Trivariate's Parker Sees Nvidia Hitting $10 Trillion Market Value

Trivariate的Parker预计Nvidia市值将达到10万亿美元 Nvidia将在2030年前达到10万亿美元估值，因其CUDA软件平台锁定了企业AI开发者，同时硬件收入翻倍。 讨论小组探讨了近期市场走势背后的宏观与基本面动态，详细阐述了为何在AI效率提升与CTO成本控制下，企业软件股面临估值压缩，而半导体板块的盈利预期却持续迎来爆发式上调。他们分析了企业分拆的投资策略，并给出了包括Broadcom、Lam Research、NRG Energy、APA Corporation和Gilead Sciences在内的夏季选股建议。此外，嘉宾们还分享了创办精品投研与财富管理公司的创业历程，分析了Ethereum的基础设施潜力，并阐述了Nvidia市值达到10万亿美元的长期逻辑。 随着CTO强化成本控制以及高昂的AI部署成本拖累远期利润率，企业软件股正面临巨大压力。 (7:26) 由于SaaS软件通常按员工人数定价，企业招聘放缓直接冲击了软件营收模式，使软件公司陷入“自证清白前先被推定看空”的境地。 (14:48) AI驱动的生产力提升预计将广泛推动标普500指数的盈利增长，而基于股票的薪酬依然是ServiceNow等高增长软件公司受股权稀释审查的关键焦点。 (16:22) 以VanEck半导体ETF在16天内实现35%的历史性飙升为代表，半导体板块的强劲涨势背后是真实的、前所未有的现金流与盈利预期上调，而非纯粹的投机行为。 (24:33) 科技板块远期市盈率从31倍压缩至19倍，主要由Nvidia和Micron等龙头企业爆发式增长的盈利预期推动，而非股价下跌所致。 (29:31)

Adam Parker of Trivariate Research and Rob Sechan of NewEdge Wealth argue that equity markets are undergoing a fundamental reallocation favoring physical AI infrastructure, semiconductors, and high-operating-leverage incumbents over traditional per-seat enterprise software. The Enterprise Software Margin and Headcount Dilemma (7:26) The panel identifies structural headwinds for the 150 to 200 publicly traded enterprise Software-as-a-Service (SaaS) companies. Parker argues that multiple contraction is merely the initial phase, with earnings and revenue misses likely to follow. Wall Street projections assuming sustained ~80% gross margins and 27% to 29% net margins conflict with reality, as SaaS vendors face rising AI infrastructure costs while enterprise chief technology officers enforce strict cost containment. Enterprise customers increasingly decline automatic price increases, realizing they can construct internal tools using foundational models. Furthermore, because standard SaaS contracts price on a per-seat basis, enterprise productivity gains that slow hiring directly suppress software revenue growth. The hosts examine ServiceNow (NOW) as an archetype: despite expanding clients paying over $5 million in annual contract value from 434 to 630 and retaining 97% of accounts, the stock fell 18% post-earnings when forward margin guidance was cut. High stock-based compensation and rising headcount from 26,698 to 29,732 employees compounded investor scrutiny. Parker advises avoiding deeply discounted software names facing technological obsolescence, favoring mission-critical niches such as cybersecurity (CrowdStrike, Palo Alto Networks) and electronic design automation (Cadence, Synopsys). Semiconductor Dominance Grounded in Earnings Revisions (24:33) Addressing whether the semiconductor surge reflects speculative excess, the panel contends that multiple expansion is fundamentally supported by historic upward revisions in earnings and cash flow. The VanEck Semiconductor ETF (SMH) experienced a record 35% gain over a rolling 16-day window, bringing the semiconductor sector to 16% of the S&P 500 market cap—nearly rivaling the combined 19% weight of Energy, Healthcare, Consumer Staples, and Utilities. Parker notes that two companies alone, Nvidia and Micron, generated 45% of the S&P 500's year-over-year earnings growth between Q1 2025 and Q1 2026. Because earnings estimates expanded so rapidly, the tech sector's forward price-to-earnings ratio actually compressed from 31x to 19x. Valuations remain unevenly dispersed; Micron trades near 4.5 times forward earnings while experiencing a product shortage and a 100% surge in earnings projections. The panel defends market concentration, asserting that index weighting reflects forward earnings guidance extending toward 2030 rather than speculative momentum, with secondary demand flowing directly into power and industrial providers like GE Vernova, Vistra, and Eaton. The Thesis for Nvidia Reaching $10 Trillion (81:23) Parker projects that Nvidia (NVDA) will expand from its approximate $4.8 trillion valuation to a $10 trillion market capitalization by 2030, driven by a compound annual revenue growth rate of roughly 15% over the next five years. He contends that investors miscategorize Nvidia by analyzing it as a single stock rather than viewing it as its own technology sub-sector, underestimating its moat. That moat is anchored in Nvidia's proprietary CUDA computing platform, developed over 15 years, which creates high switching costs for developers and enterprise software architectures. Parker dismisses risks regarding capital expenditure concentration among hyperscalers like Amazon, Microsoft, and Alphabet, asserting that hyperscaler cloud purchases aggregate underlying spending from tens of thousands of end customers. He also downplays threats from custom application-specific integrated circuits (ASICs) like Google TPUs, citing Nvidia's continuous ecosystem reinvestment. Healthcare Operating Leverage and Capital Allocation (60:06) Beyond core technology, Parker identifies healthcare as an unappreciated asymmetric AI beneficiary, estimating a 30% to 40% probability that healthcare leads market returns over the next five years, despite consensus pricing in near-zero odds. Given the sector's thin margins, large workforces, and non-cyclical demand—demonstrated by 30 consecutive years of S&P 500 healthcare revenue-per-share expansion—automated diagnostic workflows and labor prediction generate substantial operating leverage for distribution and laboratory incumbents such as McKesson, Cardinal Health, Cencora, Quest Diagnostics, and Labcorp. Complementing sector selection, Parker presents quantitative data from his 'Spinoff Playbook.' Analyzing corporate reorganizations, his research shows that over a two-year holding window, spun-off entities (SpinCos) outpace their industry group benchmarks by an average of 10%, whereas remaining parent companies (RemainCos) typically underperform. SpinCos benefit from eliminated operational friction, optimized capital structures, and tax efficiency, supported by recent examples like GE Vernova, Carrier Global, and Otis Worldwide. The broader thesis hinges on whether enterprise capital expenditure on AI hardware yields commensurate economic returns before balance-sheet fatigue sets in. While Parker and Sechan view the semiconductor rally as fundamentally backstopped by cash generation, the trajectory relies on forward earnings guidance holding firm through 2030 and non-tech sectors successfully extracting margin gains from automated tools.

Trivariate Research 创始人 Adam Parker 与 NewEdge Wealth 首席执行官 Rob Sechan 指出，美股科技板块正经历基本面分化：传统企业软件（SaaS）面临定价承压与利润率下调，而算力与 AI 基础设施则受强劲盈利驱动，其中 Nvidia 依托 CUDA 生态护城河，有望在 2030 年前达到 10 万亿美元市值。 软件板块估值收缩与商业模式承压 (7:26) 企业软件股近期遭遇大幅抛售，如 ServiceNow 在单日暴跌 18%。Adam Parker 提出悲观逻辑，认为当前估值倍数回撤仅是第一步，后续分析师盈利预测和营收不及预期将接踵而至。华尔街模型长期假设软件公司能维持约 80% 的毛利率及 27% 至 29% 的净利率，但随着企业整合高成本的 AI 工具，资本支出与运营成本将显著抬升。同时，大型金融机构的首席技术官正在推行成本控制，拒绝自动提价，并尝试利用 Claude 等模型自行搭建内部工具，不再单纯依赖外部 SaaS 供应商。 此外，市场上 150 至 200 家上市企业级 SaaS 公司普遍采用按人头计费的商业模式。随着企业借助 AI 提升效率导致人员招聘放缓，软件厂商的核心增收引擎受到直接压制。Parker 建议避开纯粹因估值下跌而看似便宜的软件股，警惕技术淘汰风险，主张聚焦于网络安全（如 CrowdStrike、Palo Alto Networks）及 EDA 设计（如 Cadence、Synopsys）等高壁垒、关键任务型领域。 芯片股盈利爆发驱动估值自然压缩 (24:33) 半导体板块走势与软件形成鲜明对比，VanEck 半导体 ETF（SMH）曾创下 16 个交易日内上涨 35% 的历史最高区间涨幅。Parker 强调，这一涨幅背后并非投机性泡沫，而是前所未有的盈利和现金流大幅上修。例如，Micron 在产品短缺驱动下远期市盈率仅约 4.5 倍，盈利预期短时间内翻倍；Nvidia 的远期每股收益预期则由约 50 美元上修至近 100 美元。从同比来看，标普 500 指数在 2026 年第一季度的整体盈利增长中，有 45% 仅来自 Micron 和 Nvidia 两家公司。 科技板块的远期市盈率已迅速从高位的 31 倍回落至 19 倍。嘉宾指出，这种估值倍数压缩主要源于盈利预期（E）的超预期大幅扩张，而非股价大幅下跌所致。目前半导体在标普 500 中的市值权重达到 16%，接近能源、医疗、必需消费与公用事业四个防御板块的总和（19%）。嘉宾认为，该权重配置反映了市场对 2030 年前盈利高增长方向的合理定价。 Nvidia 迈向 10 万亿美元市值与 AI 基础设施 (81:23) Adam Parker 阐述了 Nvidia 市值从约 4.8 万亿美元迈向 10 万亿美元的核心逻辑。他主张投资者应将 Nvidia 视作一个独立的科技生态体系，而非普通个股。其底层护城河在于长达 15 年、早期亏损研发所构筑的 CUDA 软件生态，目前主流 AI 开发者和企业模型均已与该平台深度绑定，迁移成本极高。Parker 预测，Nvidia 未来五年有望保持 15% 的年化复合增长率，实现营收翻倍及巨额自由现金流。 针对云厂商自研定制芯片（如 Google TPU）与资本开支过度集中的市场担忧，Parker 解释称，AWS 等超级云计算巨头采购芯片实际上代表了下游数千家企业客户的真实终端需求。与此同时，AI 算力部署带动了周边基础设施需求，例如 Broadcom 在定制芯片与网络交换中的垄断地位、Lam Research 在制造设备中的高集中度，以及 NRG Energy 与 Vistra 等通过向数据中心直供天然气电力的公用事业标的。 医疗板块的 AI 运营杠杆与分拆策略 (48:21) 在科技主线之外，嘉宾探讨了具备不对称收益机会的资产组合。Parker 认为，医疗板块被市场过度低估，尽管当前市场几乎未对其给予预期，但他评估未来五年医疗成为标普领涨板块的概率达 30% 至 40%。医疗行业拥有长达 30 年稳健的人均营收增长历史，涵盖诊断、药物及管理式医疗等刚性需求。由于医疗机构普遍存在人员规模庞大而净利润率较薄的特征，引入 AI 预测诊断和自动化运营有望释放巨大的经营杠杆。 在资本运作策略方面，Parker 梳理了“企业分拆操作指南”（Spinoff Playbook）。Trivariate Research 的历史数据显示，在完成分拆后的两年内（约 504 个交易日），被分拆出的独立实体（SpinCo）平均跑赢同行业基准 10%，而母公司（RemainCo）通常跑输基准。分拆不仅能规避高昂的直接出售资产税负，还能消除原有企业内部的负协同效应，使管理层得以优化资本结构并聚焦主业。 财富管理独立化趋势与以太坊基建逻辑 (63:16) Rob Sechan 回顾了 NewEdge Wealth 在五年内将管理资产规模由 80 亿美元扩张至 105 亿美元的历程。他分析指出，传统大型经纪商（Wirehouse）顾问正加速流向独立注册投资顾问（RIA）平台，后者的核心优势在于打破了单一机构专有产品的销售限制，能够站在客户立场对接全市场的贷款、执行与资本市场解决方案。NewEdge 早期通过与私募股权机构 Parthenon Capital 联手杠杆收购成熟的 401(k) 基建业务，为后续吸引资深管理团队打下了技术与现金流基础。 在数字资产领域，Sechan 探讨了其担任独立董事的 Bitmine Immersion Technologies（BMNR）模式。他认为，以太坊不仅是代币，更是服务于金融资产代币化与智能合约的 24 小时底层基础设施。面对传统金融清算缓慢且受限于交易时段的痛点，主流交易所正在推进真实世界资产（RWA）上链。该类企业通过以太坊验证节点运营（Maven）捕获约 3% 至 4% 的质押收益与 Gas 费用，旨在建立充当 AI 应用安全互信底座的可编程区块链网络。 本期节目梳理了美股在 AI 浪潮下的赢家更替逻辑：硬件算力龙头与重资产基建享有真实盈利增长带来的支撑，而依赖席位收费的 SaaS 软件则面临重定价周期。但上述推演依然取决于未来数个季度企业 AI 资本开支能否持续兑现，以及宏观经济在高利率环境下能否抵御潜在的盈利下修考验。

