's how I learned the [16:02] stock market. So thank so thank you for [16:05] that. [16:05] >> I'll take a tiny slice of the credit for [16:07] that. Thank you. I mean obviously Baron [16:09] was a great place to just like find a [16:11] voice and also you know you're being [16:13] read by people who know a whole lot more [16:16] than you. [16:17] >> Oh I agree. and you have to therefore [16:18] rise to in fact one of the reasons I [16:20] stepped off um you know a lot of reasons [16:22] I I felt like I wanted to move on from [16:24] there but one was I had got myself in [16:26] this trap on this treadmill of like you [16:29] know this is like early 2010s and it's [16:32] like I'm trying to stay one step ahead [16:35] of these guys who stay two steps ahead [16:38] of the overall market for a living and [16:40] they have all the resources and you know [16:42] and it was just exhausting and you kind [16:44] of think yourself into circles and to be [16:46] honest a lot of times What it did and [16:47] being at Barrens was part of this is it [16:49] backed you into a kind of reflexive [16:52] contrarianism or let me just say the [16:55] provocative thing that goes against the [16:57] prevailing trend or whatever it is. And [17:00] I I kind of I kind of bristled at doing [17:02] that all the time because you know you [17:04] have to have a certain tolerance like [17:05] Allen did Abson of just like screaming [17:09] into the darkness and saying why did the [17:10] market go down? [17:11] >> So he was like this feared bear that [17:14] then. Don't you feel like his columns [17:16] now versus like what else is out there [17:19] is pretty quaint? I don't even think it [17:21] would get noticed on Twitter these days, [17:23] but back then it was like, uhoh, Abson's [17:26] about to go to town on Microsoft. [17:29] >> Now it's like [17:30] >> it would just be this floorid way of [17:31] saying like, oh, there the crowd goes [17:33] again doing it silly herd like things. [17:36] And once in a while there would be a [17:37] targeted, you know, takeown of a of a [17:39] company or whatever. And you know, I [17:41] don't know if this is if if this is [17:43] true, but I've had people come to me and [17:45] point to uh the crash of 87 [17:48] uh that period of time where the that [17:51] was of course on Monday and the weekend [17:53] before that Allen who was was bearish [17:55] leading up to that. But if you remember, [17:56] the market peaked in that August and it [17:58] was down huge into the crash. Yeah. Like [18:00] it was already kind of uh kind of a [18:03] mess. And I think he was kind of saying [18:05] like, "Aha, look at this. Finally, the [18:07] world's coming around to my way of [18:08] thinking. there's some good stocks that [18:10] are cheap now, whatever. Next day, [18:12] market goes down 22%. [18:13] >> And it was like never again. [18:15] >> It was he had his moment. [18:16] >> I have no idea if that's true, but [18:17] that's [18:17] >> So then he couldn't ever be bullish [18:19] again just in case. [18:19] >> I mean, I think temperamentally he [18:21] wasn't geared to anyway. [18:22] >> Nobody ever expects the crash of 87, [18:25] right? It's like a It's like a [18:26] MontiPython sketch. [18:28] >> Exactly. [18:28] >> All right. Um and then I taught Michael [18:30] the stock market after you taught me. [18:33] >> Who taugh Who Yeah, sure. Who taught you [18:34] the stock market? [18:35] >> Nobody really taught me anything. I [18:36] think it's really just like pulling from [18:38] every direction and just like reading [18:41] smart people and uh [18:43] >> is that Barton Big's book up there? [18:44] >> Yeah. [18:45] >> Because I mean like Barton's a great [18:46] example what I'm talking about. It's [18:47] like an English major. [18:49] >> But you talked to a lot. This is the [18:51] thing about what's different about you [18:52] versus what Michael and I do. Michael [18:54] and I when we write, we're bloggers. [18:56] We've written books, but like [18:58] >> we're not sourced. We're just reading [19:01] other people, synthesizing, looking at [19:03] charts, looking at some data. Yeah. [19:06] Coming up with our op own opinions. You [19:08] were talking to real people behind the [19:10] scenes that were managing real money. [19:12] >> And I think that's where your part of [19:14] your edge probably came from. [19:15] >> That is true. And especially the people [19:17] who are a little bit more tactical, [19:20] um, willing to kind of stray away from, [19:23] you know, the the kind of standard [19:25] playbook a little bit or not the in the [19:26] closet indexer types. But you know what? [19:29] these days it's more what you do than [19:30] than not. Like I do still keep in touch [19:33] with people and try to have a read on [19:34] what they're thinking and saying, but [19:36] >> they don't know. They don't know [19:37] anything anyway. Nobody knows. [19:39] >> That's almost comforting though. [19:40] >> But you think it's the opposite now. [19:41] Everyone knows everything because [19:42] there's so much information out there. [19:43] >> I think Yeah. Almost everyone knows a [19:45] certain level of of what's going on. Um, [19:48] I've always said that that was what I [19:50] found valuable about, you know, when I [19:51] first took to Twitter and, you know, um, [19:55] you know, I was in I was a news I've [19:56] been a newswire reader in real time my [19:58] whole career, but it was just like, let [20:01] me just keep it up with this to make [20:03] sure I'm not missing anything, right? [20:04] And it is all there like you sort of see [20:06] the crescendo of attention in certain [20:08] things and um yeah so I don't know if [20:11] anybody is anymore saying you know in a [20:13] broad sense on the overall market I have [20:16] an edge and I'm going to [20:17] >> but I think to your question I think [20:19] everyone is now so up to speed and is [20:23] everyone is like drinking from the fire [20:25] hose. [20:25] >> Yeah. [20:26] >> The skill is like figuring out what to [20:28] really pay attention to what not to [20:30] which of course you can do it sometimes. [20:32] You can't always do it all the time. But [20:34] that's what makes you so valuable still [20:36] is because there's almost too much now [20:38] that you people need somebody to [20:40] synthesize. [20:40] >> Focus it down. Yeah. [20:41] >> Give me 800 words. What matters, [20:43] >> right? [20:44] >> Focus it down. Um what what theme is [20:46] either misunderstood? Look, a lot of [20:48] this comes down, you guys know, is like [20:50] what version of history applies today? [20:52] because you can find an analogous period [20:55] or or something that looks like this [20:57] type of market behavior and you could [20:59] infer what you want from it, but it's [21:01] nothing is nothing. [21:03] >> We're the we're the it's always [21:04] different guys. [21:05] >> Yeah. [21:05] >> Like unapologetically, [21:07] >> right? [21:08] >> No, this time it is different and last [21:10] time it was different too and the time [21:11] for like that's our [21:13] >> I'm so curious. You just reminded me of [21:14] this about like different [21:15] interpretations. Yeah. [21:16] >> So, I was talking with Ben this week and [21:18] we've had this argument a billion [21:19] different times. When does a bare market [21:21] end? When does a bull market start? [21:23] >> Yeah. [21:24] >> So, the analogy that I gave to Ben is [21:26] you could look at a player like Vin [21:27] Baker just as his box, right, basketball [21:30] references like, "Oh, he was a great [21:31] player." Like, whatever, he was okay. [21:33] >> It's not the same thing to look back as [21:36] to live through it, [21:36] >> right? [21:37] >> So, you can look back to 2009 as the [21:40] start of the bull market, which is what [21:42] Ben was arguing for. And I said, "Dude, [21:44] noing way was that a bull market. No [21:46] way. I know it was the end of the bare [21:48] market, I suppose, like on the chart." [21:50] Yeah. But the bare market didn't [21:52] actually end until 2012, 2013. Like you [21:56] were there. Who was talking about a bull [21:58] market in 2011 during the double dip, [22:00] the euro stuff? When did people even [22:02] start to say the word? [22:03] >> I'm on your I'm on your bull market. [22:05] >> I'm on your Ben describing Ben's [22:06] describing a rally. [22:08] >> A rally is not a bull market. [22:10] >> I think what matters is what people were [22:12] saying in real time and nobody was dumb [22:15] enough to [22:15] >> say nobody was saying that. But I do [22:17] think that uh the end of a bare market [22:20] and the beginning of a bull market are [22:21] really only defined in retrospect. So [22:23] you're in this nether zone of like we [22:26] don't know how it's going to break from [22:27] here and it's going to look very [22:28] similar. A bare market rally is what [22:31] it's I I can remember one of the uh most [22:36] highest hit rate uh pieces that Barry [22:40] Rholz ever wrote. It must be because it [22:42] was called bare market rally. [22:43] >> Okay. And it was like I used to just [22:45] stumble on it all the time for some [22:46] reason. On the big picture on big [22:48] picture block [22:49] >> and it was probably in late 2009 [22:52] >> and it's like rage bait at that period [22:53] of time. But that's the point that [22:55] Michael's making. [22:55] >> I know [22:56] >> saying bare market rally. [22:58] >> Yeah. [22:58] >> Or dare I say new secular bull market in [23:02] ' 09. [23:03] >> People would think that you should be [23:05] arrested. Well, that brings me to my [23:08] mystery broker guy because that's kind [23:09] of what he did in late '09 is he he says [23:12] the financial crisis is over. We don't [23:14] >> Should we clear up once and for all that [23:15] it's not me? [laughter] [23:17] >> Well, we we had a little bit of of [23:19] vagueness about that uh up until last [23:22] December when it actually was [23:23] identified, right? But um I wouldn't [23:26] ever I would always say it's nobody [23:28] you've ever heard of [23:29] >> which is what makes but tell the story [23:31] of the of for people. [23:32] >> I was at Baron's um and there was a guy [23:35] who was a a financial adviser a broker [23:37] who would occasionally write you know he [23:39] was like send me his kind of client [23:40] letter um and he had done so he had [23:43] written one in ' 07 that was really [23:45] close to the top of the market and he [23:46] was like this is going to fall apart. [23:48] Not saying he caught every beat. This [23:49] was not March of09 that he wrote me back [23:52] but he did uh later that year. year. I [23:54] think it might have been August, [23:54] September of that year. [23:55] >> Close enough. [23:56] >> And he was like, "It's done. It's over. [23:58] Financial crisis is over. You know, you [24:00] have to be playing it like it's a new [24:03] bull market." And I I wrote about it [24:04] without naming him because he did not [24:06] want to be named. He didn't want [24:07] >> that mystery broker [24:08] >> uh eventually. Not in the first [24:11] >> not in the first time. The first time I [24:12] was like, "So there's this guy who [24:14] writes me." I literally that's how the [24:15] thing started. And for me it was a [24:17] lesson of the people's