## Background 本期视频由财经播客频道 The Compound 于 2026 年 4 月 24 日在 YouTube 平台发布。节目由主持人 Michael Batnick 与 Downtown Josh Brown 共同主持，特邀 Trivariate Research 创始人 Adam Parker 及 NewEdge Wealth 联合创始人 Rob Sechan 作客。视频简介指出，四人围绕当前驱动美股市场的核心力量展开深度复盘，重点探讨了软件股惨烈杀跌的底层逻辑、半导体涨势是否脱离基本面、企业分拆上市策略、夏季精选股票池以及英伟达迈向 10 万亿美元市值的长期推演路径。 ## TL;DR 本期节目深入剖析了美股科技与资本市场的剧烈分化格局：SaaS 软件股因商业模式受 AI 冲击、成本高企及提价逻辑破灭而陷入“有罪推定”的杀估值泥潭，而半导体与 AI 基础设施板块则在扎实的业绩预期上调支撑下持续展现强劲动能。嘉宾们结合自身投资实战与宏观观察，指出市场惩罚机制极度严苛，但在阶梯式回调中应坚守估值准绳、向高质龙头靠拢。此外，节目还详细拆解了企业分拆（Spinoff）带来的超额 Alpha 规律、涵盖博通与公用事业等标的的平衡型夏季投资组合，以及以太坊储备公司 BMNR 的底层逻辑。Adam Parker 更做出激进非共识预测，认为英伟达凭借无可替代的软件生态壁垒已成为“一个独立行业”，将在 2030 年底前突破 10 万亿美元市值。 ## Atmosphere & style 整场对谈氛围兼具顶级华尔街老将的犀利风暴与多年挚友间的插科打诨，节奏明快且信息密度极高。从开场爆笑的“全接触拥抱”调侃和早年连线互怼趣事，到严肃拆解财报四象限与量化回测，四位嘉宾展现出极高的专业默契与敢说真话的锐气。现场既有对踏空、浮亏和宏观指标局限性的坦率自嘲，也有对 AI 重构企业护城河与资本运作规律的深刻洞见，收听体验既像在参与一场高端买方闭门投资策略会，又充满轻松诙谐的脱口秀色彩。 ## Bulletin - [01:21:46](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4906s) Adam Parker 预测英伟达将在 2030 年底前达到 10 万亿美元市值，其凭借 15 年研发的 CUDA 生态与全产业链布局，已从单只股票演变为无法绕开的独立行业基础设施。 - [15:13](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=913s) 美股软件板块陷入极度严苛的“有罪推定”审判：AI 革命导致企业招聘放缓，动摇了 SaaS 按人头席位收费的增长根基，即使营收达标，只要利润率展望下滑便会遭遇单日 20% 级别的杀跌。 - [30:18](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1818s) 科技板块远期市盈率回落至 19 倍并非估值折价，而是盈利分母（E）暴增驱动；标普 500 指数 2026 年 Q1 同比全部盈利增量中，仅英伟达与美光两家巨头便贡献了高达 45%。 - [53:53](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3233s) Trivariate 量化研究揭示分拆战术超额收益：被分拆出的独立实体（SpinCo）上市后两年内平均跑赢行业基准 10%，而母公司留存业务（RemainCo）则平均跑输 2% 至 3%。 - [55:04](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3304s) NewEdge 披露夏季杠铃配置组合，涵盖 AI 龙头博通（AVGO）与泛林集团（LRCX）、受益算力电力瓶颈的 NRG Energy（NRG）、抗通胀与地缘对冲标的阿帕奇石油（APA），以及防御与长线医药 AI 标的吉利德科学（GILD）。 ## Key takeaways - [07:26](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=446s) 华尔街盛行“做多半导体、做空软件”的配对交易惯性，软件板块技术指标极度超卖，短期估值难以释放，只有等待盈利能力长期得到重新验证。 - [09:23](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=563s) 企业级软件板块面临自上而下的基本面重估：卖方模型假设的高毛利难以维系，巨额 AI 研发开支与大客户压价控制成本正在压制远期利润率。 - [11:07](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=667s) 投资软件应偏好高估值龙头（如 EDA 软件、核心网络安全），低估值软件往往面临更高的 AI 原生工作流颠覆淘汰风险，而高价软件具备合规与防御护城河。 - [15:13](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=913s) SaaS 按席位/人头（Per-headcount）收费的商业模式在 AI 时代受到严峻挑战，反观沃尔玛等通过自动化大幅压缩人员、提升净利率的传统企业更具生产力溢价。 - [17:49](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1069s) AI 带来的盈利增长仍处于第一局，标普 500 与科技板块的高盈利增速预期并非泡沫，但市场对油价大幅下行的假设过于乐观，降息若落地可能反成增长恐慌信号。 - [30:18](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1818s) 科技板块当前估值压缩主因是盈利预期大幅上调，在标普 500 同期盈利增长中，英伟达和美光合计贡献了 45% 的利润增量。 - [32:12](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1932s) 美股遭遇地缘事件时呈现缺乏恐慌盘的“阶梯式阴跌”，反映出深层流动性健康，为自上而下配置高确信度龙头（如远期 PE 回落至 30 倍以内的英伟达）提供了建仓机会。 - [35:58](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2158s) 私募信贷位于资本结构优先受偿层且拥有厚重股本保护，尽管财富端募集增速放缓，但直接抄底被腰斩的上市公司 GP（资管机构）股票比买入平价交易的底层信贷更具性价比。 - [39:53](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2393s) 市场广度（创新高个股比例）等指标缺乏统计显著性，将其作为短期择时工具往往毁灭组合价值，指数高度集中反映的是企业基本面指引的分化现实。 - [43:06](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2586s) 半导体板块市值占比升至标普的 16% 完全具备业绩上调支撑，该牛市见顶的唯一信号是全市场一致预期被证实高估的前六个月。 - [45:15](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2715s) 盲目止盈常导致高额税负与错失超级大牛股，应运用跟踪止损顺应平稳爬坡的动能趋势，避开数天内翻倍的抛物线投机形态。 - [53:53](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3233s) 分拆战术手册实证表明，SpinCo 新公司因更务实的业绩指引与利润率释放路径，两年内平均跑赢基准 10%，为主动选股提供了机器算法无法取代的 Alpha 空间。 - [01:00:32](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3632s) 医疗保健板块连续数十年实现每股营收正增长，目前极低的估值反映出市场认定其无法受益于 AI 的极端悲观预期，长期蕴含着 30% 到 40% 的均值回归赔率。 - [01:03:17](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3797s) 独立投资顾问（RIA）行业迎来从华尔街大行出走的新浪潮，以全市场客户身份进行跨机构比价并嫁接先进 AI 工具，正在重构财富管理竞争格局。 - [01:16:20](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4580s) 以太坊具备 24 小时实时清算与可编程特性，正成为传统金融底层基础设施；BMNR 通过质押网络收益与生态投资，构筑了超越单纯持币的商业化收益模式。 - [01:21:46](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4906s) 英伟达凭借 15 年构筑的 CUDA 生态与不可替代的装机基础，已演化为一个独立的科技门类，维持年均 15% 复合增速将在 2030 年底支撑其达到 10 万亿美元市值。 ## Detailed walkthrough ### [00:00](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=0s) 开场趣事：“全接触拥抱”与录制前闲聊 节目在轻松幽默的幕后闲聊中拉开序幕。Josh Brown 和 Michael Batnick 调侃 Adam Parker 与 Rob Sechan 是否真的是私交甚笃的好友，两人立刻给出了肯定回答。随后，Rob 绘声绘色地爆料了一则关于他们共同好友的爆笑趣事：当时 Adam 专程前往劳德代尔堡（Fort Lauderdale）与 Rob 共进午餐，由于 Rob 的机构是 Adam 创办的研究公司的客户，两人一边用餐一边聊起某位金融圈内人尽皆知的共同好友。Adam 评价那人是个极其罕见的“Tip to Tip”型人物。 Rob 当时完全没听懂，反问这是什么意思。Adam 解释称，大多数人见面拥抱握手时，出于社交礼仪和身体界限，都会侧过身子，形成肩膀微倾的“Tip to Hip”（身体一侧轻触）姿态；然而这位共同好友每次打招呼都会径直迎面走来，来一个结结实实、毫无死角的“正面全接触拥抱（Full frontal hug）”。这个生动的比喻让 Rob 在整场午餐中笑得直不起腰。两人虽然极力隐瞒该好友的真实身份，但坦言全行业大概只有这位德高望重的人物能以这种热烈方式拥抱而不显冒犯。随后录音棚里的调侃进一步发散，大家互相开起玩笑：从向美国国税局（IRS）报税时的真实居住地之谜，到中年脱发危机——Josh 戏谑道如今想恢复当年的飘逸发量只能去土耳其做植发手术，甚至可能植的是小狗的毛发。 ### [03:04](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=184s) 节目花絮：Adam Parker 与 CNBC 记者 Leslie Picker 的乌龙插曲 在正式开麦前的倒计时阶段，Michael Batnick 翻出了一则关于 Adam Parker 的陈年窘事：据说 Adam 在参加 CNBC 知名财经节目《Closing Bell》与著名记者 Leslie Picker 连线直播前，竟然在最后一刻紧张地在后台“背景调查” Leslie Picker 的从业履历，似乎在核验对方是否有足够的专业水平来向他提问股市走势。 面对调侃，Adam 满脸通红、大汗淋漓地连忙解释辟谣。他坚决否认自己是在质疑 Leslie 的资历，而是因为上台前没有充分准备寒暄话题，情急之下临时搜索她的教育背景（比如毕业于 UCLA）寻找共同话题以拉近距离。Michael 则毫不留情地进一步补刀，爆料 Adam 当时在商业广告间歇甚至还向现场制片人核实 Leslie 是否真的曾获得过著名的“杰拉尔德·勒布奖”（Gerald Loeb Award）提名。全场在一片欢声笑语中隔空向 Leslie Picker 致意，录音棚内的气氛也被彻底炒热。 ### [04:41](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=281s) 赞助支持：Public.com 与 Agentic 经纪平台 节目切入中场赞助环节，介绍了现代投资平台 Public.com 推出的全新自动化智能体（Agentic）投资功能。对于主动管理投资组合的交易者而言，日常操作中往往充斥着机械重复的劳动，如逢低买入、手动归集闲置现金或建立对冲仓位。 - **自然语言驱动的工作流**：投资者可以直接用日常英语向系统下达策略指令，例如设置“当波动率指数 VIX 触及 25 时，自动买入标普 500 指数看跌期权”，或者“当账户现金余额超过 20,000 美元时，将超出部分自动转入直接指数化（Direct Indexing）组合中”。 - **意图驱动而非点击驱动**：用户确认工作流后，AI 智能体即可代为全天候监控市场、捕捉触发条件并精准执行策略。 - **全功能 API 与资产转移奖励**：平台提供账户的读写 API 权限，并为通过专属链接转移投资组合的用户提供无上限的 1% 资金匹配奖励。 ### [05:56](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=356s) 正式开场：嘉宾背景与第 239 期阵容介绍 Josh Brown 正式宣布《The Compound and Friends》第 239 期开播。Rob Sechan 幽默地形容这是自己的“播客处女秀”，在嘉宾阵容里只能算处于“打线末端”，甚至还需要老手 Adam 一起陪同充当“辅助轮”。随后 Josh 隆重介绍了本期两位重量级重磅嘉宾的履历与光辉战绩： - **Adam Parker**：独立研究机构 Trivariate Research 的创始人兼首席执行官。在此之前，他曾创立并管理股票多空对冲基金 Trivariate Capital，同时长期担任 Rob 旗下机构 NewEdge Wealth 的投资顾问委员会成员，是节目的常客与收视门面。 - **Rob Sechan**：新锐财富管理巨头 NewEdge Wealth 的联合创始人、首席执行官兼执行合伙人，同时担任 NewEdge Capital Group 的联席执行合伙人。在创立 NewEdge 之前，Rob 曾历任摩根士丹利（Morgan Stanley）顾问、雷曼兄弟（Lehman Brothers）总监（Josh 特别打趣澄清雷曼倒闭绝非 Rob 的过错）以及瑞银（UBS）总监，并屡次入选《巴伦周刊》（Barron's）与《福布斯》（Forbes）全美前 100 顶尖财富顾问榜单。 ### [07:26](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=446s) 软件股的至暗时刻：“有罪推定”与做多芯片/做空软件的行业踩踏 节目开门见山切入当下华尔街最为剧烈、痛苦的分化板块——软件行业。Josh 指出隔夜市场中软件巨头 ServiceNow（NOW）再次发生暴跌，这已经演变成整个科技板块挥之不去的月度噩梦：软件板块内大量股票此前已自高点腰斩 50%，然而哪怕表面上交出了一份相当体面甚至亮眼的季度财报，股价依然会在盘后遭到无情抛售，市场仿佛深不见底。 ```mermaid flowchart TD accTitle: 软件板块资金分流与估值杀跌机制 accDescr: 展现资金从软件板块流向半导体板块的负向反馈循环 subgraph MacroTrade["主流宏观多空交易策略"] A["做多半导体 / 算力基础设施 (Semis)"] B["做空 SaaS / 企业软件服务 (Software)"] end subgraph MarketReaction["软件股面临的市场审判"] C["财报业绩超预期"] --> D["市场情绪：有罪推定 (Guilty until proven innocent)"] D --> E["股价自高点回撤 50% 后继续破位暴跌"] end subgraph StructuralShift["行业底层格局迁移"] F["AI 技术奇点降临"] --> G["颠覆传统软件商业模式<br/>(震荡进入全新大气层)"] G --> B G --> A end ``` Rob Sechan 率先分享了他的宏观与仓位视角。他坦言目前绝不敢轻言软件板块已经见底，尽管该板块的技术指标已极度超卖，且长期价值正在逐步显现。NewEdge 旗下曾经持有包括 Adobe（ADBE）在内的多只核心软件股，但近期团队的操作策略只能是不断向最高质量的龙头防守收缩，以期在行业出现反转时能够分得一杯羹。Rob 直言现在的软件股陷入了极其残酷的“有罪推定”状态——只要利空预期存在，任何业绩都无法阻止抛售；市场上“做多半导体、做空软件（Long Semis, Short Software）”的结构性配对交易已经形成了强大的趋势惯性。他援引传奇宏观对冲基金经理、摩尔资本（Moore Capital）创始人路易斯·培根（Louis Bacon）的名言指出：“每隔一段时间，市场上总会出现某种颠覆性的力量，硬生生把你撞进另一个完全不同的大气层。”当前的人工智能浪潮正是这股力量，软件股被狠狠撞离了原有的轨道，这种格局短期内难以逆转，但从中长期来看，只要未来软件企业的盈利能力得到持续验证，其被深埋的估值终有释放的一天。 对此，Josh 苦笑自嘲称，自己甚至想打电话给富达（Fidelity）客服，请求他们系统能不能直接把自己的软件股持仓隐藏起来，免得每次登录账户看到那些刺眼的亏损数字自寻烦恼，因为“我早就知道它们每天都在跌”。紧接着，Adam Parker 接过话茬准备发表他的深度剖析，他谨慎地打预防针表示，鉴于当前宏观与科技演进的复杂程度远超往常，自己在近期所有客户会议开头都会先加上一句免责声明：“我接下来所说的一切都有可能是错的。”在此基调下，他开始从底层逻辑展开对软件股真实处境的推演。 ### [09:23](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=563s) 软件股的杀估值逻辑与财报暴雷预警 Adam Parker 非常坦率地复盘了自己团队今年的行业研报表现。他自嘲在行业层面上做过几个很糟糕的预测，比如之前持续看好医疗保健板块（Healthcare），结果表现极其糟糕；但在软件行业上，他们的判断却异常敏锐且精准。Adam 阐述了他的核心论点：在市场周期中，当估值倍数（Multiples）像过去一段时间那样剧烈收缩时，紧随其后的必然是每股收益（Earnings）不及预期，最终演变为营收（Sales）全面失守。因此，当明星 SaaS 股 ServiceNow（$NOW）暴跌时，他丝毫没有感到意外，尽管这只股票一直是多头最喜爱、维护最坚决的标的之一。 软件公司即将面临业绩暴雷的根本原因，在于卖方分析师的模型与现实严重脱节。分析师们想当然地在模型里给未来几年（2027、2028、2029 年）全部填上 80% 的毛利率和完全一致的净利率。