psychology of why [24:20] they just fixated on this guy and they [24:23] wanted they would ask for updates all [24:24] the time on Twitter. I would update when [24:25] he had a change of view. I would never [24:27] call him and ask him what he thought [24:28] because I felt like that was a little [24:30] artificial. I wanted to make sure he's [24:31] kind of got a new take before I [24:33] highlighted. And uh he became this weird [24:36] franchise. It kind of got away from me. [24:38] I didn't really want it to become a [24:39] major thing. over the years he he kind [24:42] of flirted with the idea of being [24:43] identified. [24:44] >> Uh the mystery broker ETF I just imagine [24:46] >> and I would always tell you I would [24:48] always say I would always say to [24:50] everybody you'll be disappointed when [24:52] you find out [24:53] >> cuz it's nobody from nowhere. [24:54] >> It's nobody you heard of [24:55] >> and it's you know and then they would [24:57] say like oh I think it's Ter. It's like [24:59] ter talks about ter goes on TV when he [25:02] has something to say. He doesn't mystery [25:04] broker. Why is that what's or cash? [25:06] >> What do you mean by that? the psych it [25:08] speaks to the psychology of people like [25:11] uh [25:11] >> people think there's a secret person who [25:13] knows the answer. [25:14] >> I was going to say I read somewhere 31% [25:16] of US adults believe in magic. [25:18] >> Yeah. [25:18] >> So that's like they believe there's a [25:20] man who can divine the future course of [25:24] the stock market based on whatever [25:26] signals he's looking at. [25:28] >> Michael, you you have a bit in here from [25:29] Adam Smith's The Money Game, which is my [25:32] favorite investing book of all time, [25:33] like by far. [25:34] >> And I'm pretty sure it was him, but it [25:35] could have been somebody else. Maybe it [25:36] was Peter Burns. I can't remember who [25:38] said like, "Nobody can see the future. [25:40] We're all so bad at predicting what [25:42] happens next. Then why? Surely the [25:44] public like must be onto it." After a [25:45] while, you're like, "All right, I get [25:46] it." No, the quote was like, "The demand [25:49] being there, the the predictions must be [25:52] supplied." [25:52] >> That's right. [25:53] >> And it's demand from the public. People [25:54] like, "No, I know you can't really see [25:56] the future, but like so a family member [25:58] of mine asked what Josh thought about. [25:59] Is Josh still bullish on CrowdStrike?" [26:01] >> Okay. [26:01] >> And I was like, "Listen, yes, Josh has [26:04] >> Uncle Morty, I'm still bullish." [26:05] >> Yes. I said, "But he, you know," he [26:07] would, he, this is what Josh would say. [26:08] "You probably know as much about the [26:09] stock as I do. I'm bullish long-term on [26:11] cyber. I like the CEO. I like what [26:13] they're doing, but what do I know?" And [26:14] he said, "No, I know, but like does he [26:16] still like the stock?" [26:17] >> Yeah. Like, you can't convince people [26:18] that you don't know the future. [26:19] >> That's exactly right. And people come to [26:21] me all the time like, "Wow, I'd really [26:22] love to get you, you know, just across [26:25] the table and you could tell me what, [26:26] you know, what's really [26:27] >> what's really going to happen." Can I [26:28] tell you Can I tell you a thing that [26:30] I've noticed in that regard? And I want [26:31] I wonder if you've noticed it, too. [26:34] I have spent I've been doing TV 14 15 [26:38] years. I've spent the entire time [26:40] complaining that stock people are being [26:43] held to a different standard than NFL [26:45] commentators on Sunday [26:47] >> where they go around the table, Terry, [26:49] what do you think? What do you think? I [26:50] like the Steelers. And like nobody [26:53] nobody's like, you son of a You [26:56] said the Dolphins. It's just like they [26:59] made a prediction. [26:59] >> Somehow they're worse than a coin flip [27:01] against the spread. [27:02] >> Fine, but they're right. They're wrong. [27:04] They have biases. They like the player. [27:06] They like the coach. They used to play [27:07] for the team. It doesn't matter. [27:09] >> That's right. [27:09] >> That's one standard. [27:11] >> I go on CNBC. [27:14] >> Yeah. [27:14] >> I'm right on three stocks in a row. The [27:16] fourth one's not good. This scumbag Josh [27:19] [laughter] Brown. Okay. So, I always [27:21] like whatever. I don't complain too [27:22] much. I'm doing I'm doing fine. Um but [27:25] like that was always I've noticed that [27:27] that's changing in the era of everybody [27:30] gambling. [27:31] >> Mhm. Those guys are getting hell. I [27:34] don't know if I want to be Howy Long [27:35] right now. I might rather be Jim Kramer [27:38] than Howie Long. I lost 16 games. [27:41] >> Those guys get get that thrust. They [27:42] must all the fantasy because now that's [27:45] almost being looked at as financial now [27:47] that you put gambling into Robin Hood. [27:49] >> Yeah. [27:50] >> And prediction markets into the broker [27:52] into interactive brokers. [27:54] >> Now all of a sudden those guys are like [27:56] being treated like like Kramer, [27:58] >> right? And I don't know [27:59] >> the new Kramer is like real [28:01] sophisticated seeming tip sheet type you [28:04] know program was like I I'll have you [28:06] noticed this [28:07] >> definitely okay I'll never forget um [28:09] this kind of came into a little more [28:11] clarity for me when uh dur right in the [28:13] p pandemic meme stock craze post you [28:17] know and um yeah of course we could look [28:19] at the Herz being bought up when it was [28:21] in bankruptcy or the whole thing and [28:23] there was a quote I believe it's in the [28:24] FT story about this and they they went [28:26] to a guy who's like a golf pro at some [28:28] club and uh he's been playing these [28:30] stocks and they asked him about it and [28:32] it's like you know you don't really know [28:33] anything about this like what's the [28:34] story? He's like he's like no look I [28:36] mean it's better than sports gambling [28:38] because if I'm wrong on a game I lose [28:40] everything. [28:40] >> Zero. [28:41] >> Yeah. [28:41] >> If I buy Hertz it goes down 30%. I still [28:43] have 70%. I'm like I guess. [28:45] >> Yeah. That's why you got to do the 10 [28:47] team parlay bird cage that Michael does. [28:50] >> Then you get to be wrong on multiple [28:52] legs, [28:52] >> right? [28:53] >> Okay. [28:54] >> You send somebody up to Foxwoods to [28:55] place the bets for you in a helicopter. [28:57] Yeah, I know about it. [28:58] >> Let's I want to play a video for you. [28:59] Okay. [28:59] >> Yeah. [29:00] >> All right. Do we have that clip from uh [29:02] Michael's birthday party 1989? [29:04] >> 25 years ago. When the country announced [29:06] good numbers, interest rates went down [29:08] because we had a stronger country. Now, [29:11] when we announced good numbers, the [29:12] better they are, the worse it is for [29:14] interest rates. So, we could be we could [29:17] have a GDP of 10 times. You know, they [29:19] say, "Oh, it's going to be three times [29:20] or 4.1." [29:22] Uh we could have a GDP of 10, 12, 15 [29:26] times. [29:27] If they just leave us alone, let us let [29:30] the rates go down. We should pay the [29:32] lowest interest rates. You know, every [29:34] point of interest is 600 billion. Think [29:37] of that. Every point of interest is 600 [29:40] billion. Two points means we make a [29:43] fortune, but we keep driving it up. It's [29:47] a very unfair system. And I've said it [29:49] now for a long time. When our country [29:52] does well, interest rates should go [29:54] down. I mean, every time I hear a [29:57] country is doing well, I say, "Oh, it's [29:58] too bad." Because they lift up interest [30:00] rates. They should drop interest rates [30:02] because it means we have a strong [30:03] country and it's all based on credit, [30:06] meaning good credit, and we have the [30:07] best credit. And we'd pay off the debt [30:10] very easily and very quickly. But if [30:13] somebody's paying a half a point, we [30:14] should be paying a half a point, not [30:16] somebody else. Right now, I think it's [30:18] Switzerland has the lowest. again, and I [30:20] don't want to single them out, but if [30:21] you take our business away from [30:23] Switzerland, they have problems. [30:25] [laughter] So why are they paying a half [30:26] a point and we're paying much more than [30:29] that? [30:31] >> So, does that make sense? [30:32] >> No, it does. [30:33] >> No, [laughter] no, [30:34] >> it does make sense. I All right. So, I [30:36] actually agree with everything he said [30:38] other than the the numbers like [30:41] [laughter] [30:41] >> the first thing he said was right. [30:43] >> The premise, but but it occurred to me. [30:45] It occurred to me Trump thinks like a [30:48] borrower. Of course, [30:49] >> he's a real estate guy and a casino guy, [30:51] >> a borrower who was repeatedly cut off [30:54] and who repeatedly went bankrupt and who [30:56] therefore did not have credit or access [30:57] to it. [30:58] >> Yes. But as a real estate guy, he's [31:01] like, "If my business is going great, [31:03] >> I'm going to pay a lower interest rate." [31:05] >> He traders don't think that way. Traders [31:08] think if things keep going this well, [31:11] they're going to have to tighten the [31:12] money supply. [31:13] >> Yeah. [31:13] >> And that's why the rates go up, [31:15] >> of course. [31:16] >> Okay. But I'm I'm making this point. [31:18] People were mocking him. He's he's like [31:21] sort of right. I don't know where to go. [31:23] >> I mean, he's not he's not at all right [31:25] in talking about [laughter] interest [31:26] rates. [31:28] >> No, but he's right in the sense that we [31:29] should [31:30] >> premise of if we're the United States [31:32] >> and the economy is going great. And I [31:34] think that's fairly true. Yes. Not for [31:36] every single person in the economy, but [31:38] right now there's a ton of activity. [31:40] People are making money. Consumers are [31:42] spending. It's like it's good. Business [31:44] is spending. he sort of has a point like [31:47] wait the news is good and they raise our [31:49] interest rate. I understand the [31:52] disconnect but I just thought that was [31:53] an interesting way of phrasing it and I [31:56] >> he has he has said things like this for [31:59] years and it's very clear it's exactly [32:00] where it's coming from which is what you [32:02] said. um you know but also he's not [32:06] talking about the country it's the [32:07] government and the government is has to [32:09] sell trillions of dollars worth of paper [32:12] every year right [32:13] >> and next year it's going to be two $2 [32:14] trillion more than it was this issue and [32:16] so um obviously you know global markets [32:19] set those rates um we don't pay a [32:22] premium because of bad credit right it's [32:25] because of the macro conditions by the [32:27] way we've been so fixated this week on [32:30] where Treasury yields are [32:31] >> it's not the credit worthy that's [32:33] driving the yield, [32:34] >> which is what he's experienced. [32:35] >> That's right. It's It's definitely not [32:37] directly creditworthiness. Um, now