然而现实是，如果软件厂商不进行巨额研发与资本开支，又怎么可能为客户无缝接入所需的各类前沿 AI 工具？更致命的是来自大客户的议价压力——摩根大通（JPMorgan）或摩根士丹利（Morgan Stanley）的首席技术官（CTO）迟早会回头向软件供应商施压压价，因为大机构拥有庞大的自研团队，他们完全可以自己搭建并外挂专用 AI 工具。 分析师目前仍沉溺于传统调研套路：给熟悉的 CTO 打电话，对方打包票说“我们绝不可能替换掉 ServiceNow”；再给投资者关系（IR）负责人打电话，双方一起把酒言欢、为莫须有的“SaaS 大崩盘”抱头痛哭。Adam 直言，当下的分歧根本不在于今天的基本面如何，而在于 2030 年基本面结果分布的不确定性。瑞银（UBS）近期也发布报告警告称软件板块尚未见底，因为在对众多 CTO 进行深度访谈后，所有技术高管嘴里吐出的都是同一个词——“成本控制”（Cost containment）。过去几年软件行业的暴利建立在两大神话之上：自称是不可或缺的“记录系统”（System of record），以及拥有无人敢反抗的单向涨价权，而如今这种顺理成章的提价逻辑已被彻底打破。 ```mermaid flowchart TD accTitle: 软件股基本面恶化传导路径 accDescr: 展示从估值压缩、业绩暴雷到最终营收下滑的三个阶段及背后的现实驱动力。 subgraph S1["第一阶段：估值收缩"] A["市场情绪转变与倍数压缩"] end subgraph S2["第二阶段：利润不及预期"] B["AI 工具研发与集成开支激增"] C["分析师80%毛利率假设破灭"] B --> D["利润率承压，EPS 暴雷"] C --> D end subgraph S3["第三阶段：营收见顶回落"] E["企业客户启动成本控制"] F["大型机构自研外挂替代涨价"] E --> G["席位增长停滞与提价受阻，销售额不及预期"] F --> G end A --> S2 D --> S3 ``` --- ### [11:07](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=667s) “贵有贵的道理”：为何应该买昂贵软件而非便宜货 在软件板块的选股策略上，Adam Parker 提出了一个反直觉的观点：投资者反而应该买入那些看起来非常昂贵的软件股，绝不要贪便宜去碰估值低廉的软件资产。虽然散户个体经常犯傻，但市场的集体定价往往是极其理性的。在软件行业，一只股票变得便宜通常有着致命的原因——它被新兴技术颠覆（Disrupted）的概率远高于同行；反观那些依然昂贵的股票，比如网络安全软件、Cadence 以及 Synopsys 等，之所以享受高溢价，是因为它们面临的技术淘汰风险（Technological obsolescence risk）极低。历史数据表明，在反弹周期中跑赢的往往是高成长、高估值的龙头，而不是那些看似便宜的慢速增长公司。 为了生动阐述这一点，Adam 打了一个形象的比方：很多核心软件未来会变得像咨询巨头麦肯锡（McKinsey）一样——当一家大企业想要裁员一百万人时，管理层必须花巨资聘请麦肯锡，由麦肯锡出具报告建议裁员，随后管理层才能顺水推舟地宣布“这是外部顶尖专家的建议”，以此规避自身责任。软件采购同样充斥着这种“免责买单”的防御逻辑。 例如在财富管理机构 NewEdge Wealth，即便内部技术人员用 Claude 编写了一套安全防御代码，高管也不可能直接将其投入生产环境。万一后续发生客户顾问数据泄露事件，拍板采纳内测代码的人就得被当场解雇。正因如此，企业必须老老实实向 CrowdStrike 或 Palo Alto Networks 支付昂贵的安全订阅费，目的就是为了在系统出事时能有一个行业公认的专家背锅。因此，这类核心壁垒深厚、不可替代的安全软件虽然价格高昂，但其逻辑依然坚挺。 - **便宜陷阱**：软件股便宜并非价值洼地，而是大概率面临被新型 AI 原生工作流颠覆的致命风险。 - **高估值护城河**：EDA 巨头（Cadence、Synopsys）和核心网安软件（CrowdStrike、Palo Alto Networks）凭借技术复杂性与企业合规风控需求，拥有极低的技术淘汰率。 --- ### [12:28](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=748s) AI 重构工作流：从初级分析师到企业全员 Claude 化 Josh Brown 提到，如今全美各大金融机构和科技企业的内部技术团队几乎都处于近乎狂热的高频开发状态，大家都在疯狂地调用大模型写代码。NewEdge Wealth 的管理合伙人 Rob Sechan 赞同了这一观察。Rob 特别提及了公司内部屡获殊荣的明星选股人 Jay，称赞其完全立足于技术驱动的选股框架。Rob 指出，NewEdge 从创立之初就是一家基于技术赋能的机构，直接架设在机构级的高性能底层基础设施之上，而非脱胎于传统的私人银行柜台或地下室个人作坊。这种现代化架构让他们可以即插即用各类新技术，并在一个月前就为全公司员工完整部署了 Claude Enterprise。 谈及 AI 对专业工作日常的改变，Rob 感慨现在的体验“就像指尖随时有 15 位顶级初级分析师在为自己待命”。他回忆当年在摩根士丹利做投行分析师的年代，一位董事总经理（MD）布置一项分析任务后，底下的人需要翻天覆地做模型，两天后才能拿出初步成果进行第二轮讨论。而如今，NewEdge 正在推进多起并购案，他在处理并购交易分析时只要向大模型提问，几秒钟内就能获得即时的深度反馈并持续迭代。 Adam Parker 随即调侃起实习生的尴尬境遇：他过去常常因为人情世故不得不招进很多亲友推荐的实习生，以前为了打发他们，会派任务让他们梳理微软过去五年所有的并购交易并总结收购的技术栈，实习生往往要忙上几天；而现在实习生用大模型两秒钟就跑完了结果，剩下的九天半时间坐在工位上面面相觑、无所事事。不过 Rob 指出，在强大的 AI 杠杆加持下，即使是普通实习生也能迅速产出良好到优秀的成果，而真正顶尖的人才则将彻底改变企业的生产力天花板。这种效率提升正在各行各业全面铺开，虽然企业短期内未必会大规模裁员，但招聘放缓已是不争的事实。 --- ### [15:13](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=913s) SaaS 的按人头收费死局与沃尔玛的效率溢价 Josh Brown 指出了整个企业级 SaaS 行业所面临的最深层结构性矛盾：美股公开市场上大约有 150 到 200 家企业级 SaaS 公司，撇开已经难以推进的涨价能力不谈，最根本的硬伤在于绝大多数软件都是“按席位/人头”（Per-headcount）收费的。如果 AI 带来的效率革命意味着企业哪怕不主动裁员也绝不会再像过去那样大幅增加员工总数，那么建立在员工人头持续扩张基础上的 SaaS 商业模式将彻底失效。 为了印证这一点，团队在屏幕上切出了当天早盘因发布财报而暴跌 18% 的 ServiceNow 图表。Michael Batnick 痛苦地自嘲道，自己竟然恰好在财报公布前夕或前一天刚刚把 ServiceNow 选为自己的“尾盘推荐交易”（Final trade）。数据显示，ServiceNow 的员工人数依然在逆势膨胀，从 2025 年第一季度的 26,698 人增加到了 2026 年第一季度的 29,732 人；与此同时，其基于股票的薪酬开支（Stock-based compensation, SBC）呈现出完全失控的爆发式增长。Josh 尖锐地批评道，在华尔街对科技股薪酬稀释极其敏感的当下，管理层似乎完全没有领会市场的警告信号。 ``` ServiceNow (NOW) 员工人数变动趋势： ├── 2025 年 Q1：26,698 人 └── 2026 年 Q1：29,732 人（逆势扩张带来巨大成本重压） ``` Adam 对此点评道，股票薪酬本质上是一个高贝塔因子（Beta factor）以及研发强度的代名词；在科技股大牛市中，高 SBC 的公司往往能顺风大涨，但在逆风期则会遭遇更惨烈的惩罚。对话最后引向了生产力解放的真正受益者。Adam 指出，资本市场最可能出现指数级暴涨的标的并非传统软件，而是像沃尔玛（Walmart）这样的巨头。沃尔玛目前之所以能享受高达约 38 倍的前瞻市盈率，并非因为其当前区区 3.5% 左右的净利润率，而是因为市场正在提前对其 2030 年的形态进行定价——届时借助自动化与 AI，沃尔玛的员工总数很可能远低于当下，而其整体净利润率有望从现在的低水准大幅跃升至 5% 甚至 6%。 ### [17:49](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1069s) 华尔街与经济学家的脱节，以及安库尔·克劳福德对 AI 泡沫论的驳斥 讨论从企业如何将 AI 落地到实际业务展开。各家公司目前都处于探索这项技术的“枪尖”前沿，试图摸清技术迁移对商业模式的具体影响，学习速度前所未有。亚当·帕克（Adam Parker）借此讽刺了华尔街与普通大众乃至主流经济学家之间的巨大认知鸿沟：如果沃尔玛（Walmart）宣布“到 2030 年大幅削减员工人数”，其股价很可能会迎来抛物线般的狂飙；但这恰恰是大众痛恨华尔街的原因。帕克回忆自己在摩根士丹利（Morgan Stanley）时，经济学家总在呼吁“增加资本支出、扩大招聘”，而作为股票策略师，他的第一反应却是：“如果我持有的公司宣布大举招聘或扩大资本开支，我会立刻把股票卖掉。”经济学家关心的 GDP 增长与更多高薪就业岗位，和自下而上的选股逻辑存在根本脱节。 话题随后转向阿尔杰（Alger）的明星基金经理安库尔·克劳福德（Ankur Crawford）。她在过去 12 个月中管理着全市场业绩排名第一的成长型基金，并拥有斯坦福大学博士学位。克劳福德此前在节目中直言，那些看空 AI、认定其为巨大泡沫的人完全是“一派胡言”（nonsense）。帕克对此深表认同，并指出市场当前正处于一个转折关口：虽然从股价涨幅来看，某些股票可能已经走到“第五局”，但从 AI 真正体现在财务报表和盈利数字上的进程来看，我们仅仅处于“第一局”。目前华尔街对标普 500 指数今年和明年的盈利增速预期分别为 18% 和 17%，而对科技板块的预期更是高达今年 43%、明年 25%，这正是因为 AI 带来的基本面红利才刚刚开始显现。 - 华尔街与经济学家的视角冲突：宏观经济追求充分就业与资本扩张，而二级市场更青睐降本增效与利润率杠杆。 - 标普 500 与科技板块盈利预期：标普 500 今明两年预期增速为 18% 和 17%，科技板块预期增速为 43% 和 25%。 --- ### [19:54](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1194s) 标普 493 的补涨潜力与汤姆·李的跨资产“读心术” 迈克尔·巴特尼克（Michael Batnick）与罗布·塞尚（Rob Sechan）讨论了近期小盘股的突破以及标普 500 中剔除“科技七巨头”（Magnificent 7）后的其余 493 只股票（S&P 493）。数据显示，标普 493 的盈利增速预期也达到了 15% 至 16% 左右。嘉宾们一致认为，在当前并非 8% GDP 高增长的宏观环境下，如果没有 AI 带来的底层生产力提升，这种广泛的盈利增长根本无法成立。 在解析市场价格走势与底层经济背离的现象时，罗布·塞尚盛赞了 Fundstrat 的汤姆·李（Tom Lee），称他是业内最擅长通过跨资产走势与利差变化“预见拐角处风景”的数据大师。不过，汤姆·李近期提出的一点让市场有所警惕：他预测今年年中可能会出现一次“把所有人都吓个半死”的回撤。如果发生超出市场预期的突发事件，很容易引发资金的过度抛售反应。但与那些深陷头条战争叙事、盲目推演二阶和三阶负面效应的悲观者不同，汤姆·李始终专注于高品质半导体与软件板块的真实基本面数据。 ```mermaid flowchart TD accTitle: AI推动下的美股盈利传导链 accDescr: 展示从AI生产力提升到标普成分股整体盈利预期上调的传导机制 subgraph TechCore["科技核心板块"] A["生成式 AI 资本投入与技术落地"] --> B["科技板块盈利高增 (43%)"] end subgraph BroadMarket["泛市场渗透"] A --> C["各行业降本增效 / 生产力提升"] C --> D["S&P 493 盈利预期上调至 15%-16%"] end subgraph MarketReaction["市场博弈"] B & D --> E["整体市场估值获得基本面支撑"] E --> F["潜在年中突发回调 (Tom Lee 预警)"] end ``` --- ### [21:47](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1307s) 市场的盲目自满：油价下行假设与降息的潜在“毒药” 亚当·帕克分享了近期他与多位顶级风险管理官（CRO）共进晚餐时的观察。他指出，目前市场普遍存在一种危险的自满情绪——几乎所有人都理所当然地认为原油价格迟早会大幅回落，而且回落速度会很快。正因如此，分析师们完全没有在工业制造或对能源敏感的消费板块模型中计入原材料成本上涨的压力。在地缘政治与霍尔木兹海峡局势上，投资者患上了“狼来了”的麻木症，没人愿意因为防范尾部风险而过早降低风险敞口（Risk-off），生怕再次错过反弹。 对于美联储的货币政策路径，嘉宾们提出了反共识的质疑：在当前阶段降息真的还能像过去那样提振估值乘数吗？如果通胀预期居高不下，贸然降息甚至可能引发剧烈的通胀失控风险。在讨论中，所有人一致同意：对大部分市场参与者而言，油价跌回 3 美元区间所带来的确定性利好，远胜过美联储再降息 25 个基点。回顾 2022 年底，当英伟达（Nvidia）、特斯拉（Tesla）和 Meta 从高点回撤 65% 时，市场押注加息周期见顶、降息释放流动性是绝对正确的；但在三年后的今天，如果美联储突然释放鸽派信号，很可能不再是“政策红利”，而是意味着经济出现严重失速的“增长恐慌”（Growth Scare）。 - 市场的潜在盲点：普遍押注能源价格走低，未对工业和消费股计入输入型通胀风险。 - 资产配置启示：在投资组合中配置部分能源股，是防范地缘政治与通胀再度抬头的有效尾部对冲。 - 降息预期演变：周期后期的预防式降息容易被市场解读为经济基本面恶化的信号，而非估值扩张的助推剂。 --- ### [24:36](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1476s) 半导体狂欢是否失控：美光、英伟达与分析师预期的极限错判 谈话进入高潮，乔什·布朗（Downtown Josh Brown）提出了一个尖锐问题：“半导体板块的这轮狂欢，是你们见过最失控的行情吗？”他列举了惊人的数据：在过去短短 16 个交易日内，半导体 ETF（SMH）暴涨了 35%，创下了该 ETF 历史上任意 16 天滚动收益率的最高纪录；美光科技（Micron）的市值甚至一举超越了医疗巨头强生（Johnson & Johnson）。 曾经担任半导体分析师的亚当·帕克却给出了不同的视角： > “不，我认为这并不算失控，甚至完全是有基本面支撑的。” 帕克剖析指出，半导体板块的内部结构极具分化。如果不持有美光这类股票，投资者的科技组合往往会显得增速偏慢且估值昂贵；因为美光虽然具有周期性，但其交易倍数仅为明年预期收益的 4.5 倍左右，而增速却逼近 100%。 谈及半导体板块何时见顶，帕克引用了一句形象的华尔街警句：“掉下来的钢琴从来不会迎面砸中你的脸，它们总是从脑后砸下来。”换言之，风险总在市场最意想不到的时候降临。针对英伟达，乔什指出英伟达在过去连续四个季度利润大幅超预期，但股价有时却并没有跟随利好即刻暴涨。帕克回应称，英伟达明年的每股收益（EPS）预期已经从财报公布前的约 50 美元被华尔街一路大幅上调到了近 100 美元。Trivariate Research 目前的一项深度研究表明：在美股历史上，凡是那些最终业绩比分析师两年前的早期预测高出最多的公司，往往正是长周期内表现最惊艳的超级牛股。 - SMH 创纪录暴涨：在 16 个交易日内涨幅达 35%，创下该 ETF 历史最佳滚动表现。 - 美光科技估值倒挂：在业绩预计增长 100% 的同时，远期市盈率仅约 4.5 倍。 - 英伟达业绩预期翻倍：分析师对英伟达下一财年的每股收益一致预期从约 50 美元翻倍修正至约 100 美元。 ### [26:43](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1603s) 自由现金流预期巨变与软件股的“惨案”：ServiceNow 的缩影 嘉宾们首先回顾了市场上令人瞠目结舌的自由现金流（FCF）预测偏差。在过去长达 25 年的市场经历中，这种幅度的调整都堪称罕见：原本市场对接下来两年的自由现金流预期仅仅是 15 亿到 35 亿美元左右，随后却被硬生生拔高到了 800 亿美元级别，量级上差了几个零，这种此前无人料到的剧变彻底颠覆了资金的定价模型。紧接着，话题转向了近期遭遇惨烈抛售的软件板块。迈克尔·巴特尼克（Michael Batnick）提出疑问：既然许多软件公司的基本面依然稳健，为什么市场会如此绝情？ 以企业级软件巨头 ServiceNow 为例，巴特尼克调出数据指出，年化合同价值（ACV）超过 500 万美元的超级大客户数量，从早前的 434 家猛增至今年第一季度的 630 家，客户净留存率高达惊人的 97%，当季营收增速也稳稳达到 22%。然而，由于未来利润率指引出现松动与下滑，该股在当日盘中暴跌 18% 至 20%。巴特尼克直呼这种走势“令人胆战心惊”：一家质地极佳、营收稳健达标的公司，在此前已经从高点腰斩 50% 的背景下，仅仅因为利润率展望不及预期，单日市值就能再次蒸发五分之一。 - **ServiceNow 超级客户激增**：ACV 超 500 万美元的企业客户数从 434 家跃升至 630 家。 - **高忠诚度与稳健增长**：客户留存率维持在 97%，营收同比增速维持在 22%。 - **市场残酷杀跌**：利润率展望下滑导致股价单日暴跌 18%~20%。 --- ### [28:12](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1692s) 对冲基金与做多机构的博弈：为什么营收达标依然遭遇暴跌？ 针对软件股的溃败，亚当·帕克（Adam Parker）从机构投资者的交易结构进行了深度剖析。他指出，首先必须区分长多机构（Long-only）与对冲基金（Hedge Funds）：对冲基金完全有自由避开整个软件板块，甚至直接做空；但对纯做多基金经理而言，他们就像必须造车的通用汽车一样，必须在软件基准指数中挑选赢家与输家。在财报表现的“四象限矩阵”（营收超/不及预期 × 利润超/不及预期）中，ServiceNow 恰恰落入了市场最痛恨的那个象限——“营收达标甚至超预期，但利润率不及预期”。这直接击穿了市场对该公司远期利润率锚点的信心，投资者不得不对 2030 年的长期盈利能力进行下调重新定价。 ```mermaid flowchart TD accTitle: 财报四象限与市场反应 accDescr: 展示财报中营收与利润表现对股价影响的四象限分析，突出营收达标但利润暴跌的杀伤力。 subgraph Matrix["财报表现四象限分析"] A["营收超预期 + 利润超预期<br/>最佳：获得估值溢价"] B["营收超预期 + 利润不及预期<br/>最差：利润率锚点崩塌（ServiceNow 案例）"] C["营收不及预期 + 利润超预期<br/>中性偏防御：控本保利"] D["营收不及预期 + 利润不及预期<br/>双杀：估值与基本面全线出清"] end B --> E["市场惩罚机制极度严苛<br/>未见利空出尽反弹，单日跌幅达 18%-20%"] ``` 帕克进一步强调，当前市场的惩罚机制处于极度失衡的状态。过去在健康的调整中，常能看到类似卡特彼勒（Caterpillar）业绩不及预期但股价“走平（unchanged）”的现象，这往往是“坏消息出尽、买点已至”的信号；但如今市场上只要有公司业绩暴雷，迎来的便是直接“歼灭”，甚至估值原本很便宜的股票在不及预期时跌得比高估值股票还要惨烈。乔什·布朗（Josh Brown）插话问道：“这难道不是典型的筑顶（toppy）市场特征吗？”帕克承认这确实反映了市场深层的脆弱，虽然目前多数公司业绩仍能超预期支撑大盘，但只要不及预期的比例稍微扩大，整个市场的估值体系就将面临严峻考验。 - **财报四象限的最差落点**：营收达标但利润率不及预期，暴露出长期利润率的不确定性。 - **奖惩比例极度扭曲**：超预期的奖励有限，不及预期的惩罚极其严苛；便宜股票的补跌幅度甚至超过高估值成长股。 - **缺乏“利空不跌”的安全垫**：以往蓝筹股业绩失误但股价走平的见底信号在当前市场完全缺席。 --- ### [30:18](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1818s) 科技股估值骤降至19倍：狂飙的“E”与双雄挑大梁 乔什·布朗在屏幕上展示了一张科技股远期市盈率（Forward P/E）走势图，带领听众梳理科技板块过去几年的估值压缩轨迹：在 2020 年疫情初期，科技股远期市盈率仅为 16 倍；随后在 2021 年的流动性狂欢中触顶至 28.7 倍；在经历 2022 年“效率之年”的挤泡沫后跌至 18.5 倍低点；此后一路反弹，并在 2024 年创出 32 倍阶段性高位；进入 2025 年初先降至 21 倍，年底再次冲至 31 倍；然而目前该指标迅速滑落至 19 倍左右。面对这种突如其来的估值压缩（De-rating），主持人们展开了热烈讨论：这究竟是市场给出的估值折价，还是盈利分母（E）暴增造成的“被动压缩”？ 罗布·塞尚（Rob Sechan）一针见血地指出，这主要是由于盈利预测被大幅上调所致——例如美光（Micron）的盈利预期直接飙升了 100%，科技板块今年预期利润增速高达 43%。塞尚还抛出了一个极具震撼力的重磅数据：对比标普 500 指数 2026 年第一季度与 2025 年第一季度的同比增长，整个标普 500 指数全部盈利增量的 45% 竟然仅由美光（Micron）和英伟达（Nvidia）两家公司贡献！他分析道，如果地缘政治风险导致整体经济增速放缓，全市场能够实现真正增长的标的将变得更加稀缺，资金最终仍会心甘情愿为这两家巨头的确定性高增长支付高昂溢价。 - **科技股估值大起大落**：远期 PE 从 2024 年的 32 倍快速下行至当前的 19 倍。 - **分母端“E”的狂飙**：科技板块利润增长预期达 43%，美光等多家芯片巨头预期翻倍。 - **双巨头撑起半边天**：标普 500 指数同期全部同比增长中，英伟达与美光合计贡献了高达 45% 的盈利份额。 --- ### [32:12](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1932s) 战火中的“阶梯式下行”：为何没有恐慌反成买入良机？ 布朗向塞尚发问，在遭遇地缘冲突爆发期间，美股呈现出一种奇特的“阶梯式阴跌”，市场始终没有出现集中的恐慌性抛售或崩盘（puke），这种盘面语言该如何解读？塞尚毫不犹豫地表示，这种波澜不惊的走势反而让他“更加看多”。正因为市场没有陷入流动性枯竭式的踩踏，反而让他们在整个调整期间保持了高仓位运作，并将这种可控的波动视为优化组合、将资金向高质量标的集中的天赐良机。 塞尚分享了他们团队的实战纪律：作为自上而下对标基准的纯多头或相对收益投资者，许多顶级股票在平时估值高企时根本无法下手。例如英伟达，他们团队此前长期坚守纪律，在其远期市盈率高于 30 倍时一股不买，虽然因此错过了前期的部分涨幅，但当市场出现可控回撤、英伟达估值首次跌入 30 倍以内时，他们果断大举建仓，迎来了极为丰厚的回报。塞尚与布朗一致认为，源于地缘政治的波动通常会维持在理性区间内，而只有源自金融体系内部的严重信贷危机，才会引发那种深不见底的自由落体式崩盘。 - **阶梯下行释放积极信号**：缺乏恐慌性抛盘表明市场内部承接力强韧，而非系统性崩溃。 - **纪律性升级持仓质量**：利用估值回踩将筹码置换到受冲击最小、抗风险能力更强的行业龙头。 - **买入英伟达的估值锚**：坚守估值准绳，耐心等待英伟达远期市盈率回落至 30 倍以下才进场重仓。 --- ### [33:49](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2029s) 私募信贷的隐忧：黑石募资腰斩与资本结构的安全垫 讨论进一步深入到潜在的金融隐患——私人信贷（Private Credit）。尽管市场上对于私募信贷坏账的担忧甚嚣尘上，但塞尚依然坚定捍卫其底层的股权资产与宏观韧性。他指出，底层企业的经营状况依然良好，私募股权投资机构（PE sponsors）绝不会轻易抛弃这些业务。更重要的是，在资本结构（Capital Stack）中，私人信贷绝大多数位于最顶层的优先顺位，只有当底层的巨额股本与次级债务被完全抹平之后，信贷资金才会真正受到实质性冲击。此外，公开市场的信用利差始终保持平稳，并没有发出警报。 然而，真正的潜在瓶颈并非现有的存量信贷质量，而是未来的流动性补充。如果私募机构向个人及财富管理端募集资本的能力受损，依赖持续融资扩张的轻资产策略将受到沉重打击。虽然机构端资金依然留存，但在募资放缓的背景下，资金分配将更加挑剔苛刻，“强者愈强”的分化格局将进一步加剧。布朗适时调出黑石（Blackstone）的最新财报走势，当天黑石股价重挫 6%，图表显示其私人信贷的总募资额已从峰值近乎腰斩，降至单季约 33 亿美元。塞尚对此坦承，虽然他的团队此前出于税务亏损收割（Tax-loss harvesting）的目的减持了黑石并受到过质疑，但他对这类资产管理龙头的长期价值依然认可，并准备在合适时机重新买回。 - **资本结构的安全边界**：私人信贷处于资本结构最优先级别，拥有厚重的底层股本作为安全垫。 - **募资端遭遇“倒春寒”**：散户与财富端募资放缓，黑石单季总募资规模降至 33 亿美元，股价单日跌逾 6%。 - **生存分化加剧**：资本紧缩倒逼资金集中于最强玩家，弱势企业融资成本激增。 ### [35:58](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2158s) 逆向投资与私募信贷：拥抱风暴还是买入GP股票？ 围绕私募信贷（Private Credit）市场的讨论仍在继续。数据显示，资本流入速度从上一季度的峰值大幅放缓至 19 亿美元，但嘉宾们澄清这仅代表新增规模放缓，并非资金净流出。媒体铺天盖地的悲观叙事成功吓退了正准备配置资金的投资者。Rob Sechan 指出，面对市场动荡，绝大多数投资者的本能是回避，而优秀顾问的核心价值在于“迎着暴风雨前行”（steer into the storm），寻找未来预期回报率正在走高的领域。他举了此前科技创投危机的例子：当一级市场初创公司估值大幅缩水、难以完成股权融资时，市场迅速转向风险债权（venture debt）；当时那些敢于买入风险债权的人，最终斩获了极高的远期回报。 ```mermaid flowchart TD accTitle: 私募信贷情绪与资产定价分歧 accDescr: 展示媒体负面叙事如何影响资金流，以及底层资产与GP股票之间的性价比分歧。 subgraph Narrative["舆论与情绪驱动"] A["媒体悲观叙事发酵"] --> B["投资者与资金配置放缓"] B --> C["底层信贷资产溢价并未明显打折"] end subgraph Opportunity["另类资产配置逻辑"] D["底层私募债产品<br>仍按面值1:1交易"] E["另类资管巨头股票<br>黑石/KKR股价腰斩"] C --> D C --> E E --> F["买入GP股票优于买入底层产品"] end ``` 如果《华尔街日报》头条刊登“杠杆贷款价格暴跌 20%”，媒体的意图是抨击私募信贷泡沫破裂，但 Josh Brown 直言自己反而会欣喜若狂，因为那正是绝佳的买入窗口。然而对于普通理财顾问而言，要说服客户买入报纸头条正在口诛笔伐的资产，难度堪比登天。尽管 Blackstone（黑石）的高管们自掏腰包数千万美元大举回购自家股票和产品，但外界依然质疑不断。 Adam Parker 对此给出了极其尖锐的视角：他更倾向于直接买入 GP（普通合伙人，即资管机构本身）的股票，而不是去买底层的信贷产品。他打趣道，一年前看到某私募信贷项目承诺“无杠杆 13% 的收益率”，他第一反应是：“到底是谁需要以 13% 的无杠杆成本向我借钱？难道是加州橙县的美甲店吗？”这种底层算账根本站不住脚。更关键的是市场定价分歧：底层信贷产品依然按面值 1:1 交易、毫无折扣可言，而像 Blackstone 和 KKR 这样的资管巨头股票此前却被腰斩。因此如果着眼于未来两年，在 GP 层面抄底上市公司股票显然比买底层信贷资产划算得多。 ### [39:53](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2393s) 虚假的高点？打假“市场广度”指标与宏观择时陷阱 随着美股再次刷新历史新高，市场上出现了一种担忧情绪：虽然标普 500 指数创出新高，但创下 52 周新高的成分股比例却不足 5%。Michael Batnick 展示了来自 SentimenTrader 创始人 Jason Goepfert 的历史统计：在指数创下单月首个历史新高、且创新高个股比例不足 5% 的情况下，后市表现往往偏弱或呈现震荡下跌——后 1 个月上涨概率仅为 33%，后 2 个月为 33%，后 3 个月为 42%。该统计覆盖了 1929 年、1983 年、1990 年、1993 年、1995 年、2015 年和 2020 年等多个历史样本。 Adam Parker 对这种“市场广度”（Breadth）指标嗤之以鼻，毫不留情地予以反驳。他指出： - **缺乏统计学显著性**：将 1929 年的市场结构与当今高度集中的市场生搬硬套毫无意义； - **广度指标本质上是波动率指标**：无论是以 VIX 恐慌指数、均线交叉还是广度指标来做短期择时，长期来看只会毁灭投资组合的价值； - **过度集中是现实**：当前指数本身就由少数超级权重股驱动，仅凭“上涨个股数量少”就做出 1 个月维度的看空预测，胜率极低。 Josh Brown 也补充道，普通投资者往往拿这类指标当借口，来合理化自己内心早已做出的恐慌决策。现实的铁律是：每当真正的买入机会降临时，没有任何客户会愿意入场。顾问的核心任务是帮助客户“留在牌桌上”（stay in the game）。Rob Sechan 指出，正因为指数权重过度集中，纯粹选股的容错空间被严重压缩，必须借助量化模型将基本面因素与技术面特征结合起来，才能在波动的两端占据有利位置。 ### [43:06](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2586s) 半导体 vs 四大传统行业：AI 资本狂潮与估值天花板 Michael Batnick 接着抛出了由 Strategas 的 Todd Sohn 绘制的另一张重磅对比图表：当前标普 500 指数中，半导体板块的市值占比已经飙升至 16%，而能源（Energy）、医疗健康（Healthcare）、必需消费品（Consumer Staples）和公用事业（Utilities）四大板块合计的市值占比不过 19%，两者几乎呈现“针尖对麦芒”（touching tips）的胶着态势。Michael 质疑，如果把这四大行业的实际净利润加总（尤其是庞大的医疗健康板块），其盈利体量理应远远碾压半导体板块，目前的估值倒挂是否已经脱离理性？ Adam Parker 犀利反问：“为什么这就不理性了？”他强调，股票价格从不完全反映当前的静态利润，而是由远期业绩指引（forward guidance）以及对 2030 年终局分布的预期所驱动： - 现在的标普 500 已经演变成一个高度倾向科技和 AI 的结构性指数，“八大巨头”（Great Eight，即传统七巨头加上 Broadcom）独占约 35% 的权重； - 整个指数有接近 60% 的仓位可以被视为广义的“AI 或半导体衍生 ETF”——连 GE Vernova、Vistra、Constellation Energy 等公用事业/能源公司，以及 Eaton（伊顿）这类工业巨头，本质上都在享受 AI 数据中心电力与基建的溢价； - 市场追捧半导体而抛弃传统能源股完全情有可原，因为半导体行业拥有持续上调的业绩预期。 当被问及这轮半导体牛市的上限（upward bound）在哪里时，Adam 给出了一个精准的研判标准：“当市场一致预期被证实定得太高的前六个月，就是见顶之时。”在热烈讨论中，嘉宾们也笑称 Adam 对同行研究图表的批驳向来毫不手软，尽管大家私下都是 Strategas 和 Todd Sohn 优质研报的忠实读者。 ### [45:15](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2715s) 半导体估值迷局与“止盈”的交易心理学 Adam Parker 谈到半导体板块时表示，眼前的市场远不是他经历过最疯狂的阶段。真正让他觉得诡异的是那些“零营收却被炒上天”的公司，而像美光科技（Micron）这样的企业，其远期市盈率仅为下一年度盈利的 4.5 倍；美光的盈利预期在短短几周内翻倍上调，核心产品面临肉眼可见的短缺，几乎所有产品不依赖存储芯片都无法生产。面对这种局面，主持人们探讨起买卖双方如何在极端动能下寻找平衡：投资者常常由于“股价涨得太高”而害怕上车，但价格趋势一旦启动，就像物理学中的惯性一样，在遇到外力阻断前会持续沿着既有轨迹运行。 Downtown Josh Brown 随即指出散户甚至专业投资人身上常见的通病——盲目“止盈”（taking a profit）。散户总是骄傲地宣称“落袋为安总没有错”，Josh 戏谑地反驳道：“当然有错，你还得交税呢！”他观察发现，很多被卖掉的股票走势都是稳健的“阶梯式上行”，如果持仓感到焦虑，完全可以挂一个 10 日均线跟踪止损（trailing stop loss），让市场行情自然把你带出局，而不是武断地在某一天凭感觉斩断利润。Adam Parker 赞同这一观点，建议大家在事后做真实复盘（ex-post evaluation）：评估这笔卖出决策在经 Beta 调整后相比可比资产组合究竟是创造了价值还是摧毁了价值。 讨论随后延伸到动量与均值回归的本质：到底该买刚刚翻倍的股票，还是该抄底暴跌 50% 的标的？Josh 强调关键不在于过去的绝对涨幅，而在于上涨的“速率”与形态。对于一周内从 30 美元翻倍到 60 美元的狂暴抛物线走势，他绝不会追高，因为那很可能是 Reddit 散户抱团或逼空制造的迷因行情（meme stock），容易沦为最后的接盘侠；相反，对于耗费时间、由机构资金耐心推升而呈现平稳爬坡（grind higher）的图表，即便已经涨幅巨大，依然是极具吸引力的做多标的。 - **美光估值与基本面**：远期市盈率约 4.5 倍，下财年盈利预期近期上修达 100%，核心产品供应处于全面短缺状态。 - **动量与止损哲学**：主张顺应趋势动能，使用短期跟踪止损（如 10 日均线）保护浮盈，避免人为择时导致的“踏空大牛股”。 - **形态偏好区别**：警惕几天内翻倍的抛物线脉冲走势，聚焦机构长周期建仓推动的平稳上行资产。 --- ### [48:18](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2898s) 分拆战术手册（The Spinoff Playbook）与投行逻辑 话题转向 Adam Parker 旗下 Trivariate Research 的最新研究报告——《分拆战术手册》（The Spinoff Playbook）。Josh 援引报告中的核心数据：2025 年企业分拆交易的中位数规模达到了 33 亿美元，在 11 笔交易中创下了 26 年以来的历史最高纪录；年内已有 Comcast 成功分拆其有线电视资产 Versent（主持人调侃“就是你我都去录节目的那个频道”），此外 Madison Square Garden Sports（MSGS）与 Genuine Parts Company（GPC）等多家公司已宣布分拆计划，另有 20 起已宣布的分拆方案仍在推进中，其中 6 家属于中盘股或大盘股。 ```mermaid flowchart LR accTitle: Spinoff Value Unlocking Process accDescr: Diagram illustrating corporate spinoff drivers, structure separation into RemainCo and SpinCo, and market outcomes. subgraph CorporateAction["母公司动因"] Tax["税收优势 / 规避直接出售重税"] Value["估值释放 / 聚焦主业"] end CorporateAction --> Split["分拆执行 (Spinoff)"] subgraph MarketEntity["分拆架构"] RemainCo["母公司保留业务 (RemainCo)"] SpinCo["新独立分拆实体 (SpinCo)"] end Split --> RemainCo Split --> SpinCo SpinCo --> Alpha["合理盈利指引 + 利润率扩张预期 + 跑赢母公司"] ``` Josh 回忆起自己早年做零售经纪人（retail broker）时的兜售套路：当年向客户打电话推销分拆概念几乎百试不爽，最经典的论调就是“你持有 3Com，猜怎么着？你还能免费拿到 Palm 的股票！”客户沉迷于催化剂，以为自己是“花一份钱白得两只股票”，根本意识不到除权日母公司股价会自动折价调整。Adam 补充道，从量化角度看，散户对“低绝对价格”存在一种莫名偏好，潜意识里觉得 2 美元的股票比 4 美元更有吸引力。 对于企业为何热衷于分拆，Adam 分析指出： 1. **税务优化**：直接出售子公司（例如摩根士丹利早年出售其大赚特赚的 Discover 信用卡业务）需要缴纳巨额资本利得税，而合规分拆则享有极大的税收豁免。 2. **释放隐藏价值**：大集团内部具有高成长或特定资产属性的子公司长期被市场忽视或给予估值折价。 3. **独立治理与资本结构优化**：分拆后 SpinCo 拥有独立的管理团队和激励机制，不必再在母公司庞杂的内部流程中争夺资本预算。 --- ### [50:54](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3054s) SpinCo 跑赢 RemainCo 的实证与人类分析师的 Alpha 在具体实证表现上，Adam Parker 明确指出历史数据显示：**被分拆出来的新公司（SpinCo）平均表现通常优于母公司原主体（RemainCo）**。这一方面是因为投行和管理层在运作分拆上市时，通常会给出相对保守、极易达成的未来几个季度业绩指引；另一方面，新公司往往具备清晰可见的利润率扩张路径。对于市值在 200 亿至 500 亿美元之间的上市公司董事会与管理层而言，若想实现迈向千亿美元市值的蓝图，分拆正是展示资本配置能力、为股东释放价值的核心手段。 现场嘉宾回顾了近年来的多起经典超级大牛股案例： - 从辉瑞（Pfizer）分拆出的动物保健龙头硕腾（Zoetis）。 - 从通用电气（General Electric）分拆出的能源装备巨头 GE Vernova（GEV），成为近期市场上的超级超级大牛股（“monster”）。 - 联合技术公司（United Technologies / UTX）在分拆为开利空调（Carrier Global）与奥的斯电梯（Otis Worldwide）后前 12 个月的惊艳走势。 Adam 总结强调，在量化与机器算法主导的高频与规则交易领域，人类分析师很容易被全面碾压；但面对涉及公司治理、并购（M&A）以及资本重组等复杂的管理层重大决策时，机器模型往往无法有效推演价值重塑或价值毁灭的微妙变化。