I [32:39] think there's a lot of debate as to why [32:40] rates are where they are if you look [32:42] longer term. I don't want to get too [32:43] like wonky about it, but like how low do [32:46] we think 10year yield should be um when [32:51] nominal GDP is like close to 6%. Right. [32:53] >> And we have all this borrowing going on [32:55] to invest from the private sector and [32:57] everywhere else. Um, it's not weird. [33:00] It's like it's kind of in the range of [33:01] where you'd expect it to be. [33:03] >> So, here are the things I want to hear [33:04] your your response to them. [33:07] >> Thing one is political dysfunction. As [33:09] if as if like three years ago everything [33:11] was like not politically dysfunctional. [33:14] Okay, fine. Throw that out. May maybe [33:16] that's a an issue, but it's like a [33:18] forever issue, right? [33:19] >> It's global yields. Okay. Thing two, to [33:22] Michael's point, this is happening [33:23] everywhere with long bonds in every [33:25] country. thing three uh $1.7 trillion [33:30] dollars worth of corporate debt which is [33:34] like 30% more than the same time last [33:36] year competition for you know it's AAA [33:39] debt for the most part [33:40] >> on top of at least sticky inflation if [33:43] not rising [33:44] >> the war prices so to you this is where [33:47] the rates I think it's multiple weather [33:49] systems all interacting in a way that [33:51] are pushing in a direction of higher not [33:53] lower rates it's everything you said [33:55] it's basically [33:57] The world is demanding so much capital [34:01] the bond market has to repric and ration [34:04] it, right? You have to just find the [34:06] clearing price uh at and at through [34:08] higher yields. Um the fiscal concerns [34:11] which arguably you could say long term [34:13] are kind of a creditworthiness thing uh [34:15] in a vague way. I always feel like [34:17] that's it's kind of like the uh the [34:21] underlying autoimmune condition where [34:24] it's like under high stress all of a [34:26] sudden that starts to flare up and it [34:28] starts to create symptoms and people [34:29] start to get really worried about it but [34:31] it's not really [34:32] >> you're describing the difference between [34:33] the weather and the climate. [34:35] >> Yeah. And I think and so the fiscal [34:37] concerns are always going to be there [34:38] but like you say $40 trillion in US debt [34:42] today. We could have had the same panic [34:43] at 30. Um, I'm not I don't think there's [34:46] a magic hard trigger level where all of [34:48] a sudden the world changes. What I will [34:50] say, you talk about political [34:51] dysfunction. So, we're basically at 3% [34:55] of GDP goes to paying interest on the [34:58] debt. [34:59] >> Okay. We were last there in the early [35:01] 90s. [35:03] So, in the early 90s, what it did create [35:05] was a singleisssue third party [35:08] presidential candidate, Ross Perau. [35:10] Like, literally, that's all he cared [35:11] about. [35:12] trade [35:13] >> and the debt, [35:14] >> right? [35:14] >> And you know, right or wrong, it did, [35:18] you know, maybe just because the [35:19] pendulum swung and you had gridlock [35:22] between Congress and the president in [35:23] the 90s, you actually did get fiscal [35:26] discipline even though nobody really [35:28] kind of planned for it or expected or [35:30] wanted it, [35:30] >> right? Um, and I also think that's one [35:32] of the reasons and you know reason that [35:34] you know the kind of hoped for AI [35:36] productivity miracle might have a harder [35:39] time happening in exactly the way it [35:40] happened in the 90s because in the 90s [35:42] you had you know debt to GDP coming [35:44] steadily down the entire time to the [35:46] point where you had a a surplus on paper [35:48] by the end of the 90s. The other piece [35:50] of it is the demographics. You had you [35:53] know very few retired people per working [35:56] person [35:57] >> which is not the case [35:57] >> which is not the case now. So, I just [35:59] feel like those are a little bit of [36:01] headwinds to some kind of huge [36:02] productivity boost, but as you guys are [36:05] saying, it's always different. [36:06] >> Put up the chart, guys. Can we do that? [36:08] >> What is this? What is this saying? [36:11] >> This is Yeah. [36:12] >> public debt outstanding. We've got two [36:14] colors. The light color is debt held by [36:16] the public, which Michael and I have [36:18] said like, yeah, we owe ourselves money. [36:21] Yeah. We are the investors in the debt [36:23] and the debtors. [36:24] >> Robbing Peter to pay Paul. And then the [36:26] other is intragovernmental debt which I [36:28] don't know what is it. [36:31] >> It's like a accounting plug factor for [36:33] like social security trust funds and [36:35] other things that we say you know they [36:38] have a surplus now but and so we say [36:40] that they own treasuries but it's [36:41] >> is it too convenient for us me and [36:44] Michael anyone else to say hey we're the [36:47] people that hold the treasuries. We own [36:49] them in our money market funds. We own [36:51] them in our 401ks. we own the like we're [36:54] we're the whole because is that too [36:56] convenient and simple to just say ah 40 [36:59] trillion we own 30 of it [37:02] >> I mean I don't I don't know that you can [37:03] dismiss it like in other words any level [37:05] would be be fine because we owe it to [37:06] ourselves because at some point [37:09] >> turtles turtles all the way down [37:11] >> yeah it it crowds out other productive [37:13] uses of capital [37:14] >> let me ask this but I don't know [37:16] >> are you surprised how strong the stock [37:18] market is so you have basically every [37:20] index at or near an all time high. We [37:24] are still involved with the war. The [37:26] straight is still closed. That should [37:28] have been or could have been or would [37:29] have been predicted to have been a black [37:31] swan event. Energy limit up, stocks [37:34] limit down, right? Uh that didn't [37:36] happen. The AI trade is not really that [37:40] hot. Yes, the memory stocks. [37:42] >> Yeah. [37:42] >> And the chips had a moment, but Nvidia [37:45] is flat. Meta is down. Microsoft is [37:48] down. Google whatever. Apple's up. But [37:50] it's not like it's not like the Mag 7 [37:51] are powering the stock market higher. [37:53] All their free cash flow is down. You [37:55] had a report earlier this week that uh [37:57] that OpenAI's revenue numbers look kind [37:59] of shitty. [38:01] >> I would have thought just and with [38:02] interest rates where they are given all [38:04] this that the market would be I don't [38:05] know in a normal 12% draw down [38:07] considering how long the bull market has [38:09] lasted. [38:09] >> Yeah, I I I wouldn't say I'm outright [38:12] surprised. I do think all the things you [38:14] mentioned could easily have served as a [38:17] handy excuse [38:18] >> easily [38:18] >> for something much better on the [38:21] downside. we have now on the one hand I [38:24] don't know how much trouble the economy [38:26] or the market can get into with you know [38:28] 6% nominal growth deficits 6% of GDP [38:32] corporate earnings absolutely flying to [38:34] the point where I'm more worried about [38:36] overearning and overstating of earnings [38:38] than anything else but they're doing it [38:40] the earnings are just supporting things [38:42] and I think there's this massive swing [38:43] from you know labor to capital that's [38:46] all going on and that's to the benefit [38:47] of what the S&P 500 captures which is [38:50] mostly a businessto business capital [38:52] goods kind of wholesale economy and so [38:56] for those reasons I'm not super [38:57] surprised. Um I I guess like it wouldn't [39:00] also surprise me to be down a bit. Um [39:02] it's a bull market that to me that means [39:04] 3 to 7% drops happen for almost random [39:06] reasons. [39:07] >> You make you make such a great point [39:08] like Micron is 10 times bigger than [39:10] Disney. [39:11] >> Yeah. People think about how's the [39:12] economy doing. They think about by the [39:14] way Disney's doing okay. It's like $107 [39:16] stock again. But like people when they [39:18] think about how's the economy doing, [39:20] their minds go to Disney, maybe a hotel [39:24] chain, [39:24] >> Target or something. [39:25] >> Target um [39:28] I mean I guess Apple. Yeah. [39:30] >> But like their minds don't go to Micron. [39:32] But that's what's in the earnings. [39:33] >> That's what's that's what's driving it. [39:34] I mean look I I was saying this in June [39:36] back when you know semis could you know [39:38] were just vertical to the upside is so [39:41] many approaches and strategies got you [39:45] to the same place. It's like, oh, I buy [39:47] uh the best earnings revision stocks. I [39:49] buy the best price momentum stocks. I [39:50] buy growth of the reason the same. [39:52] Congrats, you own semis [39:53] >> and value. Micron's the biggest. Yeah, [39:55] exactly. Very true. Um and so you had [39:57] this situation where it's like 18% of [39:59] the S&P is semis. Another 16% is the [40:02] four hyperscalers. They kind of were a [40:04] zero something trading against each [40:06] other for a while. Um I think another [40:08] part of the answer and I know you guys [40:09] have kind of tried to puzzle out this uh [40:12] this whole dynamic of this immaculate [40:14] rotation as I call it where it's just [40:16] like on a given day oh semis are down 2% [40:19] that has to mean Apple's up a percent [40:20] and a half and healthcare's flying like [40:22] it's just almost like [40:23] >> programmatic it feels [40:25] >> very mechanical and and it kind of is [40:27] right it's like there's these big trays [40:28] on where the incremental dollar at least [40:30] tactically is all about trading one [40:33] factor against the other um essentially [40:36] trying to stay neutral across all these [40:38] different um variables and also not be [40:41] out of the market like you kind of you [40:43] know all the signals say you should [40:45] probably have exposure to equities but [40:47] on the other hand nobody has to buy [40:49] >> when you but when you talk to traders [40:51] about the modern market [40:53] >> most likely you're not talking to a [40:55] trader who's trading news [40:56] >> you're most likely talking to somebody [40:58] that works at a hedge fund that's acting [40:59] as a market maker [41:01] >> so if you talk to somebody at Jane [41:03] Street or Saskuana or Citadel like they [41:07] don't give a what the news is. So [41:09] that that that mechanical thing that [41:11] you're describing, that rotation, [41:13] >> we just look at headlines and say, "Oh, [41:15] that's why this is happening." But it's [41:17] not it's not that way. It's machines [41:19] >> with machines and every once in a while [41:22] there'll be like a Monaesque moment [41:24] where the news actually is the thing [41:27] that the traders are reacting to. I [41:29] think a lot of intraday trading, yeah, [41:31] >> it's it's senseless. It's mindless. [41:33] >> Intraday for sure. I do think look [41:35] there's there's news there's economic [41:38] data that gets released it creates a bit [41:39] of a flutter something moves on it