通过深入研究分拆背后的业务肌理与治理逻辑，人类分析师与主动选股者依然能够在纷繁的市场中捕获扎实的超额收益（Alpha）。 ### [53:53](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3233s) 分拆上市（Spinoff）的超额收益规律 Adam Parker 深入展示了 Trivariate Research 关于分拆上市（Spinoff）的量化研究成果。历史上这类分拆交易每年能有 20 到 30 起，而近期只有寥寥几笔，未来可能迎来新一轮分拆浪潮，且通常发生在由中盘股主导的场景，而非巨头级公司。为了排除某些极端个股（例如表现亮眼的 SanDisk）对整体结论的干扰，该研究引入了“行业相对收益均值”进行归一化测算。 图表清晰地展示了被分拆出的独立新公司（SpinCo）与母公司留存业务（RemainCo）截然不同的命运轨迹。从交易日跨度来看，在分拆发生后的两年（约 504 个交易日）内，新分拆公司（SpinCo）的平均表现能跑赢其所在行业基准整整 10%，而母公司留存业务则平均跑输行业两到三个百分点。主持人 Josh 与 Michael 惊叹于这组数据在统计学上的显著性与跨行业的稳健性。 ```mermaid flowchart TD accTitle: 拆分上市相对行业收益走势 accDescr: 展示分拆公司（SpinCo）与母公司留存业务（RemainCo）分拆后两年的相对行业超额收益对比。 subgraph 拆分后两年表现 A["发生公司拆分"] --> B["新分拆公司 SpinCo"] A --> C["留存母公司 RemainCo"] B --> D["跑赢行业基准 +10%"] C --> E["跑输行业基准 2% - 3%"] end ``` - **分拆公司（SpinCo）两年前景**：平均超越行业基准 10%，超额收益显著。 - **留存母公司（RemainCo）走势**：平均落后行业基准几个百分点。 - **标的特征与趋势**：主要集中在中盘股，未来有望出现密集的分拆落地潮。 --- ### [55:04](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3304s) 夏季精选股组合：双板平衡与多重期权策略 话题转到 Rob Sechan 及其 NewEdge 投研团队（包括 Jay Peters、Cameron Dawson 和 Brian Nick）为即将到来的夏季制定的核心持仓。面对主持人们“是不是春天就不灵了”的调侃，Rob 解释道，这套组合并非追求机械的时间精准度，而是采用了一种“双脚踩在不同雪板上”的平衡投资架构：既拥抱当前处于历史新高、最受追捧的高确信度 AI 赢家，又配置了受益于 AI 算力电力瓶颈的公用事业股，同时搭配对冲中东地缘局势的能源生产商，以及防御属性兼备医疗 AI 潜力的优质药企。 该组合精选了五家具有代表性的标的： 1. **博通（Broadcom, AVGO）**：定制化芯片（Custom Silicon）与数据中心网络基础设施的无可争议之王，直接受益于超大规模云计算厂商（Hyperscalers）资本开支的飙升。公司今年营收增速有望达 60%，享有业内领先的利润率。Rob 直言“运动中的物体会保持运动”，且早在 2023 年 4 月它以十几倍市盈率低估交易时市场犯了错，如今重估完全合理。 2. **泛林集团（Lam Research, LRCX）**：半导体制造设备领域的准垄断龙头。Josh 指出该股在过去一年暴涨了 297%，甚至在团队去年 8 月高位推荐后又逆势翻倍，展现了设备股难以替代的产业壁垒。 3. **NRG Energy（NRG）**：AI 算力爆发背后的电力瓶颈衍生受益者。NewEdge 在持有的 Vistra 经历史诗级暴涨后选择止盈部分资金，转而配置估值更为便宜的 NRG（目前市盈率约 16 倍）。NRG 具备将天然气直接转化为数据中心所需电力的能力，并通过创新的“自备电力”（Bring Your Own Power, BYOP）模式直接向数据中心售电。 4. **阿帕奇石油（APA Corp, APA）**：传统油气勘探生产（E&P）标的，年初至今上涨 58%，当前较前期高点回调约 14%。该标的不仅具备遍布各区域的多元化资产组合，更是对冲中东危机升级与通胀的天然工具。其市盈率仅为 7 倍，且通过股票回购与分红提供了高达 12% 的综合股东回报率（Total Yield）。 5. **吉利德科学（Gilead Sciences, GILD）**：兼顾防守与稳健质量的医疗权重股。吉利德在 HIV 领域处于垄断地位，肿瘤学领域进展亮眼，手握处于各研发阶段的 50 款储备药物。其稳固的管线成长性能够有效平抑组合波动。 --- ### [01:00:32](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3632s) 医疗保健板块的 AI 错配与价值重估辩论 讨论随后聚焦到医疗保健（Healthcare）板块近期的极端低迷。主持人与嘉宾们发问：为何在全市场都在炒作 AI 赋能的当下，医疗板块作为未来 AI 降本增效最大的潜在受益者，却得不到市场的任何估值溢价？ Adam Parker 坦承，长期超配医疗板块是 Trivariate 目前“表现最糟糕的策略之一”，但他依然坚定持有该逻辑，并拒绝放弃这一核心假设： > “市场目前给出的定价意味着，未来 5 年医疗保健成为标普最佳板块的概率是 0%；但我认为这一概率至少有 30% 到 40%。我就是想套利这种预期差。整个人类科技进步的核心目的，就是让我们活得更长、活着的时候更有生产力。” Adam 从基本面拆解了看好医疗股的底逻辑： 1. **长期稳定的营收增长**：在标普 500 指数中，医疗行业的每股营收已经连续三十多年保持正增长，老龄化趋势催生了对诊疗、耗材、药物和住院服务的刚性刚需。 2. **极大的 AI 效率提升空间**：医疗行业充斥着大量雇员规模庞大、营收巨额但净利率极低的企业。过去检验科医生还在用老式显微镜逐个切片人工分析，只要 AI 能够介入并预测客户与员工行为，利润率就存在巨大的扩张潜力。 3. **与半导体低相关性的避险属性**：除了表现亮眼的礼来（Eli Lilly）等药企，分销与服务巨头如麦克森（McKesson）、卡地纳健康（Cardinal Health）、信诺（Cencora）、奎斯特诊断（Quest Diagnostics）以及 Labcorp 的业务增速必然超越 GDP。 最后，Adam 还风趣地拿健康管理组织（Managed Care）举例证明其强大的商业定价权：“我自己就是开公司的，你知道每年谁把保费硬生生提高 9% 吗？而且他们可绝对没有多给我提供 9% 的服务。这类企业未来只会赚取更多的利润。” ### [01:02:40](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3760s) 医疗投资的远期愿景与大型药企格局 嘉宾们延续了此前关于医疗板块的探讨。面对医疗支出的增长曲线，嘉宾指出到 2030 年之前，政界两党都没有任何政治意愿去改变现有的支出算法或推行大规模的财政紧缩；除非未来有执政党推行激进的紧缩政策，否则这一趋势难以逆转。关于选股方向，讨论聚焦于医疗是否应避开大型药企（Big Pharma）。 分析认为大型药企中依然存在优秀标的（例如表现惊艳的礼来 Eli Lilly），但目前的布局策略更看重五年的远景回报。当下的策略是在市场形成共识前超额配置，待五年后散户涌入所谓的“计算化学”（computational chemistry）ETF 等热门概念、市场情绪陷入狂热 Euphoria 之际，顺势将持仓卖出获利。不过，要实现这一理想策略，中间还需要经历漫长而扎实的发展阶段。 --- ### [01:03:17](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3797s) 走出传统大行：NewEdge 的创立与 RIA 行业的真实生态 Downtown Josh Brown 将话题引向 Rob Sechan 创立的独立财富管理机构 NewEdge Wealth，并邀请 Adam Parker 一同探讨独立投资顾问（RIA）行业的演进。Josh 回忆最初认识 Rob 时，Rob 还在瑞银（UBS）管理着全公司规模最大的财富管理团队之一。五年前，Rob 毅然离开传统华尔街大行投身独立财富管理赛道，如今管理规模已从初期的 80 亿美元一路狂飙至 1,050 亿美元。 ```mermaid flowchart TD accTitle: NewEdge Scale and Advantage Model accDescr: 展示 NewEdge 如何利用杠杆收购打下底座并获取中立买方优势的结构图 subgraph Acquisition["基础设施底座 (LBO)"] A["收购 401(k) 基础设施业务<br/>(原服务富达/培基等机构)"] B["由 Parthenon Capital 联合支持"] C["自带成熟 IT 团队与充裕现金流"] A --- B A --- C end subgraph Position["结构性买方优势"] D["站在街区对立面 (Client of the Street)"] E["跨机构贷款比价<br/>(高盛 / 摩根大通 / 加拿大皇家银行)"] D --> E end subgraph Ecosystem["双轨服务平台"] F["开箱即用平台 (Turnkey Platform)"] G["独立创业孵化 (Alex Goss 执掌)"] end Acquisition --> Position Position --> Ecosystem ``` 谈及在 RIA 领域的创业心得，Rob 坦言行业现状远比表面看起来更复杂： - **市场噪音与决策瘫痪**：生态圈中充斥着各类宣称无所不能的服务商，但真正能落地的少之又少，导致许多想要从大型传统机构跳槽出来的顾问陷入观望与瘫痪状态。 - **身处中心的结构性优势**：传统大行（如高盛）的顾问只能推销自家内部的单一产品（例如做贷款只能走自家通道）；而成为独立机构后，变成了“全街的客户”（Client of the Street）而非竞争对手。在为高净值家族客户匹配大额信贷时，可以同时要求高盛、摩根大通（JPMorgan）或加拿大皇家银行（RBC）等机构竞标报价，拥有无可比拟的客观买方视角与议价规模。 - **半山腰起步的幸运（借力 LBO）**：NewEdge 并非从零白手起家。2020 年疫情期间，Rob 联手私募股权机构 Parthenon Capital 对一家深耕 401(k) 退休金基础设施的成熟企业完成了杠杆收购（LBO）。该标的原本就为富达（Fidelity）、约翰·汉考克（John Hancock）、Paychex 及 Creative Planning 等巨头提供机构级支持，不仅自带稳健现金流，还拥有一支极其过硬的 IT 技术团队。这省去了底层 IT 搭建的巨大风险，让团队得以直接站在半山腰向上攀登。 --- ### [01:07:22](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4042s) 顶尖华尔街班底与前沿科技护城河 面对想要跳出传统大行（如摩根士丹利、美银美林）的顶级顾问，最核心的顾虑在于独立后是否会失去强大的中后台支撑。为了打消这种“站在悬崖边缘跳下却看不到底”的恐惧，NewEdge 组建了一套由华尔街传奇老将构成的核心阵营： - **Chuck Warden**：被收购基础设施业务的原创始人； - **John Strauss**：曾先后掌舵摩根大通、摩根士丹利、瑞银等华尔街所有主要私人银行部门的资深高管； - **Bob McCann**：华尔街传奇人物，曾统领瑞银与美林证券（Merrill Lynch）； - **James Jesse**：前摩根士丹利国际业务主管，后与 Divesh Makan 联合创立著名硅谷财富管理机构 Iconiq Capital；去年被正式聘请担任 CEO，从而让 Rob Sechan 能够专注于发挥自身的核心业务优势； - **Cameron Dawson**：知名投资策略专家，担任首席投资官（CIO）。 在业务模式上，NewEdge 搭建了双轨体系：既提供全套合规、运营与技术“开箱即用”的一体化加盟平台，也可以由合伙人 Alex Goss 挂帅，全方位孵化赋能顾问自立门户。在技术应用层面，Rob 直言传统大行行动迟缓，目前尚无一家真正完成全面企业级 Anthropic（Claude）等领先 AI 技术的落地集成，而 NewEdge 已经实现全员部署，并深度打通了 Adam Parker（Trivariate Research）与 Tom Lee（Fundstrat）等顶尖智库的高阶智力资本。 --- ### [01:10:18](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4218s) 传统大行外逃潮初现与行业共鸣 Josh 针对行业格局提出疑问：传统大行（Wirehouse）顶级团队的出走潮，究竟是已经如火如荼，还是尚未真正爆发？Josh 列举了身边仅在一家传统大行，过去两年内就有五个管理规模超 50 亿美元的顶级合伙人团队出走独立。 Rob 认为真正的大规模迁徙才刚刚拉开序幕。过去两年来咨询与加盟的排队管线（pipeline）规模极其庞大。只要市场上能有既懂传统大行体系、又懂独立头部机构运作规律的平台出现，顾问的信心就会被彻底激活。这段激情澎湃的行业复盘与商业模式解析，让主持人与在场嘉宾赞叹不已，直呼这场兼具极高商商（EQ）与智商（IQ）的分享“电力十足”（electric），展现了顶级创业者的野心与格局。 ### [01:11:54](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4314s) 顾问本位的商业模式与创始人的角色转变 Rob Sechan 继续深入探讨 NewEdge Wealth 的核心架构与竞争壁垒。他强调，当 NewEdge 收购或引入其他顾问团队时，被收购方持有的完全是与管理层在杠杆收购（LBO）中一模一样的股权份额，绝不搞两套标准，这彻底规避了过去许多失败同行埋下的隐患。Rob 将这种策略生动地比作“维他命水（Vitaminwater）与佳得乐（Gatorade）”之争——作为后来者，拥有巨大的“后发优势（second mover advantage）”，能够精准识别并修正行业前辈犯过的错误。更关键的是，NewEdge 是一家“由顾问创立、服务于顾问（started by advisors for advisors）”的机构，天然不会制定自掘坟墓的伤害性政策。 随着企业规模迅速扩大，Rob 也清醒地认识到自身角色的边界。他直言，在处理日常繁琐事务与具体运营方面，完全可以有比他更擅长的人选，他不应将时间耗费在“一天开八场会、微观管理 50 个人”的行政泥潭中。作为公司的布道者与捍卫者，他唯一的使命是为那些相信这一愿景的顾问们创造价值——不仅体现在日常执业与客户服务中，更体现在他们所持有的公司股权增值上。“哪怕为此让我靠边站（shooting myself），我也完全不在乎。” - **股权结构统一**：合伙顾问持有的股权层级与创始合伙人在 LBO 中获得的股权完全一致，实现真正的利益绑定。 - **后发优势**：借鉴早期整合型 RIA（Registered Investment Advisor）的踩坑教训，以顾问为中心设计基础设施。 - **管理放权**：创始人将日常具体运营（nuts and bolts）移交给专业管理人才，自身专注于战略推进与资本价值创造。 --- ### [01:13:46](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4426s) 独立创业的真实代价：从洗马克杯到业务拓展 Adam Parker 对 Rob 的管理体悟深感共鸣。他打趣道，自己在打理 Trivariate Research 时也逐渐有了自知之明：每当自己坐在电脑前敲键盘，身后的量化分析师总会投来异样的目光，仿佛在说“这人根本不会用电脑，可千万别碰键盘了”。他意识到，公司最有效率的运转绝不是由他亲自下场做基础操作，AI 时代的到来更是加速了这种分工的必要性。 Josh Brown 提到，很多从华尔街大行首席策略师位置上退下来的人往往只想纯粹做研究，但 Adam 显然极其享受“从零搭建一家企业”的创业过程。Adam 坦言自己热衷于探索商业版图的各种可能——除了研究业务，Trivariate 还推出了面向大众的付费时事通讯（Trivariate Newsletter），拓展资产管理与投资者关系业务，为律所及董事会提供咨询，甚至他即将在下周正式出任一家欧洲上市公司的董事。 谈及从华尔街离职独立创业的心理落差，Adam 与主持人们分享了创业初期的真实艰辛：在大机构时虽然会有官僚病，但各种资源一应俱全；而一旦自立门户，前几年不得不“一边洗盘子，一边往三明治里抹蛋黄酱”。Josh 和 Michael Batnick 笑着回忆当年创立 Ritholtz 时甚至要亲自给信封舔胶水，Adam 则透露 Trivariate 至今没有洗碗机，平时都是他亲自动手给年轻员工们洗咖啡杯。尽管如此，所有人都一致认同独立是无比正确的抉择，Adam 感慨道：“离开大行就像搬去佛罗里达，你什么时候听过有人去了之后说‘见鬼，这里真糟糕，我想搬回去’？” --- ### [01:16:20](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4580s) 转型以太坊信徒：BMNR 与传统金融的基础设施重塑 对话随后转向备受市场关注的话题——由知名策略师 Tom Lee 推动的 Bitmine Immersion Technologies（股票代码：BMNR），以及 Rob Sechan 出任该公司首席独立董事（Lead Independent Director）的经历。BMNR 被市场视作“以太坊版的 MicroStrategy”，定位于以太坊资产储备企业（Ether Treasury Company）。Rob 坦白承认，自己过去曾坚定地认为加密货币是个彻头彻尾的“江湖骗术”，甚至多次在 CNBC 电视直播中公开唱衰。然而，在深入研究以太坊的技术逻辑并与 Tom Lee 深度交流后，他从一名怀疑论者彻底蜕变为了以太坊的布道者。 ```mermaid flowchart TD accTitle: BMNR 与以太坊价值捕获模型 accDescr: 展示 BMNR 如何通过质押收益、交易验证与生态投资实现多元于单纯持有 ETH 的收益机制。 subgraph Core["底层基础设施: 以太坊 (Layer 1)"] ETH["以太坊网络\n(可编程 / 24小时实时结算 / 绝对安全)"] end subgraph BMNR_Engine["BMNR 价值捕获层"] Treasury["ETH 资产储备"] Maven["Maven 验证节点业务\n(获取 3%-4% 质押与 Gas 费)"] Moonshots["登月投资 / 生态引流\n(如 MrBeast 合作导入网络用量)"] end subgraph TradFi_Bridge["传统金融互联"] Inst["传统机构资金 (TradFi)\n(合规化接入与资产代币化)"] end ETH --> Treasury Treasury --> Maven Treasury --> Moonshots Inst <--> BMNR_Engine ``` Rob 解释称，外界最大的误解在于把加密货币单纯看成某种投机性的代币，而它本质上是不可或缺的底层价值网络基础设施。当前的传统金融（TradFi）体系高度割裂、依赖大量中介机构、速度缓慢且无法做到 7×24 小时运行，虽然各大交易所（如纽交所）都在探索资产代币化与数字化，却普遍缺乏底层搭建能力。相比之下，以太坊提供了一个兼具安全性、可编程性与全天候实时清算的平台。当前阶段的核心逻辑已不再是二级市场投机，而是传统金融向新架构的系统性整合与迁移。 针对 Josh 提出的疑问——“如果看好以太坊，为什么不直接去买 ETH，而要买 BMNR？”——Rob 详细拆解了 BMNR 区别于单纯持币的商业模式与超额回报来源： - **质押与验证收益（Staking Yield）**：BMNR 旗下拥有名为 Maven 的交易验证业务，通过维护节点安全直接赚取 3% 至 4% 的质押收益与网络 Gas 费，使公司本质上变成了数字高速公路的“收费站（toll road）”。 - **生态引流与“登月投资”（Moonshots）**：BMNR 不仅囤积资产，还会投资能够为以太坊网络带来海量用量与曝光的项目（例如与顶级网红 MrBeast 的合作）。网络使用率越高，基础设施的商业价值就越大，股票持有者能直接分享这些生态投资带来的额外红利。 - **AI 时代的底层安全保障**：在 AI 技术快速迭代并对传统科技栈带来潜在冲击的背景下，以太坊 Layer 1 作为不可篡改的底层安全结算层，配合 Layer 2 与去中心化应用（dApps），构成了极其坚固的安全基底。 ### [01:21:06](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4866s) 以太坊的收益逻辑与 Adam Parker 的非共识预测 在讨论完 Solana 与以太坊（Ethereum）的区别后，主持人们称赞 Tom Lee 早在数年前就已看穿以太坊的经济模型本质——持有代币即可获得质押收益。随后，Michael Batnick 将话题抛给 Adam Parker，调侃他是否打算买入加密资产，Rob Sechan 则打趣称 Adam 还没有入场、但也绝不算完全出局。 然而 Adam 并没有顺着加密货币展开，而是抛出了一个截然不同的重磅观点：他预测英伟达（Nvidia）将在本年代末（2030 年底前）达到 10 万亿美元的市值。当被问及当前市值时，现场提到目前大约在 4.8 万亿美元（注：播客录制时探讨的情境），这一激进的看涨预测瞬间引爆了全场讨论。 ```mermaid flowchart TD accTitle: Nvidia Long-term Valuation Flywheel accDescr: Diagram illustrating Nvidia's competitive moat driving its path toward a 10 trillion dollar valuation. subgraph Moat["护城河壁垒"] CUDA["15年亏损研发的 CUDA 软件生态"] Base["全球不可替代的庞大装机基础"] end subgraph Expansion["全链路产业扩张"] Upstream["向上游投资锁定供应链"] Downstream["向下游算力与电力基础设施渗透"] end subgraph Growth["财务与估值目标"] Financials["年均 15% 增速 + 营收翻倍 + 强劲现金流"] Target["2030 年底目标市值: 10 万亿美元"] end CUDA --> Base Base --> Expansion Expansion --> Financials Financials --> Target ``` --- ### [01:21:46](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4906s) 英伟达是“一个独立行业”，而非单纯的一只股票 Adam 深入拆解了他为何对英伟达如此坚定。他认为市场严重误解了英伟达——不能再把英伟达当作一只单只股票来看待，它在本质上已经成为了一个独立的“行业”（Sector）。核心逻辑在于其软件与生态护城河：要脱离 CUDA 架构几乎是不可能的。在当今的 AI 领域，任何具备规模化的大模型研发都无法离开英伟达的软硬件生态。 Adam 特别指出，英伟达在 CUDA 早期连续亏损了 15 年才搭建起今天的壁垒，全球所有从事 AI 的开发者都沉浸在这一平台上。从财务角度来看，他预计英伟达未来 5 年内每年仍能保持 15% 的复合增长，营收至少将再翻一倍，且伴随极其充沛的自由现金流。他认为，每当英伟达股价陷入长达 12 个月的横盘休整期，都是在为下一波爆发蓄力，绝对是最佳买点，他一股也不会抛售。 针对现场关于“英伟达是否会启动大规模股票回购”以及当前估值处于阶段低位的探讨，Adam 表示公司更重要的举措是把巨额资金向上游和下游全产业链持续再投资。面对诸如电力短缺等基础设施瓶颈，英伟达必须主动下场确保全局顺畅。Adam 直言，外界总是拿“英伟达市值已超过整个能源、医疗或公用事业板块”来制造恐慌，但这种比较毫无意义，因为英伟达代表着推动当今时代最核心技术爆发的引擎。 - **破除看空论调**：早期空头宣称的“循环交易”已无人再提；而针对“资本开支全靠少数几家超大规模云厂商（Hyperscalers）”的质疑，Adam 反驳称像 AWS 背后实际上代表着成千上万家企业客户的真实需求，绝非单一公司的独角戏。 - **自研芯片威胁不足为惧**：对于谷歌 TPU 等竞品的蚕食担忧，Adam 认为这丝毫不影响英伟达的统治地位。长期追踪黄仁勋（Jensen Huang）25 年的投资者都清楚，英伟达庞大的开发者装机量和生态锁定效应牢不可破。 - **与标普 500 的联动**：Adam 强调，如果一个人在 3 到 5 年的时间跨度上看好标普 500，就绝不可能看空英伟达。他早在三年前就预言标普 500 指数将在 2030 年突破 10,000 点，未来四年只要实现 30%–35% 的涨幅即可达成目标，这甚至是一个相对保守的长期年化复合回报。 --- ### [01:24:32](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=5072s) 演播室插科打诨与《Halftime Report》的兄弟情义 严肃的宏观与选股讨论告一段落后，四人开启了轻松的互怼模式。Rob 笑称在节目开场讨论 Tom Lee 时，大家一直在模仿嘲笑他的口音，Josh Brown 则开玩笑问他为何说话总像华纳经典动画里的“来亨鸡”（Foghorn Leghorn）。Rob 自嘲解释道，自己在匹兹堡生活了 26 年（典型的“Yinzer”口音），后来搬到了康涅狄格州，两种截然不同的口音互相冲撞，导致发音听起来十分滑稽。 随后，Josh 提及自己与 Rob 曾在 CNBC 的《Halftime Report》节目中多次激烈交锋。Josh 动情地分享了一则从未公开过的幕后趣事：大约十三年前在 Englewood Cliffs 录制时期，有一次 Josh 并没有排期上节目，但他边看直播边就 Rob 的观点在 Twitter 上向主持人“Judge”（Scott Wapner）疯狂发推吐槽。Scott 随即给 Josh 发短信说：“你现在直接连线进来，跟 Rob 当面对质怎么样？”当时 Josh 正在亚利桑那州一家酒店的健身房里穿着运动服举铁，外面艳阳高照；他直接在健身房跑步机旁现场连线，当着所有健身路人的面与演播室里的 Rob 展开了面红耳赤的股票大辩论。 事后一位好友发短信告诉 Josh：“看到你和 Rob 在电视上为了一只股票争吵的样子，完全就像我和我亲兄弟打架一模一样。”Josh 感慨道，他们两人永远只就股票本身进行专业探讨，私底下其实胜似亲兄弟。全场在一片欢声笑语和商业互捧中迎来尾声，嘉宾们互致感谢，并向听众推荐了各自的业务主页。 - **研究与咨询机构推荐**：Adam Parker 创办的 Trivariate Research 推出了面向理财顾问和个人投资者的产品 **Trifecta Research**（定价 1,200 美元/年），专注于 ETF 深度分析、机构投资洞察与视频解读；Rob Sechan 的财富管理公司 **NewEdge Wealth** 官网为 `newedgewealth.com`。 ## Notable quotes > [07:26](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=446s) 每隔一段时间，市场上总会出现某种颠覆性的力量，硬生生把你撞进另一个完全不同的大气层。 — Rob Sechan (引用 Louis Bacon) > [07:26](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=446s) 我接下来所说的一切都有可能是错的。 — Adam Parker > [17:49](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1069s) 如果我持有的公司宣布大举招聘或扩大资本开支，我会立刻把股票卖掉。 — Adam Parker > [24:36](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=1476s) 掉下来的钢琴从来不会迎面砸中你的脸，它们总是从脑后砸下来。 — Adam Parker > [45:15](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=2715s) 当然有错，你还得交税呢！ — Downtown Josh Brown > [55:04](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3304s) 运动中的物体会保持运动。 — Rob Sechan > [01:00:32](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=3632s) 市场目前给出的定价意味着，未来 5 年医疗保健成为标普最佳板块的概率是 0%；但我认为这一概率至少有 30% 到 40%。我就是想套利这种预期差。整个人类科技进步的核心目的，就是让我们活得更长、活着的时候更有生产力。 — Adam Parker > [01:13:46](https://www.youtube.com/watch?v=0Q96NwnsiFo&t=4426s) 离开大行就像搬去佛罗里达，你什么时候听过有人去了之后说‘见鬼，这里真糟糕，我想搬回去’？ — Adam Parker ## Mentioned Adam Parker, Rob Sechan, Michael Batnick, Downtown Josh Brown, Leslie Picker, Louis Bacon, Jay Peters, Cameron Dawson, Brian Nick, Ankur Crawford, Tom Lee, Todd Sohn, Jason Goepfert, Chuck Warden, John Strauss, Bob McCann, James Jesse, Divesh Makan, Alex Goss, Jensen Huang, Scott Wapner, Public.com, Trivariate Research, NewEdge Wealth, NewEdge Capital Group, Morgan Stanley, Lehman Brothers, UBS, Goldman Sachs, JPMorgan, RBC, Parthenon Capital, ServiceNow, Adobe, CrowdStrike, Palo Alto Networks, Cadence, Synopsys, Walmart, Micron, Johnson & Johnson, Nvidia, Tesla, Meta, Blackstone, KKR, Broadcom, Lam Research, NRG Energy, APA Corp, Gilead Sciences, GE Vernova, Vistra, Constellation Energy, Eaton, Pfizer, Zoetis, General Electric, Carrier Global, Otis Worldwide, McKesson, Cardinal Health, Cencora, Quest Diagnostics, Labcorp, Eli Lilly, Bitmine Immersion Technologies (BMNR), Fidelity, Claude, Anthropic, CUDA, Ethereum, Solana, S&P 500, SMH, MrBeast ## Video description On episode 239 of The Compound and Friends, Michael Batnick and Downtown Josh Brown are joined by Adam Parker (Founder, Trivariate Research) and Rob Sechan (Managing Partner, NewEdge Wealth) to break down what’s really driving markets right now. They discuss the state of software stocks, whether the semiconductor rally has gone too far, how AI is impacting corporate profitability, and where investors can still find value in an expensive market. Plus, the spinoff playbook, favorite stock picks for the summer, and a debate on Nvidia’s path to a $10 trillion valuation. Topics covered include: -The bull vs. bear case for software -AI, margins, and earnings power -Is the semiconductor trade overcrowded? -Market structure and recent volatility -Spinoffs as an alpha opportunity -Summer stock picks: AVGO, LRCX, NRG, APA, GILD -Crypto, ETH, and Tom Lee -Can Nvidia really 10x from here? This episode is sponsored by Public. Learn more at ⁠https://public.com/compound ►00:00 - Cold Open ►05:56 - Intro ►07:26 - We Need to Talk Software ►24:33 - Is the Semiconductor Rally Out of Control? ►32:10 - How the Markets Stair-stepped Lower ►39:53 - The Markets Today ►48:18 - The Spinoff Playbook ►55:04 - Favorite Stocks of the Summer. AVGO, LRCX, NRG, APA, GILD ►01:03:16 - NewEdge ►01:16:20 - BMNR, ETH, Tom Lee ►01:21:23 - Why Nvidia is Going to 10 Trillion Dollars 👕 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 #nvidia [Source](https://www.youtube.com/watch?v=0Q96NwnsiFo)

[7:26] Rob Sechan (引用 Louis Bacon): 每隔一段时间，市场上总会出现某种颠覆性的力量，硬生生把你撞进另一个完全不同的大气层。 [7:26] Adam Parker: 我接下来所说的一切都有可能是错的。 [17:49] Adam Parker: 如果我持有的公司宣布大举招聘或扩大资本开支，我会立刻把股票卖掉。 [24:36] Adam Parker: 掉下来的钢琴从来不会迎面砸中你的脸，它们总是从脑后砸下来。 [45:15] Downtown Josh Brown: 当然有错，你还得交税呢！ [55:04] Rob Sechan: 运动中的物体会保持运动。 [60:32] Adam Parker: 市场目前给出的定价意味着，未来 5 年医疗保健成为标普最佳板块的概率是 0%；但我认为这一概率至少有 30% 到 40%。我就是想套利这种预期差。整个人类科技进步的核心目的，就是让我们活得更长、活着的时候更有生产力。 [73:46] Adam Parker: 离开大行就像搬去佛罗里达，你什么时候听过有人去了之后说‘见鬼，这里真糟糕，我想搬回去’？

[24:33] Rough order of magnitude, people had like a billion and a half in free cash flow for next year, and it was like three and a half billion over two years—and now it's 80 billion over the two. The magnitude is like zeros off. [32:10] Rob Sechan: We didn't have a panic. We went lower... That's actually what kept us invested completely through that. [32:10] Rob Sechan: We never owned Nvidia until it traded below 30 times earnings. We waited... but boy did we buy it at the right time. [39:53] Adam Parker: I don't think this kind of stuff is helpful for predicting subsequent return. This is not statistically significant... I can empirically show you that any kind of breadth metrics do not effectively help you make money. [39:53] Adam Parker: If you gave me a thousand of these charts over the next few years, I'll take the under more than 500. [60:06] Adam Parker: The whole point of all of this is that we live longer and we're more productive while we're alive. [63:16] Rob Sechan: When you're a client of the Street versus a competitor of the Street, you have a structural advantage that's very meaningful. You don't have one arrow that you can pull out of your quiver. [63:16] Adam Parker: the best use of Trivariate's time is not when I touch the keyboard. [74:50] I wish I could go back.