and [41:42] then everything else we're talking about [41:44] sort of like reacts [41:46] >> counter moves [41:47] >> against it [41:48] >> I feel like this year more than any in [41:51] recent memory John chart on please it [41:52] does feel like it's basket trading [41:54] >> where it's like so predictable that one [41:56] thing's going to happen and one thing [41:57] will get taken up or down by it to the [41:58] point where bespoke said we haven't seen [42:01] an all or nothing day when the advance [42:03] when basically every stock went up. [42:05] Yeah. Or every stock went down. [42:07] >> We haven't had that since December 31st, [42:10] 2025. That's the longest streak. Yeah. [42:12] >> Since 2001. Now, a huge part of this is [42:16] March and the energy stocks not being [42:18] all or nothing. So, that sort of [42:19] distorts us a little bit. But, it's also [42:21] been like AI is going to kill [42:22] everything. Oh AI is actually not [42:23] what we thought it was. So, it's the AI [42:25] semi uh the AI software stuff. It's just [42:27] been a very interesting year. [42:29] >> It has. Um so there are all these offset [42:31] trades and the other piece of it is you [42:34] mentioned energy and you know everybody [42:36] is on this idea of like this this group [42:39] of stocks that act as negative beta [42:40] >> negative beta. Yeah. [42:42] >> So now that's just an outgrowth of this [42:44] current situation. By the way so much of [42:46] this stuff was like oh how many days [42:47] have we had negative breath when the [42:50] index was up and vice versa. That's all [42:52] downstream of the concentration. [42:53] Correct. I mean like that mathematically [42:55] only happened. [42:55] >> Oh this has never happened. Yeah. It was [42:57] it never looked like this. [42:57] >> Exactly. Um, but the negative beta thing [43:00] is really fascinating to me because I [43:01] think it became really consensusy in the [43:03] industry that energy is your diversifier [43:07] because bonds can't be owned at least in [43:09] the way they used to be. [43:10] >> So describe this factor that we're [43:11] talking about. [43:12] >> So it means stocks that have a tendency [43:14] to move in the opposite direction of the [43:16] S&P 500 on a given day or even longer [43:18] than a day and therefore can act as a [43:20] diver. [43:20] >> They used to be utilities that doesn't [43:22] work anymore. Exactly. Those are AI [43:23] trades now. [43:24] >> They're AI trades. a lot of trades are a [43:26] little more rate sensitive than they [43:27] used to be like you know tech hardware [43:29] and all that. Um so I think that's [43:31] definitely part of it. What I want to [43:33] hesitate to to actually [43:36] suggest is um it's not the same as [43:39] saying like the machines are mindless [43:41] and the machines run the market and [43:43] therefore you know it doesn't make any [43:45] sense and it's not connected to [43:46] fundamentals because if there was a [43:47] macro shock if there was something that [43:49] came along that really did change the [43:51] underlying equation [43:52] >> another co every stock would drop [43:54] >> of course. [43:54] >> Yeah. [43:55] the machines in that scenario, the first [43:57] move they make is they turn off, [43:59] >> right? [43:59] >> And then they might trade, [44:00] >> right? [44:01] >> But I've been dealing with this my whole [44:02] career where it's like, you know, HFT [44:04] was a huge thing 15 years ago as if it [44:06] was just like, you know, and I was like, [44:08] yeah, fine. HF if the market makers, you [44:10] know, they were kind of trading these [44:11] little like flow models, flash. [44:15] Exactly. And it's like, oh, you know [44:16] what? Um, they they're like [44:18] >> these models are right like 51% of all [44:20] trades and they're making a sliver. It's [44:22] not like they're, you know, racking up [44:24] the big gains. Um, and it's funny when I [44:27] when I also first got into it, I get [44:29] into the business in '92. It's really [44:31] psychologically still in the in the [44:33] hangover of the 87 crash and like the [44:36] 1990 [44:37] >> real estate crash and the um the LBO [44:40] crash, savings loan, all that stuff. [44:42] Financial uh markets really had it back. [44:45] Um, and so if you remember after the E7 [44:47] crash, they did this forensic thing. [44:48] What caused it? You know, oh, program [44:50] trading. portfolio insurance. So from [44:53] that moment on they mandated every [44:55] single week there was something that [44:56] came out New York Stock Exchange that [44:58] was the program trading activity you [45:00] know report on Thursday after the close [45:03] and I used to look at it every week it [45:04] was in the wires and it would be kind of [45:06] meaningless but it show you like volumes [45:08] each firm executed by index arb strategy [45:10] or other strategies and I was like what [45:13] are we doing here I don't know what to [45:14] do with this information but somebody [45:16] decided that that was the tail that [45:17] wagged the dog once let's make sure it [45:19] doesn't wag it again and so years later [45:22] this is probably mid 2000s I was in with [45:24] a head of equity capital markets at one [45:26] of the big firms and he said yeah he's [45:28] like you know that wasn't really a [45:29] scientific thing program trading it was [45:31] like his definition of you know as me at [45:34] least 20 stocks traded um as part of a [45:38] strategy [45:39] >> it's like I'm working like an order of [45:41] like multiple but it was like open to [45:43] interpretation and he said back in the [45:45] day the stock exchange like the the [45:47] examiners would be like if there's a [45:49] gray area just say it's not a program we [45:51] don't want to make it look like, you [45:53] know, this is all bots doing this stuff. [45:55] And then at some point in the early [45:56] 2000s, it changed and New York Stock [45:58] Exchange is like, "No, no, we want to [45:59] seem high-tech. We want to seem like [46:00] we're, you know, we're up with it." [46:02] >> More program trading. Good. [46:03] >> Yeah. Loaded into program trading. [46:06] >> So, I I sort of see uh flows that way. I [46:09] don't know what to do with it. [46:10] >> Yeah. Exactly. [46:11] >> Is it contrarian? Do I always do I [46:14] >> It's just interesting. Some It's for [46:17] It's for content. [46:18] >> Yeah. But do I need to know at Meil [46:20] Lynch? [46:22] Uh we re I know [46:25] >> look we have a weekly report is what [46:26] you're saying. [46:27] >> So they it's institutions hedge funds [46:29] retail [46:30] >> retail bought the most tech stocks in [46:32] five weeks. [46:34] >> Okay. [46:34] >> Good bad. [laughter] [46:36] >> How about this? That data is probably [46:37] valuable to somebody. [46:38] >> I do think there's a way to actually [46:40] make a look. You guys had Todd S on from [46:42] Strategus. He does good work with ETF [46:45] flows in sectors. has a sentiment as a [46:48] sentiment you create bands that say this [46:50] is normal, this is extreme and then you [46:52] can trade it. Um I will say that um you [46:56] know one thing that has been consistent [46:57] is people now track retail net buying [47:00] obsessively that does that um it's been [47:03] happening especially since the meme [47:05] stock craze and definitely retail is [47:07] much more of a force much more active. [47:09] They push and push they stampede in some [47:11] directions and they're just they buy [47:12] like that's what they mostly do. But [47:14] Scott Ruben over at Citadel, who's this [47:16] flow guy, used to be at Goldman, you [47:18] know, you have retail net selling. It's [47:21] not happened often. Last week of March, [47:23] guess what? The market bottom there. And [47:25] the last week of July, [47:26] >> it's just another way of saying the VIX. [47:27] >> Exactly. Or it's another way of saying [47:29] like stocks were down. [47:30] >> We could arrive at that answer in 50 [47:32] different ways. I could look at RSI at [47:35] 30. I could look at advanced decline [47:37] washed out. Like it's it's all the same. [47:38] My my only take on that is I I kind of [47:41] bristle at the what's happened more [47:44] recently, which is to lionize retail [47:46] traders as actually they're the ones [47:48] that are the smart money because they [47:49] always buy the dip. [47:51] >> They buy the dip until it gets a little [47:52] scary or goes on a few weeks and then [47:53] they sell. [47:54] >> Not in 401ks. That's that proves the [47:56] rule. Those are [47:57] >> But that's different. But that's like [47:58] >> that's the best investing [48:00] >> of course [48:00] >> anywhere in the country. Better than any [48:02] hedge fund. They they will buy [48:05] they they Vanguard talked about how they [48:08] reacted to co. [48:09] >> Yeah. [48:10] >> The answer is they didn't. [48:11] >> I know [48:11] >> they literally bought every every print [48:13] on the way down. [48:14] >> Well, Vanguard will also fire a client [48:16] that trades too much and gets too over [48:17] excited. But that's good. [48:19] >> I'm just, you know, they don't act like [48:21] retail investors, but they are. It's the [48:23] same people. [48:23] >> Here's another great example of just [48:25] it's it's great stuff to talk about. Is [48:26] it actionable? I don't know. But what [48:28] we're looking at John Arthur's uh shared [48:29] this chart DRAM ETF total assets. So, [48:33] he's comparing it with the socks index [48:34] and we know semiconductors got the [48:35] kicked out of them during the [48:37] situational unwind and then individual [48:39] investors didn't care. They just kept [48:41] piling in. Yeah. And Michael, you're [48:42] right. Um I think there's maybe too much [48:45] of them. They're now the smart money. [48:47] It's a reflection of the market [48:48] environment that we're in. So, it's not [48:49] to disparage them [48:50] >> 100%. [48:50] >> Credit to them. They've had the balls to [48:52] continue to pile in. [48:53] >> It's and it's a reflection of the market [48:54] that we're in. [48:55] >> Yeah. There's no doubt about it. And and [48:56] they have the tools now. And um yeah, I [48:59] also think there's a there's a a thing [49:00] with retail is they don't crystallize [49:03] losses. [49:04] >> What do you mean? [49:05] >> If if something's down, they don't [49:07] they're not quick to sell it. It's like [49:09] that'll come back. And so therefore, [49:10] they always seem to be the next move is [49:12] always to buy or it's more often to buy [49:14] than not. I know that this isn't isn't [49:15] borne out by like when Interactive [49:17] Brokers says what their people are [49:18] doing. They're quasi hedge funds. [49:19] They're kind of semi-professional [49:21] traders a lot of that uh that flow. But [49:23] I do Yeah, I totally agree with that. I [49:25] mean, now you have [49:26] >> they don't sell unless it's a margin [49:27] call. [49:27] >> If I don't get obsessed with with like [49:30] zero dated maturity options and all that [49:32] stuff, it's kind of just noise. Um, and [49:35] if anything, it creates a little more of [49:37] a mean reversion effect throughout the [49:38] day. It's kind of like it kind of keeps [49:41] things in a range over the course of a [49:42] day because it's kind of like the public [49:44] buys the calls in the morning, the [49:45] street sells them to them, and then by [49:47] the end of the day, you have all this [49:48] decay in the options values, and then [49:50] they buy them. [49:50] >> But it's so true. This is push and pull [49:52] because Citadel Millennium, they're down [49:55] 5%. Sell, don't care, sell. Yes. [49:57] >> And the retail's like, great, we're sold [50:00] to us. Thank you. [50:01] >> Totally. And I I think there's so much [50:03] of that going on. Like I I've been [50:05] working on this thing where like the [50:06] options income funds are like private [50:09] social security because it's like the [50:11] young people, they they pay for juice [50:14] call premium to play the upside in these [50:16] stocks. And you have all these people [50:17] who just want income out of options and [50:19] they're just like, "Let's sell the juice [50:21] calls, covered calls." Oh, I never [50:23] thought about that. Yeah, of course. [50:24] >> And you know, it's kind of, you know, [50:26] it's it's sort of overstated that it's [50:27] actually like, you know, funding the [50:29] retirements of people, but I know people [50:30] own those. [50:31] >> No, you're right. And look at the most [50:32] popular ETFs this year, a lot like a lot [50:35] of the names in in that on the in the [50:38] winner circle are selling calls. So NEO [50:41] NEO is an innovator. The ones that [50:43] Goldman just bought, both of them big [50:44] time options ETFs. [50:46] >> I find it somewhat ironic. [50:47] >> Transfer from traders to to investors. [50:50] >> I find it slightly ironic because I [50:51] understood why that stuff became popular [50:53] at 0% interest rates. You know, money [50:56] markets weren't yielding anything, but I [50:58] guess people just like it. [50:59] >> I So Ben and I interviewed Bruce Bond in [51:01] 2018 or 19, and I immediately said, [51:05] >> "Holy this could be a huge [51:06] category." And the reason why I was so [51:08] confident is because there's there was [51:10] never there's never been anything for [51:12] the everyday investor where they can [51:14] guarantee their range of outcomes. Yeah. [51:16] >> With a 6040 portfolio. All right. You're [51:18] shrinking the range a little bit, but [51:20] then 22 comes along like you don't [51:22] Right. So it's offset a little bit. But [51:24] when you could say [51:26] >> uh -10 up to + 12. Nah, that doesn't [51:29] work for me. Okay, fine. Five plus up to [51:32] plus 7. Oh, that's that's more my [51:34] flavor. There's never been anything like [51:35] that with with the stock market where [51:37] you can say this is the risk I want. [51:39] >> I totally agree and you know there's a [51:40] reason that annuities have been around [51:42] forever. People psychologically some [51:45] people just want the certainty of [51:47] outcome. [51:48] >> You put this in the doc uh I guess about [51:50] the current bull market. Prudent to [51:52] assume that the valuation peak is in [51:55] then be open to pleasant surprise if [51:58] not. What do you mean? [51:59] >> Yeah. What's your problem? So at least [52:01] on a PE basis. [52:02] >> Why are you trying to confuse everyone? [52:04] >> I know we get to 23 times uh last [52:06] October forward. You know, you were [52:08] there in the pandemic, but that was [52:09] depressed earnings. So you're on 23 [52:11] times kind of peak earnings at the time. [52:13] And since then, it's compressed, right? [52:16] Earnings have grown a lot faster than [52:18] stocks have gone up, even though stocks [52:19] are up since that. And um I just feel [52:21] like a few things are mitigating the uh [52:25] the rebuilding of that PE premium. One [52:28] of them is, and I know you guys talk [52:30] about this, the whole like, well, we [52:32] don't have free cash flow anymore, [52:34] right? This is all kind of like capex [52:35] heavy capital intensive type drivers of [52:38] the growth right now. Actually, on a [52:40] forward price to free cash flow basis, [52:42] we're at 30 in the S&P. [52:44] >> Don't love that. [52:45] >> And so, [52:46] >> but it's voluntary. They're doing it on [52:47] purpose. That's the thing. Yes, I agree. [52:48] >> And everyone knows it's not against [52:50] their will. [52:50] >> I totally agree with that. And that's [52:52] the fascinating element to me which is [52:55] >> it's funny because you know you have [52:56] like um Google does their earnings call [52:58] and like you know they get out there and [53:01] they're like no it's early trust me it's [53:03] still early and I'm not sure investors [53:05] want to still hear it's early like they [53:07] want to get to a [53:08] >> destination but the people running these [53:09] companies they're they grew up [53:12] worshiping Jeff Bezos [53:13] >> totally [53:13] >> that's what they studied [53:14] >> 100% [53:15] >> when they when they were in business [53:16] school or when they were at Stanford [53:18] that's what they studied the shareholder [53:20] letter Amazon [53:21] >> from S1 is like in their crib. [53:23] >> That's right. So they're they're these [53:25] aren't Amazon cover bands. [53:27] >> Totally. [53:27] >> And Wall Street's not stupid. They get [53:30] it. Yeah. [53:30] >> Like, oh, you're doing this on purpose. [53:32] Okay, in that case, we can live with it. [53:33] I mean, to a point. [53:34] >> Well, look, and I also totally agree [53:36] with the other bull case of these [53:38] companies are responding to genuine [53:39] demand signals. It's not like totally [53:42] speculative that we're going to build it [53:44] and maybe somebody's going to use this [53:45] stuff. Um, I still think it's a little [53:47] bit of a threat. Like capitalism [53:49] shouldn't work that everyone all at once [53:51] decides to spend all the free cash flow [53:53] on the same thing to build the same [53:55] thing and everybody gets a great return [53:57] off of it. But maybe that's not today. [53:58] >> This is what Katraski is saying. He's [54:00] saying, I get the fundamental [54:02] uh evolutionary technology. Yeah, [54:05] >> we're not spending because we're dumb [54:07] asses. Exactly. But the ROI is just not [54:09] going to be there. [54:10] >> And maybe that's okay. Like I don't [54:11] know. I, you know, the longer I do this, [54:13] like the more I I sort of doubt that [54:15] there are any of these ironclad rules of [54:17] like what creates value and what does [54:18] stocks need to like I was always pushing [54:20] back against the oh buybacks jack up the [54:23] market. [54:24] >> Yeah. Well, we don't have any anymore. [54:25] So, [54:25] >> we don't have any. Well, you have a [54:26] trillion dollars worth, but it's not as [54:28] much relative to the size of the market [54:29] cap. Um, but it just didn't really hold [54:32] up. Like, it was just it didn't goose [54:35] the stocks that were doing the biggest [54:36] buybacks. In certain circumstances, they [54:38] work. I do think that the economy runs [54:40] on stockbased compensation to a degree [54:42] most people don't appreciate. And so you [54:44] have these huge companies that their [54:45] buybacks are effectively soaking up the [54:48] equity compensation that they give to [54:49] their employees. And that's great [54:51] because those people have the money. [54:52] >> Who's more disingenuous generally, bulls [54:55] or bears? [54:58] >> Um, you know what I mean by that? [55:00] >> I do. I do. Um, I would say [55:03] >> because I think it's a landslide. I [55:04] think bears are probably more [55:06] opportunistic in terms of the [55:09] information that they [55:11] >> will [55:11] >> they will change the argument but [55:14] maintain the stance [55:15] >> right [55:15] >> almost no matter what. Yeah. [55:17] >> Here's why [55:17] >> I don't think bulls do that. [55:19] >> Here's why you're right. Bulls will [55:22] always concede that there is a bearish [55:24] case out there almost universally. [55:25] They're like, "Yeah, we know like I I [55:27] understand the risk. I'm not naive. [55:28] Bears never said that there's upside [55:30] risk. It's just they just keep digging [55:32] and digging and digging and then [55:33] changing the story. [55:34] >> So, here's why I'm asking you that [55:36] question because I I know you I know you [55:38] respect the Bulls and the Bears at all [55:40] times. And that's that's I think why you [55:45] you have almost universal approval on [55:47] Wall Street. People say like people [55:51] >> you have credibility. Let's let's let's [55:53] put it that way. You have credibility on [55:55] both sides. It's not that you're like [55:58] catering to the Bulls this week and then [55:59] the Bears. You just you you recognize [56:02] the risks. You write about them. You [56:03] don't pretend they don't exist, but [56:05] you're also not one of them just for [56:07] clicks. [56:08] >> You're not going to say the scariest [56:09] you can in the headline to get [56:11] people to click the way I do on YouTube. [56:13] Okay. Wait a minute. [56:14] >> Right. [56:14] >> So, but here's here's my point. [56:17] >> Two years ago, 2024, we're in a bull [56:20] market. Extremely concentrated. [56:22] >> Yeah. [56:23] >> Definitely led by MAG 7. can't argue it. [56:26] Um, and the bears said, "This is bad. [56:29] Here's what happens to concentration. [56:31] Look what happened at the end of the 50s [56:33] n uh 1960 this time, that time." [56:36] >> And then all of a sudden, the market [56:38] broadened out over like two years later [56:40] to the point where we had multiple mag [56:43] seven names in 20% draw downs and the [56:44] S&P was at all time highs, right? [56:46] >> Did one of those people come along and [56:48] say, [56:49] >> "Okay, I was bearish about that thing. [56:52] That thing has been cured, [56:53] >> right? Therefore, [laughter] [56:55] therefore, I'm not bearish anymore. No, [56:58] they move on to the national debt. [57:00] >> No, it's true. [57:00] >> That's the dis the disingenuous thing [57:02] that I'm referring to. [57:03] >> I agree with that. And look, I I start [57:05] with the premise as everybody should [57:07] that market goes up 70% of all years. It [57:10] goes up 55% of all days. You're fighting [57:12] the tide if you really think that you're [57:15] going to be down a lot and on a [57:16] sustained basis. [57:16] >> It's a conspiracy. [57:18] >> Now, yeah, I mean, every incentive moves [57:19] in that direction. Why wouldn't it, you [57:21] know? Um, [57:23] >> that being said, I do find myself just [57:25] like temperamentally not always wanting [57:28] to play along. Like in this recent [57:30] period where, and it's funny because I I [57:33] sit there in front of the wires, in [57:34] front of the screens, listening to to [57:36] CNBC and all the guests all day and you [57:39] start to hear the mantra, you start to [57:41] hear the echoes. Everyone starts to [57:43] sound. And once the market came back [57:45] after the July selloff, it was like [57:46] >> earnings, earnings are my north star. [57:49] earnings are earnings are the lifeblood [57:50] of a bull market and everyone is very [57:52] self- congratulatory about having stayed [57:54] the course because it feels virtuous and [57:57] it was all fundamentals all along and [57:59] it's a foolish game to to to bet against [58:01] it. [58:01] >> I told you not to panic [58:02] >> and and that's fine but I I start to [58:05] bristle at that a little bit not because [58:07] I think they're wrong but because you [58:10] know I wrote about it this this week in [58:11] my column where I said you know in [58:13] Madmen Dr. Fay Miller says to to Don [58:16] Draper, you know, you only like the [58:18] beginnings of things. [58:20] >> And I only like the beginnings of [58:21] things. I like when a when a rally feels [58:23] like it's in the face of challenges or [58:26] it's it's not just extending it on [58:29] everyone earnings were amazing. You're [58:31] like, "Yeah, I know." [58:32] >> But what I don't do anymore is say [58:35] that's why it's over because it probably [58:37] isn't over. [58:38] >> I still feel like there is a wall of [58:39] worry. There is a lot of disbelief up [58:42] there. But I I would be moderately [58:44] surprised if a year from now we're [58:46] having the same conversations with the [58:48] continued negative free cash flow. Yeah. [58:50] >> The continued like it's coming, it's [58:52] coming, it's going to pay off. I would [58:54] be surprised if the market is giving is [58:56] cool with that a year from now. [58:57] >> Yeah, I think that's right. Or at least [58:58] if there's not some kind of intervening [59:02] jolt, some kind of gut check, some kind [59:04] of uh because honestly, I sometimes feel [59:07] like that's what the market needs. It's [59:08] like if it goes along on the same [59:10] storyline for a while, it needs a scare. [59:12] And a scare and relief cycle is often [59:15] what can kind of cleanse. [59:16] >> You need that. I love it. So, we had [59:17] that. We had situational awareness. We [59:19] had a leverage unwind in Korea and then [59:21] the earnings bailed us out, right? [59:23] >> What else would you want to be bailed [59:24] out? [59:24] >> No, I don't think I don't think I don't [59:25] think that that's that's wrong. I think [59:27] that the extraordinary part of it was [59:28] you never had more than 3% pullback in [59:30] the S&P 500. So, you had the [59:32] choreography work so well. [59:34] >> Yeah. [59:34] >> And and you know, you mentioned the [59:36] broadening. I'm I'm like known for not [59:39] necessarily thinking that a broader [59:42] market is by definition a more stable or [59:44] rewarding market. [59:45] >> Mobes empirically proved that. He said [59:47] moes has a piece with Kylie. He said [59:48] actually [59:49] >> bull markets are where concentration [59:51] happens. Be careful what beware what you [59:52] wish for. [59:53] >> I agree with that. But the but they can [59:56] be like these interludes these phases [59:58] where when the big stuff is correcting [60:00] it's good if it if if if the rest of the [60:03] market kind of you know rises to take up [60:05] the slack. I mean, that's what's [60:07] happened. [60:07] >> The other thing though that I think has [60:09] been a hallmark of the last 15 years, [60:12] everyone assumes everything's going to [60:14] be a catchdown. [60:15] >> Yeah. [60:16] >> So, they assume anytime there's a [60:17] negative divergence, small caps are [60:19] lagging. [60:19] >> Yeah. [60:20] >> Or uh value stocks are uh in a 20% draw [60:23] down while growth is at all time highs. [60:25] They assume the cure is going to be the [60:28] whole market succumbs. [60:30] >> Sure. [60:30] >> And I know that does happen, but almost [60:32] never. What actually happens is it's a [60:36] catch up. [60:36] >> Yeah. [60:37] >> And that's got to drive the bears [60:38] absolutely insane [60:40] >> probably. [60:40] >> If they even are aware of it. [60:42] >> Yeah, probably. So, I mean, look, the [60:43] flip side of that is um you know, this [60:46] this chart that I just I I'm not going [60:48] to expect anyone to see it, but it it [60:50] basically shows like [60:51] >> Did you hand draw that? That looks like [60:52] [laughter] a that looks like a model [60:55] from somebody who had handdrawn it. [60:56] >> Okay. [60:57] >> Um percentage of S&P stocks above 70% [61:00] above the 200 average exceeding 70%. So [61:02] 70% of all stocks above the 200 day and [61:05] these are all periods when you had a 15 [61:07] to 20% drop from that level. Like in [61:10] other words, it's not like a get out of [61:12] jail free card. Oh, it's a broad. [61:13] >> So basically, is this as good as it [61:15] gets? Which brings me to this. [61:17] >> Was such a awareness a tremor the same [61:20] way that LTCM was, the same way that the [61:22] Quantic was? Like are we a year, two [61:25] years away? [61:26] >> Is it the canary in the coal mine? [61:29] >> I don't know how to answer it. I don't [61:30] think it has to be. Like for example, I [61:32] don't think long-term capital was a [61:34] tremor that somehow you could draw a [61:37] direct direct line from there to March. [61:39] >> Had nothing to do with it. You're right. [61:41] In fact, if anything, the only thing you [61:43] could say is it creates this huge global [61:46] tightening financial conditions, [61:49] recession scare, Fed has to cut, [61:52] gun the economy into 99, and then you [61:55] create the excesses. So, in that way, [61:56] maybe, but it wasn't the long-term [61:58] capital, the the the imbalances [62:00] themselves. [62:00] >> Where are you on this? People say, and [62:02] I'm sympathetic to this. [62:03] >> This is a service-based economy. There [62:05] is so much money. Something seriously [62:07] bad needs to happen for for for uh that [62:09] train to be slowed down. [62:11] >> Sure. I mean, I think that adds a [62:13] stability to the macro. I think so many [62:14] of those like rules of thumb like we [62:16] were talking about like, oh, market 15 [62:18] times earnings is the long-term, you [62:20] know, multiple. Um, [62:22] >> not now it's not, [62:23] >> etc. No, I know. I'm saying that when I [62:25] came up that's where it was. Well, [62:27] that's because you used to be like [62:28] trapped in this manufacturing business [62:30] cycle. You recessions every three years. [62:32] >> Margins used to mean revert, [62:33] >> right? [62:34] >> And um now that doesn't mean I don't [62:36] think people are over earning right now [62:37] because I [62:38] >> John, we're going to title the show [62:39] earnings can never fall. [laughter] [62:42] Dash Michael Sani. [62:44] >> No, I mean [62:45] >> with his Twitter account in the [62:46] headline. Plus, you know, it's there's [62:48] all I mean, you want to talk about bears [62:49] like there used to be a big thing of [62:51] like I can't believe that people bless [62:53] operating earnings as the standard. [62:55] >> Yeah. [62:56] >> You think about that like it used to be [62:57] gap earnings. What What about this one? [63:00] This the current crop of CEOs and CFOs [63:06] might be the most battle tested [63:09] uh group of executives collectively ever [63:13] to run the S&P 500's companies. Look at [63:16] what the last 10 years has been like for [63:19] these people. And you could start 10 [63:21] years ago. You start five years ago. But [63:23] let's just say Trump won. [63:25] >> Yeah. [63:25] >> Trump term one. Um literally being [63:28] screamed at on Twitter. [63:30] >> Yeah. [63:31] >> By the president threatened. Uh roll [63:33] right into the original tariff uh and [63:37] all the issues with soybeans and [63:39] whatever we were dealing with in 2018 [63:41] manufacturing blah blah blah. roll right [63:43] into COVID. Uh January 6th um gay pride [63:49] issues at the retailers like how dare [63:51] you put that display up, Disney having [63:53] to fight social culture war stuff um in [63:56] the parks, blah blah blah blah blah blah [63:57] blah. Right. Right into like the next [63:59] Trump term, the new tariffs, liberation [64:02] day, the Iran war, uh record high [64:05] inflation, [64:07] work from home, like these people [64:09] running these companies. And I know some [64:11] there's been some turnover, but by and [64:13] large, [64:14] >> can you think of another era like [64:16] without going to World War II? [64:18] >> Yeah. [64:18] >> Of people running companies through this [64:21] that never ends and and [64:23] seems to get crazier with every passing [64:26] year. Like these are ninjas at this [64:28] point. [64:28] >> Yeah. I mean, I I think you can [64:30] definitely credit the the kind of [64:32] institutional [64:32] >> profit margins are at 15%. Yeah. [64:35] >> Take everything I just listed and profit [64:37] margins are at 15%. revenue growth this [64:39] quarter was plus4. That's not [64:41] >> so much of that is is I had to say so [64:43] much of it is compositional, right? It's [64:45] like the kinds of companies that are [64:46] that big in the index are [64:48] >> magiculated. Starbucks and they can't [64:50] get out of their own way and they're not [64:51] run by UPS's earnings are going to be [64:52] what they were like three years ago and [64:54] Nike's where they were 15 years ago and [64:57] you know I was just looking at thermal [64:59] fisher great growth company over the [65:00] years it's been flattish earnings for a [65:02] couple years but I agree with you in [65:03] general. I mean, you probably have to go [65:04] back to like maybe 6872 like [65:08] hyperinflation, oil crisis, Nixon, [65:10] Vietnam. But, you know, look, I think it [65:13] always seems like we've just been [65:15] through the worst or the most or the [65:17] most extreme. [65:18] >> Um, I always go back to uh Byron Ween, [65:21] the the Morgan Stanley and later [65:22] Blackstone strategist, [65:23] >> one of the greats. [65:24] >> He was he one of the greats? [65:26] >> Absolutely. Sweet guy as well. Um I I [65:29] remember hearing him speak at this event [65:31] and he said that he came into the [65:34] business in like 1958 or something like [65:36] that, right? Kim's out of business [65:37] school, get a job at a asset manager and [65:40] he says it was at exactly the moment [65:42] when [65:43] stock dividend yields crossed below [65:46] treasury yields [65:47] >> which was supposed to be a market top. [65:49] >> Supposed to be a market top. It never [65:50] happened sustainably before that. It was [65:52] supposed to mean you were massively [65:53] overvalued market and then it stayed [65:55] there for 50 years until the global [65:56] financial crisis. Right? And he said he [65:58] saw what it did to the people at the [66:01] firm, the older guys, [66:02] >> broke their brains. [66:03] >> Yeah. [66:04] >> He said they couldn't adapt [66:05] >> because they set their watch by it. Any [66:07] anytime the dividend anytime the [66:09] dividend on the stock market goes below [66:10] the treasury, [66:12] >> that means stocks are too expensive. [66:13] Sell. [66:14] >> Yeah. Sell stocks [66:15] >> and then the market quadruples [66:17] >> even more. And so he said it it kind of [66:19] taught him he said he used to have a [66:21] funny way of saying like you know these [66:22] guys like they obviously are wrong for a [66:25] while and they kind of lose some of [66:26] their clients and you know he said [66:28] eventually they go from a corner office [66:30] to an interior office and all they got [66:32] to do is call their college roommate for [66:33] new money you know whatever and um and [66:36] he I think that that he said that it fed [66:38] into his uh idea to do the 10 surprises [66:42] list every year because that was a big [66:43] surprise. [66:44] >> Let me test myself to figure out blind [66:45] spots and where things might go [66:47] different. Okay. So, you like Ween, you [66:49] liked Barton Bigs. [66:50] >> Sure. [66:50] >> What would Barton Bigs or Byron Ween be [66:52] saying right now? [sighs and gasps] [66:54] >> I think they would, for one thing, be [66:56] celebrating [66:58] the long-term [67:01] economic [67:03] and sort of societal benefits that we're [67:06] probably building with AI. Like, [67:07] whatever you think about how the equity [67:08] market's going to metabolize all this [67:10] and whether it's overdone in the short [67:12] term, if all this gets built [67:14] >> the way that like it just increases [67:16] capacity. so much whether it means that [67:19] you know we accelerate the renewable [67:21] energy thing like it's going to create [67:23] uh you know I think that they would they [67:25] would embrace that uh while also being [67:28] nervous about I think pockets of you [67:30] know unthinking excess I don't know how [67:32] they would think about you know three [67:34] times leveraged single stock ETFs you [67:36] know what I mean they probably wouldn't [67:37] love them what [67:38] >> what's this money game anecdote from [67:40] Adam Smith let's let's let's do this [67:43] >> yes so Adam you want to read it Um, [67:47] sure. Let me read it. Um, Adam Smith, of [67:49] course, was a pen name. I believe his [67:50] name was [67:51] >> George Goodman. [67:52] >> Jerry Goodman, maybe. [67:53] >> Okay. [67:53] >> Uh, you might be right. [67:54] >> So, there's the money game in 1968. [67:56] >> And this was kind of a real like slice [67:59] of life of Wall Street at that time. It [68:01] was, of course, a real booming bull [68:03] market. Um, and so he's kind of talking [68:05] about how the younger people in the [68:07] business were so excited about mostly [68:09] the mainframe computer uh craze and how [68:12] it was printing money. So this is in the [68:14] voice of one of the younger people [68:15] saying computer leasing stock sir he [68:17] said like a cadet quiz by an [68:19] upperassman. Uh the need for computers [68:22] is practically infinite uh infinite said [68:24] Billy the kid. Leasing has proved the [68:26] only way to sell them and computer [68:27] companies themselves do not have the [68:29] capital. Therefore earnings will be up [68:30] 100% this year will double next year. [68:32] We'll double again the year after that. [68:33] The surface has barely been scratched. [68:35] The rise has scarcely begun. So [68:37] >> that's cor. [68:38] >> Yeah exactly. I mean that's obviously [68:40] why I chose it because you know uh hey [68:42] but you know what the mainframe [68:44] revolution was real [laughter] [68:45] >> and it's just about like I mean so [68:48] here's another premise I here's another [68:50] long-standing principle of mine and [68:53] everything ends in a boring place. [68:55] whatever company you're excited about [68:57] right now, if everything goes [68:58] beautifully, like it ends up being kind [69:01] of a utility or a mature company or some [69:05] parts of the guts and operations of the [69:07] economy and it slows down. It's like [69:09] eBay was a moonshot exciting stock at [69:12] one point. And you know, I even think [69:14] this about things like, oh, Circle comes [69:16] public, it's a stable coin company. It's [69:17] like, congrats. Uh, you know, you're a [69:20] custodian. Uh, you you earn a spread off [69:22] tea bills. uh Bank of New York Melon uh [69:24] has trillions [clears throat] of [69:25] dollars, trades at 12 times earnings, [69:27] you know. So, I do think that you have [69:28] to be aware of that and you kind of ride [69:30] the exciting phase and then figure out [69:32] how it [69:33] >> how it decelerates off of that. [69:34] >> I just I I think that's true except if [69:36] Elon is involved, [69:38] >> right? [69:38] >> Because he will cannibalize his own [69:40] company. He will reinvent. He just shut [69:43] down. No more Model S. [69:44] >> Yeah. [69:44] >> No more I forget which other. No more [69:47] Model X. We're going to make robots [69:49] instead. Like, [69:49] >> nobody has the license to do that. I [69:51] think he's the exception, but generally [69:53] I I agree with you. And actually, one of [69:55] the one of the most fun parts of the [69:57] rally this year and late last year, [70:00] >> how many throwback stocks have become [70:03] their former selves? [70:04] >> Okay. [70:04] >> And I'm thinking about Sienna and Dell [70:07] and Cisco. Totally. [70:08] >> And I love that so much because those [70:11] were the momentum stocks that I grew up [70:13] with. [70:14] >> Y [70:14] >> and they all became moment whichever [70:16] ones that left [70:17] >> all became momentum stocking. Yeah, [70:19] exactly. Can I can I [70:20] >> I was looking for MFNX. I couldn't find [70:22] it. I said I would buy that if that was [70:24] still around. [70:24] >> Let me read something another thing from [70:26] the money game that always stuck with [70:27] me. And I think this is so important for [70:29] individual investors to heed this [70:32] statement because it's so true, [70:35] especially when momentum breaks. All [70:36] right, here we go. A stock is for all [70:38] again 1968. A stock is for all practical [70:41] purposes a piece of paper that sits in a [70:43] bank vault. Most likely you will never [70:45] see it. It may or may not have an [70:47] intrinsic value. what it is worth on any [70:49] given day depends on the confluence of [70:51] buyers and sellers that day. The most [70:53] important thing to realize is [70:54] simplistic. The stock doesn't know you [70:56] own it. All those marvelous things or [70:59] those terrible things that you feel [71:00] about a stock or a list of stocks or an [71:02] amount of money represented by a list of [71:04] stocks, all of these things are [71:05] unrescrocated by the stock or group of [71:07] stocks. You can be in love if you want [71:09] to, but that piece of paper doesn't love [71:11] you. And unrecrocated love can turn into [71:14] massochism, narcissism, or even worse, [71:17] market losses. and unrescrocated hate. [71:19] How good is that? [71:20] >> That's beautiful. Yeah. And of course [71:21] the coral area as people always say is [71:23] like it doesn't know what price you paid [71:25] for. Like if you think there's something [71:27] magic about your cost basis that it has [71:29] to gravitate back there or anything like [71:31] that or I still do that. [71:33] >> No, of course it's the natural way. But [71:35] uh by the way, one quick thing. [71:37] >> I don't revenge trade though. One of my [71:38] one of my one of my favorite [71:40] observations right now is if you look at [71:42] Tesla relative to the S&P 500 [71:45] >> in its history, go back however you how [71:47] far you want. It's outperform the SP by [71:49] like what 3600%. It's massive. Every [71:53] every basis point of the outperformance [71:55] happened in calendar year 2020. [71:57] >> It went up 10x. [71:58] >> Wow. [71:59] >> Right. So it's like [72:01] >> but it held it. I'm not saying it's like [72:03] a disaster since then. It basically has [72:04] mostly held it. Um, but it's just [72:07] fascinating that it's just like so many [72:09] things hit perfectly well for that [72:11] moment [72:11] >> and people love their Tesla. [72:12] >> So, so one of the other features of this [72:14] bull market is I find myself on a weekly [72:17] basis, maybe daily, asking myself out [72:20] loud, am I dumb or are they dumb? And I [72:24] don't know the answer, but I want to run [72:25] this one by you [72:27] >> just as a not that this particular story [72:29] is that important. Open router. It's [72:33] basically a harness. So it's like you [72:36] used to go to Google as a search engine [72:38] and it indexed all the links. So you [72:40] went to Google first because it would [72:41] take you to where you eventually wanted [72:43] to go. Okay. So open router is the same. [72:45] You have a project you want to use for [72:47] AI, you go to open router. Um you'll [72:50] select from hundreds of different LLMs [72:53] and you'll pick one or it'll be a [72:55] combination of multiple. It's a great [72:57] idea. Yeah. [72:57] >> It's sort of like the Google for the AI [73:00] age except it's tiny. Um, but it's so so [73:03] they were calling it like the har like [73:05] the AI harness rather than going [73:07] directly to Claude or directly to Okay, [73:09] fine. Um, [73:11] this this is the news on open router [73:14] this week. [73:16] Stripe is going to buy this company [73:19] which is quote this is the information [73:21] like a retail store that sells access to [73:23] hundreds of AI models. Um, most it it [73:27] they say including anthropic, but I [73:29] would assume it's a lot of anthropic. [73:31] Uh, they're going to buy this company [73:34] that just had revenue triple to 13 [73:37] million with an M. [73:39] >> 13 million. Stripe is going to pay 7 to [73:42] 7.5 billion. [73:44] The valuation on Open Router in May, [73:48] which was 3 months ago, was 1.3 billion. [73:52] So, in 3 months, and I don't know what [73:54] the user growth, all I know is it's 13 [73:57] million in revenue, valued at 1.3 [73:59] billion 3 months ago. It's going to get [74:01] acquired for 72 billion. Am I an [74:04] >> I mean, [74:04] >> or like, am I dumb? Are they dumb? I [74:07] don't know. [74:07] >> Do the numbers really mean much? I don't [74:09] know how they're paying for this. [74:10] >> It might be a brilliant Who am I? Like, [74:12] I don't know. [74:13] >> Remember when Zuckerberg bought WhatsApp [74:14] for 11 billion and we were like, what? [74:16] You could go back to Google with [74:17] YouTube. Even [74:18] >> Instagram [74:19] 11 people a billion dollars. Like who [74:22] knows? [74:22] >> I mean people freaked out that Apple [74:24] paid $3 billion for beats and they like [74:26] you don't even notice that. [74:27] >> Do you find yourself asking that? [74:28] >> Absolutely 100%. And and to me if [74:31] nothing else it's a measure of you know [74:32] the desperation of the buyers to play in [74:34] a certain area or to kind of find [74:36] somebody else. [74:38] >> Skeleton key to the next thing we need [74:39] to do. I did hear somebody just talking [74:41] about open router as as one of the the [74:43] the thing that makes it valuable is is [74:46] it has all this data for like all these [74:49] agents that are flooding into it. So [74:51] like there's a there's a way I'm sure [74:52] you could use it to exploit and map [74:54] other things and have access to other [74:56] information, but I am actively ignorant [74:58] about a lot of the details of what's [75:00] going on right now in in AI and [75:02] everything else. And I know everyone [75:03] tries to pretend that they know [75:05] everything about this kind of wafer and [75:07] what tokens are going to cost down the [75:09] road. I try not to pretend I have a [75:11] show. [75:11] >> Dude, it's impossible. I listen to Ben [75:13] Thompson. Yeah. [75:14] >> Who I I love. I I read his stuff. He was [75:15] on with Patrick for an hour and 15 [75:17] minutes. Listen to the whole thing. I [75:19] can't tell you a word of what he said. [75:20] Yeah. [75:20] >> I have no idea. I mean, I'm a late buy. [75:23] >> Yeah. [75:24] >> Um but this is another thing that I [75:26] think is going to stop. And we we were [75:28] talking about this last week. [75:30] >> There's such an intense focus by [75:32] traders. people that if they tripped [75:34] over uh a wafer, couldn't tell you what [75:37] it's used for, they think it's a waffle [75:39] iron. [75:39] >> Yeah. [75:40] >> Now all of a sudden they're talking [75:42] about like they're talking about like [75:44] chip yields and the that's not going to [75:46] persist for more than I I I would guess [75:48] the next correction, [75:50] >> right? [75:50] >> That'll stop. But right now, I've never [75:53] heard so many Wall Street money guys [75:56] talk more about the intricacies of of [75:59] manufacturing a memory chip, right? I [76:01] don't I can't remember a time where [76:04] people were this comfortable spouting [76:06] terms they have no idea what it even [76:08] means. [76:08] >> Yeah. I was at a dinner where there was [76:09] a lot of that talk going around small [76:11] group and one but one guy too was [76:13] >> like Parker dinner cuz I can picture it. [76:15] All right. Go on. [76:16] >> Every you know every single thing about [76:18] like the the kind of repurposing of jet [76:20] engines into you know gas turbine [76:22] generators. [76:23] >> Oh, sure. Sure. Sure. [76:24] >> And I mean look I he he obviously did [76:26] the work. He's up huge in the stock he [76:28] was talking about. Like it's not that it [76:30] was for nothing, but I was like, you [76:32] know, the other probably two years ago, [76:34] he's trying to figure out like Lululemon [76:36] comps, you know? [76:37] >> That's my I think that's my point. And [76:39] it's not as though I'm not guilty of it. [76:40] Everyone's not guilty. We're all to some [76:43] extent now forced to learn this new [76:44] language because this is what the stocks [76:47] that we care about are trading on. [76:49] >> But I'm just amazed at how far it's [76:51] gone. And now they're launching ETFs [76:54] that will build a basket of the [76:56] companies that are in a specific AI [76:59] company's ecosystem. [77:01] >> Yeah. [77:01] >> And I just I have no problem with it and [77:03] I bet there will be people trading it [77:04] successfully. My I guess my point was [77:07] that's got to be toward the end is one [77:10] and two people are going to lose [77:12] interest in that real fast cuz I [77:13] remember when they were taking apart the [77:15] iPhone. [77:16] >> Yeah. Right. [77:16] >> And building baskets of whatever [77:18] components. How long did that go on? For [77:20] a year. It's true. [77:21] >> Okay. [77:22] >> Or like the LAR companies and the EVs or [77:24] whatever. Yeah. [77:25] >> Right. So, um that's that's toppy [77:28] behavior. I think [77:29] >> it feels like it I mean it also is I [77:31] mean to your point about the old kind of [77:34] guard of companies that are coming back. [77:35] I mean they obviously have a durable [77:39] knowhow and they are going to be in the [77:41] middle of whatever these trends are and [77:43] the microns and you know the Western [77:45] Digital all that stuff. Great. Let's see [77:47] have this renaissance. But never forget [77:49] Western Digital spun off SanDisk a year [77:52] and a half ago. [77:52] >> Nobody wanted because you couldn't care [77:54] about it. [77:54] >> So crazy. [77:55] >> It's so crazy. [77:56] >> And so and Sandis would up how many [77:58] thousands of percent. [77:58] >> I think their shareholders demanded that [78:00] they deal [78:03] an unbelievable [78:04] >> right. So so no so even the people in [78:06] the business aren't quite sure what the [78:08] next move is going to be. [78:09] >> Um did you have fun on the show today? [78:10] >> I loved it. [78:11] >> We had so much fun. So we're going to do [78:13] a quick intermission. [78:15] Um, [78:16] >> we'll do dinner. [78:17] >> Sure. Of course. [78:18] >> Can we talk? [78:19] >> You need me to cook or what's [78:20] >> So, I want to do two things before I let [78:21] you out of here. I want to do uh [78:24] >> I want you to tell everybody about [78:26] closing bell Overtime. Yeah. [78:28] >> So, you're the you're the anchor. [78:29] >> Co-anchor with Melissa Lee. [78:31] >> Fine. Of course. Love Melissa. So, you [78:33] haven't had your you've been the anchor [78:35] on every show on the network. [78:37] >> Yes. As a fill in. [78:38] >> As a fill in, but you've done Squawk. [78:40] You've done you've done it all [78:41] >> pretty much. [78:41] >> Um, you and I had a show together. We [78:43] did. We got cancelled after six weeks, [78:45] but I knew we would. [78:46] >> It was a planned cancel. [78:47] >> It was temporary [78:47] >> because they told us it was canceled [78:48] before it started. [78:49] >> And Netflix calls it a limited series. [78:51] >> That's why we did a limited series. [78:52] Yeah. Uh tell us about Closing Bell [78:54] Overtime, what you love about it, and [78:56] how it differs from what's elsewhere on [78:58] the network. [78:59] >> 4:00 every day, four to five. And you [79:01] know, the the simplistic analogy, but [79:03] it's an accurate one, is the postgame [79:05] show, the immediate like here's what [79:07] happened. Um but also just pulling the [79:09] the themes out that matter. I mean it's [79:11] not just like the numbers and here's the [79:13] up and down. Uh we keep it pretty close [79:15] to the markets. Um [79:16] >> it's an amazing time slot because you [79:18] get earnings [79:18] >> and we get earnings and so [79:20] >> which is like the best [79:21] >> and which feels like you know it's [79:23] basically seven months out of the year [79:26] >> pretty much is like pretty full of [79:28] >> I can't believe Wapner let you have that [79:29] real estate and he took three. [79:31] >> He does get to he does get out a little [79:34] early but um [79:36] >> it's uh great. The earnings are great. I [79:38] mean, look, it's always tricky to figure [79:40] out exactly h how to execute that [79:43] trade-off between speed and depth. [79:45] >> That's really hard. [79:46] >> It's hard, you know, it's always like [79:48] kind of a moving target on that. Um, [79:50] like you're never going to be faster [79:51] than [79:51] >> you have [clears throat] to do that with [79:52] the right guest selection [79:53] >> than the headline reading algos like to [79:55] trade these things, but you want to be [79:56] fresh and want to make sure you have an [79:58] urgency about getting these numbers. And [80:00] so, yeah, that's uh it's been great so [80:02] far. Started in January and uh having [80:04] fun with it. [80:05] >> And you are still writing. [80:06] >> Yeah. [80:07] >> Okay. Okay. So, tell tell us uh about [80:09] the writing and where people can find [80:10] your stuff. [80:11] >> Sure. Um, so yeah, I've written a a [80:13] weekly column uh for CNBC Pro since I [80:15] since I got there. Now, it's kind of [80:17] being uh repackaged in a way into a [80:20] newsletter. Uh it's called market memo. [80:22] Most of it is just the body of it is [80:24] kind of like my column, my market comp. [80:26] Maybe a little more targeted, a little [80:27] bit less like here's the whole state of [80:29] play for the markets. And then maybe [80:31] just stray observation stuff like you [80:33] guys would do like here's a here's a [80:35] chart that's fascinating. here's um [80:37] here's a a a a point of conversation [80:39] that really kind of got escape velocity [80:41] during the the week and what are people [80:43] saying and then a little bit of pop [80:45] culture nonsense and Gen X, you know, [80:47] complaining that uh [80:48] >> that's the part I'm looking most forward [80:49] to. I know what happened in the market [80:51] that day. [80:51] >> I've been suppressing all the all these [80:53] years. Yes. [80:54] >> Uh why don't they brand that as like the [80:56] Michael Sani column? It see you have [80:58] like [80:58] >> I think it's Mike's market memo or Mike [81:00] Santo's market memo. [81:01] >> Can I pitch you a different version? [81:03] >> Go ahead. [81:03] >> Okay. Sam told me [81:05] >> it's not bad. [81:07] >> It's better than John. [81:08] >> You know, people have tried uh nicknames [81:10] over my course of my life. They haven't [81:12] stuck except for the kid in fifth grade. [81:13] Write my name on the board and he [81:15] misspelled it and so I became sand [81:16] toilet for a little while. [81:18] >> Nice. [81:18] >> But I'm glad that didn't hang with me. [81:20] >> All right. And then the last thing, [81:21] we're going to settle a beef. The Long [81:24] Island's eternal northshore versus [81:25] Southshore beef. Well, [81:27] >> where are you from? [81:27] >> Well, here's the thing. I'm talking [81:29] >> I'm sort of I'm sort of I was originally [81:32] from the Northshore. I was say you from [81:33] Plane View. [81:34] >> That's not originally from Port [81:36] Washington. Okay. [81:37] >> That's not sure. [81:37] >> But um my whole like extended family had [81:40] lived there for a long time. Look, I [81:41] like the hills. [81:42] >> But what's the beef though? [81:43] >> I'm I'm making that up. [81:44] >> I think there's good good and bad on [81:46] both. [81:46] >> No, absolutely. You guys got the ocean. [81:48] >> You have restaurants. [81:50] >> You have you have more you have more of [81:53] the good restaurants. [81:54] >> I live in the city. Let's be sure. Has a [81:57] northshore. Uh, better obviously better [82:00] school districts, but not [82:02] >> crazily better. No, [82:03] >> slightly. [82:04] >> It's preference. [82:05] >> It's a lot of preference. I do like the [82:06] woods [82:07] >> and the hills. [82:08] >> The Northshore is obviously way [82:09] prettier. [82:10] >> The woods and the hills and the whole [82:11] like, you know, if you go down a certain [82:13] area, it's Gatsby and all the rest of [82:15] it. [82:15] >> Yeah, but the coast sucks. Like we have [82:17] better beaches, [82:18] >> of course. Right. [82:19] >> Yeah. The Long Island Sound uh beaches [82:21] are [82:21] >> So, I wouldn't jet ski off the [82:23] Northshore. or you'll hit a rock like [82:25] where I where I am I have like white [82:27] sand beaches which so it is pre you're [82:30] right it is preference [82:31] >> uh it's 100% preference yeah [82:33] >> so if you live on in middle island you [82:35] get the best of both worlds [82:36] >> I kind of grew up yeah more like in the [82:38] middle [82:38] >> could ride my bike to either either [82:41] north shore or southshore [82:42] >> all right so I guess we settled that [82:43] with no answer [82:44] >> yeah I now live on a different island in [82:45] that [82:46] >> Michael we're obviously huge fans of [82:48] yours so much you did an amazing job on [82:50] the show you did not disappoint we're [82:52] going to encourage everybody to check [82:53] out. Closing bell Overtime 400 p.m. [82:56] Eastern, 5 days a week. Check out Mike's [82:59] market memo at CNBC.com. [83:03] Definitely subscribe to that and uh just [83:05] thank you so much for everything that [83:07] you've done, everything you've told us. [83:08] You guys are the best. Really appreciate [83:09] it. [83:10] >> You hear that? He said you're the best. [83:13] [applause]