[0:00] You guys are actual friends. Like [0:01] really? [0:02] >> Yes. Yeah. [0:03] >> Tell us tell us about it. [0:04] >> They go tip to tip these guys when they [0:06] hug it out. They do. [0:08] >> There's a storyual That's a mutual [0:10] friend of ours. But yeah. [0:11] >> How long How long do you guys go back? [0:12] >> He told me. [0:12] >> Wait. You have a friend named Tip to [0:13] Tip. He told [laughter] me he told me. [0:16] >> That's a great nickname. [0:17] >> We're not going to say who it is. [0:19] >> We cannot say who it is. [0:20] >> No, no, no, no, no. [laughter] [0:22] >> You tell the story if you want. [0:24] >> Yeah. You You tell the story. Don't say [0:26] Don't say the name. Don't say the name. [0:27] >> So, we are going to say the [laughter] [0:28] name. [0:30] But it's it's honestly hysterical. It's [0:32] really I I I met Adam. We have a lot of [0:35] mutual friends. He came to meet me in [0:36] Fort Lauderdale. We're having lunch. Uh [0:39] we're a client of his firm. And he goes, [0:42] "This guy, you know, I know him well. [0:44] We're mutual friends. This, that, and [0:46] the other thing." And he goes, "He's a [0:47] real he's a real tiptotip guy." And I [0:50] said, [0:50] >> "What does that mean? [0:51] >> What what does that mean?" And he goes, [0:54] he goes, "You know how when some people [0:56] hug you and shake your hand, they kind [0:57] of lean the shoulder to the side?" He [1:00] comes in straight and hugs you. And he [1:02] said, "It is full frontal." I could not [1:05] stop laughing. [1:06] >> I respect that the entire lunch. [1:08] >> No, we both, [1:09] >> to be clear, we both really love this [1:10] guy. Like, it's not [1:12] so. And he's like the only person I [1:14] would say that he can get away with it. [1:16] Like, like, right. Like, it actually [1:19] works. [1:20] >> It's a very well-known person. [1:21] [laughter] So, So you call Robin. [1:24] >> We were talking about it and then he [1:26] called our mutual friend and was like [1:27] >> laugh. [1:29] >> I could not I could not [1:31] >> cuz it resonated. He's done it to him [1:32] too. He's tip to hip tip to tip. Yeah. [1:35] >> Most people are tip to hip. [1:37] >> Tip to hip is okay. Tip [laughter] to [1:39] tip is a lot. [1:40] >> Does this guy also um [1:42] >> you can't you can't no. [1:44] >> He's amazing. [1:44] >> He's amazing. [1:45] >> It's uh Michael Jordan. [1:48] >> No, no. I had a great I had a great joke [1:49] that was not appropriate for the [1:50] airways. [1:51] >> Yeah. Let's not do that. [1:52] >> The equivalent of them. [1:53] >> All right, boys. You ready to rock [1:54] today? Something tells me this is going [1:55] to be one of the alltimers. I It's just [1:58] It's in the air. [1:59] >> I don't know if it's spring. I don't [2:01] know if it's you guys. Maybe a little [2:02] bit of both. I'm I've been looking [2:04] forward to this all week. What about [2:06] you? [2:06] >> All month. [2:07] >> All month. [2:08] >> Where's home base for you? [2:09] >> Uh, [2:11] depends on who's asking, but mostly for [2:14] the IRS. [laughter] [2:15] >> Mostly for [2:18] you guys don't mind. [2:20] >> Oh, yeah. Oh, sorry. Bob, you look very [2:22] smiley. You take an edible before you [2:23] come on. [2:23] >> No, this is me. [2:25] >> He's pumped. I'm telling you something. [2:26] It's in the air. [2:27] >> All right. Oh, I hate it. [2:28] >> Remind me uh wire on the right or the [2:30] left? [2:31] >> Wire on your left. [2:32] >> Thank you. [2:33] >> All right. [2:33] >> Is it Is it smashing down my flow? You [2:36] look great. [2:37] >> I had flow back in the day. I was nice [2:40] 18-year-old. Had some hair. Not anymore. [2:44] >> It's possible again these days. [2:46] >> No, it's not. Josh, is it possible? [2:48] >> No. You have to go to Turkey. Then it's [2:49] possible. It won't be your hair though. [2:51] It'll be from a dog. [laughter] [2:53] >> But you can get [2:54] >> You have to decide the dog. [2:56] >> You can get [applause] [2:59] >> All right. All right. Let's pod. [3:00] >> All right. Two seconds. [3:01] >> Two seconds. [3:03] >> So, what else is going on, boys? [3:05] >> Oh, I heard a I heard a crazy story [3:07] about you. Um, [laughter] [3:10] >> you look nervous. You're sweating. [3:12] >> You were doing Closing Bell with Leslie [3:14] Picker. Um, and right before the [3:18] segment, you looked up her credentials [3:22] to make sure that she was up to the [3:24] level to ask you why you think the [3:26] market's going up or whatever. She's [3:27] going to ask you. [3:29] >> There's no way. It's not true. [3:31] >> I did look up her credentials, but that [3:33] was only because I was trying to just [3:34] resonate with something about her [3:35] background. It wasn't to see if they [3:37] were up to this. [3:38] >> Trying to connect sounds crazy. You [3:40] know, the first time Adam was on, he was [3:42] super duper sweaty. She's not m She's [3:44] not mad about it, but she thought it was [3:45] funny. [3:46] >> Crazy sweating. I really feel bad she [3:47] took it that way. I was actually [3:48] >> No, no, no. Not in a bad way. She's just [3:51] like, "All right, am I good now?" [3:53] >> No, she was very impressive. I've been [3:55] I've been on with her many many times [3:57] before. I just I just looked her up. [3:59] That [3:59] >> is awkward. [4:01] You went to UCLA, you know, whatever. I [4:02] was just trying to connect, you know, [4:04] and I didn't have I didn't I didn't [4:05] prepare. [4:06] >> I was I was I was screwing with her on [4:08] the commercial breaks. I was looking up. [4:10] She was up for a a Gerald Lobe award and [4:12] I was asking the producers to verify. No [4:15] [laughter] ver can you please verify [4:17] that Leslie was nominated for this [4:19] award. Shout shout out to Leslie Picker. [4:21] >> Yeah. [4:22] >> All righty. [4:22] >> All right. [4:23] >> I hope she sees that. I genuinely [4:25] >> she loves She loves you. [4:28] >> Episode 2 39. [4:41] Support for this show comes from [4:43] public.com. [music] If you're actively [4:44] involved in your portfolio, you probably [4:46] catch yourself repeating the same [4:47] actions. Buying the dip, manually [4:49] sweeping idle cash, putting on a hedge. [4:52] On public, you can now [music] create AI [4:54] agents that handle all of these tasks on [4:56] your behalf. Just describe what you [4:58] [music] want to do in plain English. [5:00] like if the VIX hits 25, buy a put [5:04] option on the S&P 500 or if my cash [5:07] balance goes above $20,000, move the [5:11] excess into my direct index. You approve [5:14] the [music] workflow and your agent [5:16] handles the rest. [5:17] >> Monitoring the market, watching your [5:18] conditions, and executing your [5:19] strategies exactly [music] as defined. [5:21] Public is the world's first aentic [5:23] brokerage and investing platform driven [5:25] by your intent, [music] not just your [5:27] clicks. Oh, and PS, you can also get [5:29] full read and write access to [music] [5:31] your account via the public API. Go to [5:34] public.com/compound and earn an uncapped [5:36] 1% match when you transfer your [5:38] portfolio. That's public.com/compound. [5:41] Paid for by public [music] investing. [5:42] Brokerage services by open to the public [5:44] investing inc member FINRA and SIPC. [5:47] [music] Advisory services by Public [5:48] Advisors LLC. SEC registered advisor. [5:51] Complete disclosures available at [5:53] public.com/disclosures. [5:55] [music] [5:58] Oh wow. 239. [6:00] Rob, we've done this 239 times so far. [6:03] Or 238 going into 239. [6:06] >> And this is my virgin experience. I kind [6:08] of rank at the bottom. [6:09] >> We ran out of people and [6:10] >> bottom of the order. [laughter] [6:13] >> All right, guys. [6:13] >> They didn't trust you to go solo either. [6:15] They had to like [6:17] >> training wheels training. [laughter] [6:19] Training. Well, if AP is here, we know [6:21] it's going to be okay. Uh Adam Parker is [6:23] one of the fan favorites [music] on this [6:24] show. Let's do your intro first. Adam is [6:27] the CEO and founder of Tvariat Research. [6:31] Prior to Tvariat Research, Adam was the [6:33] founder and lead portfolio [music] [6:35] manager of Triariat Capital, an equity [6:37] longshore hedge fund. Adam is also [6:40] [music] an investment advisor board [6:42] member for Rob's firm, New Edge Wealth. [6:45] Been around. Uh when did you guys first [6:47] meet? [applause] [6:48] Uh few years ago. [6:50] >> All right. All right. Uh and making his [6:53] first appearance on the compound at [6:54] Friends. I'm so excited about this. Rob [6:56] Sichin is the CEO, managing partner, and [6:59] co-founder of New Edge Wealth and [7:01] co-managing partner of New Edge Capital [7:04] Group. Rob was an adviser at Morgan [7:07] Stanley, a director at Lehman Brothers. [7:11] Was not his fault [laughter] and a [7:13] director at UBS prior to founding New [7:16] Edge. He has been recognized by both [7:17] Baronss and Forbes [music] as a top 100 [7:20] financial adviser. Give it up for Adam [7:22] and Rob. Welcome to the show, guys. [7:25] Thank you. All right, question one. [7:28] [laughter] No, I'm kidding. Uh, we have [7:30] to start, guys, we have to start with [7:32] software. Uh, there was another blow up [7:34] overnight and and into today and service [7:37] now. This seems to be like a recurring [7:39] nightmare where every week it's another [7:42] or every month it's one, two, three of [7:45] these stocks. They're already in 50% [7:48] draw downs and then they report what [7:50] looked like a good quarter on the [7:52] surface and they go even lower. Is there [7:54] an end? Let's start there. Is there an [7:56] end in sight? What do you think? [7:57] >> Do you want me to go or do you want to [7:58] go? [7:59] >> It's up to you. I I'll start. I mean, [8:01] I'm not ready to call a bottom in the [8:02] group, but certainly there's a lot of [8:04] value being created. It's oversold. We [8:07] own We've owned a lot of positions, as [8:09] you know. We owned Adobe at one point in [8:12] time. We keep trying to rotate into the [8:14] higher quality names. So maybe we can [8:16] participate if there is a a turnaround. [8:19] But it seems like these these stocks are [8:22] guilty until proven innocent. And this [8:24] trend of uh you know short software, [8:26] long semis is going to be in place for [8:29] as long as is in place. Um you look at [8:32] what uh uh uh more capital always says, [8:36] you know, every now and then Lewis [8:37] Bacon, something comes along and knocks [8:39] you into a different atmosphere. [8:42] something came along and knocked them [8:43] into a different atmosphere and it's not [8:46] changing and it may not be changing for [8:48] a while but that doesn't mean that value [8:51] is not unlocked at some point in the [8:53] future in the form of earnings that [8:56] sustain. [8:57] >> You know what's a good sign? I want to [8:59] call Fidelity and ask them if they could [9:01] hide my software positions from me so [9:03] that when I log in I don't have to look [9:05] at them. I already know they're down. [9:06] >> I I have a view on this. [9:07] >> Yeah. And I assume you [9:09] >> and I want to be I want to be kind of [9:11] like, you know, I feel like I I start [9:14] all my meetings recently with like [9:16] >> everything I'm saying could be wrong, [9:17] >> you know, just because it feels like the [9:19] uncertainty is more than normal. So [9:20] like, you know, I feel like I got to [9:21] bookend my comments. But like, [9:23] >> and we've had some pretty bad calls this [9:25] year, I'd say, at the sector level. I'm [9:27] just saying I'm I'm pretty self I'm [9:28] pretty honest about that. Like we've had [9:30] some good calls and bad, you know, we've [9:31] been recommending healthcare that's been [9:32] crap. Like I I could go through it, but [9:34] the we've been seeing the ball clearly [9:36] on software. It's a good call we've had [9:38] and our call has been when the multiples [9:40] contract like they have, what comes next [9:42] is they miss on earnings and then [9:44] eventually they miss on sales. And so um [9:46] I'm not surprised on now at all. It's [9:47] one of the ones that people love and [9:48] defend the most. And the reason I think [9:50] these companies are going to miss on [9:51] earnings is because the analysts have [9:54] 80% gross margin and the same net margin [9:56] every year going forward 27 28 29 in [9:58] their models. And and how are they going [10:00] to attach all the AI tools that their [10:01] customers need without some spending? [10:03] And if you're JP Morgan CTO or Morgan [10:06] Stanley CTO, you're going to pressure [10:07] them on pricing eventually because [10:08] you're going to realize, wait guys, we [10:10] can attach our own tools. We have a [10:11] massive organization. So there may be [10:13] value gets unlocked, but I think what's [10:14] going some of the names, but I think [10:15] what's going on is they miss first on [10:17] earnings and then eventually they miss [10:19] on sales. And what the analysts are so [10:20] used to doing is saying, "I'm calling my [10:22] CTO contacts. They're telling me they're [10:23] never getting rid of now. I call the IR [10:26] guy. We think it's a SAS apocalypse. We [10:27] cry in our beer together." And none of [10:29] that's what's going on. It's not about [10:30] today's fundamentals. It's about the [10:31] distribution of outcome of 2030 [10:32] fundamentals. So, some will work and [10:34] some won't, but the median software [10:35] company's going to be bad. [10:37] >> UBS finally last week came out and said [10:39] it's not the bottom and here's why. We [10:41] talked to CTO's [10:43] >> and they're all using the same term cost [10:45] containment. [10:46] >> Yeah. [10:46] >> None of them are going to accept this [10:48] automatic role, [10:49] >> right? They're going to pressure [10:50] pricing, right? [10:50] >> But how much of the how much of the [10:52] earnings power of the software group for [10:54] the last few years has just been like we [10:56] are indispensable. We are the system of [10:58] record for these customers. They can't [11:00] get rid of us. We also have the ability [11:03] to raise prices and nobody does [ __ ] and [11:06] now it's not so automatic. [11:07] >> I think that's right. And I think the [11:08] other thing is like when it comes to [11:09] software selection kind of maybe [11:11] perversely the ones you want to buy are [11:13] the expensive ones. You don't want to [11:14] buy cheap software. [11:15] >> I heard you saying I heard you saying [11:16] that. Could you explain what you mean by [11:17] that? [11:18] >> If if you take this premise that like [11:20] maybe we all know individuals are idiots [11:23] but the market collectively is smart. [11:24] Right. When you get stocks that get [11:26] cheap on average they're cheap for a [11:28] reason which is the probability they're [11:29] disrupted is higher. Right. So the ones [11:32] that are more expensive, the security [11:34] software, uh, cadence and synops like [11:37] they're more expensive for a reason, [11:38] which is their technological [11:39] obsolescence risk is lower. And so when [11:42] you go back and study like what works in [11:43] the rebound, it's not the slow growing [11:44] ones that are cheaper. It's the fast [11:46] growing ones. So some of these going to [11:48] work. I I kind of view it a little bit [11:49] like um a lot of software is going to [11:51] turn into like um you know how like a [11:53] company wants to fire a million people. [11:54] So they hire McKenzie and Mackenzie says [11:56] you should fire a million people and [11:57] [laughter] then they fire a million [11:58] people and they say yeah the expert [12:00] souls to do it some software is going to [12:01] turn to that right because imagine [12:03] you're at Morgan you're at new edge and [12:05] you're like I cla coded some security [12:08] Rob let's implement it right and then [12:10] somehow there's a breach of all the [12:11] adviserss like you're fired and he's [12:13] probably fired for being a [ __ ] for [12:14] listening to so you just got to pay [12:16] crowd strike or powto or whatever just [12:18] because you have to have an expert in [12:20] case something goes wrong like you may [12:21] get some of that happening in software [12:23] for sure but the ones that are more [12:24] expensive are more expensive for a [12:25] reason and that reason is they're less [12:27] likely to get disrupted. [12:28] >> It's it's got to be hard because I know [12:30] you're claude quoting your face off and [12:32] I know your your team is like like my [12:35] team like every firm the people that are [12:38] involved with tech are going crazy right [12:40] now at every company in America. [12:42] >> We we [12:43] >> it's it's hard to then look at the board [12:45] and look at stock prices and be like I [12:47] want to fade this. He's he he I'm close [12:50] with a number of his employees and one [12:51] of his guys who's a stock picker comes [12:53] to a lot of our events and he won the [12:55] best stock picker at our main event last [12:57] year and has crushed it in in tech and [12:59] >> all technology based too. I mean he he [13:02] he [13:04] listens to this give a shout out. [13:05] >> So Jay is his name. He's he's [13:07] unbelievable talented but it it's we've [13:10] leveraged tech throughout the start of [13:12] our ecos. It was a tech enabled [13:14] solutions firm. We built new new edge on [13:17] top of institutional-grade [13:19] infrastructure. We didn't start it out [13:20] of a private bank. It wasn't an idea in [13:23] my basement. It wasn't built upon my [13:25] practice. It was built on infrastructure [13:28] on rails. And that infrastructure [13:30] allowed us to bring in technology, [13:33] plugandplay different things and try [13:35] them religiously. We rolled out cloud [13:37] enterprise to everybody a month ago. So, [13:39] we're trying to be on the front edge of [13:42] uh of kind of everything we do in [13:43] portfolio management. We have a very [13:46] quantitative approach. You know, I I [13:48] slept at a Holiday Inn last night when I [13:50] go on TV because the reality of it is is [13:53] we're sometimes reverse engineering the [13:55] story out of the math, [13:56] >> right? [13:57] >> That that drives the positioning that [13:59] we're we're going into and you can see [14:01] you can see a lot of these things, but I [14:04] am amazed. [14:05] It's like I have 15 analysts working for [14:08] me at my fingertips. So when I was a [14:10] banker back in the days at at Morgan [14:13] Stanley and and doing analysis, some MD [14:16] would come to me that we'd iterate and [14:18] then I'd go back to him two days later. [14:21] I am doing that same thing. We're [14:24] working on an acquisition right now, [14:26] several. And I'm doing that same thing [14:28] and it's instant feedback. So you can [14:30] you can kind of interact. [14:31] >> You know what you're making me think of? [14:33] He's probably like me where like I just [14:34] have too many interns, right? cuz I say [14:36] yes like can my daughter can my nephew [14:38] can feel the problem the problem is like [14:40] they don't have any skill it used to be [14:42] I'd be like hey go go go go tell me all [14:43] the acquisitions Microsoft made in the [14:45] last 5 years and summarize what [14:46] technologies they're buying now they do [14:48] two seconds and go back so I don't know [14:49] what they're going to do for the other [14:51] nine days and and and nour and fans the [14:54] machine [14:58] I would tell you that the intern now [15:01] >> the average is going to be good to great [15:04] in the great is going to be gamechanging [15:08] for the enterprise. I I just can see [15:11] efficiency happening all over the place. [15:13] So while we might not lay anybody off as [15:16] a result of this, I can tell you our [15:18] pace of hiring will slowly [15:21] >> I'm hearing this everywhere [15:23] >> and then ultimately profitability is [15:26] going to explode as a result of [15:27] productivity and I think that's endemic. [15:29] >> So here's the market. [15:30] >> So here's the problem then. So then [15:32] here's the problem. You have I don't [15:33] know what it is 150 200 enterprise SAS [15:38] companies in the public markets. [15:39] >> Y [15:40] >> forget about pricing because no one's no [15:43] one's going to be able to pull off a a [15:45] big enough increase. The real problem is [15:49] most of these companies are selling by [15:50] headcount. And what we're all saying [15:52] here is headcount may not shrink, but it [15:56] ain't going to grow to the extent that [15:58] it used to anywhere. I but I'd like to [16:01] know his his view on that because the [16:03] reality of it is what does that mean for [16:05] profitability for these companies if [16:08] they still have essential kind of [16:10] infrastructure and tools doesn't that [16:13] ultimately make their profitability [16:15] explode as well and isn't that a [16:17] positive thing at some point and so [16:20] should we just watch themselves hold on [16:22] we have charts for this John so [16:23] ironically throw up chart five so [16:25] service now reported this morning down [16:27] 18% not bad um we have [16:29] >> [laughter] [16:30] >> They're headcount by department. [16:31] >> It was my final trade two days ago or [16:34] yesterday the earnings. Have you learned [16:36] nothing from me? [16:37] >> I do it all the time. [16:38] >> Yeah, we we've all been there. Um Q1 [16:40] 2025 26,698 [16:43] employees. Q1 2026 29,732. [16:48] John, go to the next chart. Their [16:50] stockbased comp is exploding. Like they [16:52] have they not gotten the memo at all [16:54] that the street does not like this. Look [16:56] at that. [16:57] >> So [16:57] >> it's breaking out. SBC didn't matter [16:59] until it really mattered. [17:00] >> I I yeah stockbased compensation is now [17:04] we're going down like the twig down the [17:05] branch down the [laughter] down the the [17:07] tree but like it's just a beta factor. [17:09] So when tech outperforms the ones with [17:11] lots of stock b outperform when [17:12] underperforms the lots underperform. So [17:14] it's just it's just a beta factor [17:15] because it's like an R&D intensity [17:16] factor. [17:17] >> But you know you could have died on that [17:18] hill. You would have lost a lot of money [17:20] on the stockbased comp hill over the [17:21] last 15 years. So I got you gotta manage [17:23] risk around it. But like I I kind of [17:25] agree with Ros's point or big time I [17:26] agree with it. like it's about [17:27] productivity and the question is like [17:29] what's in the price? Look at Walmart [17:31] maybe as the ultimate poster child like [17:32] what would make the market go [17:33] parabolically higher. One of the things [17:34] would be Walmart gets on it says in 2030 [17:37] we'll have less employees than we have [17:38] now, [17:39] >> right? [17:40] >> Which might actually end up being the [17:41] case. [17:41] >> It might and there's a reason it trades [17:42] at whatever 38 times forward earnings. [17:44] It's not because they have three and a [17:45] half% net margin or whatever the number [17:46] is now. It's because you're in the [17:48] prices five or six eventually that [17:49] they're going to nail predicting how [17:52] many jugs of milk or everything. [17:53] >> I think that's too early is his his [17:55] point. We are we are at the tip of the [17:58] spear right [17:59] >> for these companies figuring out whether [18:01] they can make that migration, figuring [18:03] out the implications for the business. [18:06] You guys probably are too. We are too. [18:08] We're we're learning as we go and we're [18:11] learning at a pace that I've never seen [18:13] before. [18:14] >> Gee, I wonder why Wall Street hates uh [18:15] why why uh the country hates Wall [18:18] Street. You just said what would make [18:20] Walmart really go parabolic if they come [18:22] out and said by 2030 we're going to have [18:23] less employees. Economists and and stock [18:26] people are they've never been more in [18:27] congruous. Like if you if you I remember [18:29] when I was at Morgan Stanley our [18:30] economists would say stuff like I want [18:32] capital spending and I want hiring and [18:33] I'm thinking if I own a stock and they [18:35] announce either of those two things I'm [18:36] selling it immediately. Right. Like [18:38] there's a giant disconnect between that [18:39] doesn't sound good. [18:40] >> Right. Right. Like I don't want hiring [18:42] at my company. [18:43] >> More potential customers with higher [18:44] paychecks is one more healthare. [18:48] Right. Like but so they the GDP and the [18:51] economy are are kind of different than [18:53] than than picking stocks, right? I mean [18:54] look, you had a guest on uh last week or [18:57] the week before, a personal friend and [18:58] favorite Encore Crawford. [19:00] >> Do you know 70,000 people and counting [19:02] have watched that episode? She is such a [19:04] star. [19:04] >> I know her for a really long time. I met [19:05] her through you and you skipped you [19:06] skipped a couple things about her in her [19:08] bio. One of which is she has a PhD from [19:10] Stanford and the other is she has the [19:11] number one performing growth fund in the [19:12] last 12 months in the entire of all [19:14] growth managers. I told her [laughter] [19:15] after [19:17] but she said yeah she said something [19:19] that is totally awesome. Okay and I've [19:21] stolen it from her for the last week [19:23] which is people who are like bearish on [19:24] AI don't you don't get it like they like [19:27] they they if you think like it's a [19:29] bubble and it's over [19:29] >> nonsense. She said it's nonsense. [19:31] >> Yeah. Yeah. And and and everything [19:32] sounds smarter when she says it for [19:33] sure. But like I I I just feel like you [19:36] know we're on the precipice of it. Like, [19:38] you know, the reason there's earning [19:40] estimates that are 18% for the S&P this [19:42] year and 17 next year and 43 in tech [19:44] this year and 25 in next year is because [19:46] you're just you're like in the in the in [19:48] the we might be in the fifth inning of [19:50] the stocks, but we're in the first [19:51] inning of like it hitting the numbers. [19:53] >> You think that's why small caps are [19:54] breaking out? Part of the reason. [19:56] >> Uh [19:58] yeah, maybe some [20:00] >> that the S&P 493 so no mag 7 [20:05] >> earnings are supposed to be up 15 point. [20:07] quote 16% [20:09] there's got to be some AI productivity [20:11] in there has to be there's got to be [20:12] >> how why else why else would that happen [20:15] there there is [20:16] >> it's not 8% GDP growth [20:18] >> but there is underlying economic [20:20] strength right there you you can defin [20:23] just if you look at the price action of [20:26] just about everything whether it be [20:27] spreads it is telling you that there is [20:31] a miss between positioning and what's [20:34] happening in the underlying economy I [20:36] don't think there's anybody better at [20:38] reading the tea leaves than Tom Lee. I [20:40] think we could all all agree that this [20:42] is the best data guy out there. Tom Lee [20:45] sees around corners. It's it's freaking [20:47] unbelievable. And how does he see around [20:49] corners? He's watching these uh cross [20:53] asset movements, right? And you know, [20:57] one thing that scared me, you might have [20:58] said it on your show, is he kind of [21:00] thinks there's going to be this like [21:01] midyear pullback that scares the [ __ ] [21:04] out of every test [21:06] at some point. [21:07] >> Yeah. So, and [21:09] >> meaning if if something that the market [21:12] doesn't expect, there'll be a big [21:13] overreaction. [21:14] >> Yeah. Yeah. So, but when he when he's [21:17] looking at these things and seeing [21:19] what's happening in, you know, uh [21:22] quality names like like the semis and [21:26] what's happening in in software, he's [21:29] listening and many don't. Yeah. [21:31] >> Right. Many get sucked up in the [21:34] headline narrative of what's happening [21:36] in the war and they start to think [21:39] second and der and third derivative [21:41] effects of what that what could be. But [21:43] what is it? Yeah. [21:45] >> Today, what what is it? [21:46] >> Yeah. I mean, I think if earning like [21:48] the way to think about it might be if [21:49] the street's got 43% earnings for tech [21:53] and yeah, a lot of it's microvidia, but [21:55] let's just say it's got 43% growth and [21:57] let's say the real number is 30 and it's [21:58] got 25 next year and the real number is [22:00] 15. Tech's not going to be 45% cheaper [22:02] in a year because it's stayed flat for [22:04] the entire next 12 to 18 months. Like [22:05] unless there's a much bigger growth [22:07] scare coming in 28 or 29 or something, [22:09] but like the odds are just the absolute [22:11] level of growth is high enough that [22:12] things work. And so I think the market [22:14] woke up to that a few weeks ago, but [22:16] like where could people be complacent? [22:18] Like I did a big risk dinner this week [22:19] with a bunch of risk officers and like [22:22] nobody thinks Yeah. You It's not It's [22:25] not exactly [22:25] >> Rob wasn't invited to that. [laughter] [22:26] >> No. Okay. [22:27] >> I wasn't either. [22:28] >> Yeah. This Rob not his not his crew. But [22:32] like [22:32] >> annual value [laughter] like risk people [22:34] what people are like if you say what are [22:37] people complacent about? It's probably [22:39] that everybody thinks oil eventually is [22:42] going to come lower and probably faster. [22:44] So like right now nobody's taking their [22:46] numbers down for input costs in [22:48] industrials or for you know select um [22:53] you know um energy sensitive consumer [22:56] because they just think ah you know [22:58] second der of hormuz news is positive if [23:00] I get bad hormone news market's down 40 [23:02] bits if I get good it's up 150 so like [23:05] you know whatever it's [23:06] >> nobody wants to look like an nobody [23:07] wants to look like an [ __ ] again [23:09] going risk off [23:10] >> you called 17 the last zero like tariff [23:12] problems so I'm I'm not being the [23:14] Hormuse problem guy, right? So, like [23:15] people are a little bit, [23:17] >> you know, so I'm not saying that's going [23:18] to happen, but I just think people are [23:19] playing for so like on the Fed like I'm [23:22] not sure cutting rates is going to be [23:25] bullish for multiples like it was [23:27] frankly how can it even happen? It [23:30] creates an inflation expectation problem [23:34] that is going to be pretty dramatic. I [23:35] think it's why you have to own some [23:37] energy in the portfolios is kind of like [23:39] a like a tail hedge to this. Do you [23:41] think most market participants would [23:43] prefer the price of gasoline go back to [23:46] three and change versus another 25 basis [23:49] point rate cut? I do. [23:51] >> I do too. [23:52] >> Yeah, for sure. [23:53] >> Yeah. Yeah. [23:53] >> No doubt. [23:54] >> Well, there's a higher likelihood of [23:56] that to Rob's point. [23:57] >> But but also like it depends where [23:58] you're on the cycle. Like when it was [23:59] the end of 2022 and you perfectly [24:01] covered your Nvidia, Tesla, and meta [24:03] shorts which are all down 65% and you [24:05] started buying the max long on Gen One, [24:07] right? Your logic [24:08] >> actually it was the December that you [24:10] got the position you're big you run a [24:12] lot you got to get [laughter] okay so [24:14] then your logic was well the Fed's [24:16] closer to the end of the hiking cycle [24:17] than the beginning eventual [24:18] accommodations coming the Fed action is [24:20] going to be super bullish for multiples [24:22] nailed it right but the question is now [24:24] three plus years later if they get [24:26] incrementally dovish is that really like [24:27] oh awesome or is it because like stuff's [24:30] slowing and therefore like at some point [24:31] >> it becomes a growth [24:32] >> scale it's a little bit different I'd [24:34] rather have the gas price come down is [24:35] the semiconductor rally the most out of [24:37] control thing you've ever seen. [24:38] >> No, [24:38] >> it's not. [24:39] >> I think it's completely [24:40] >> I think it's justified, too. [24:41] >> Is it the most out of control? I've seen [24:43] a lot of stuff. [24:44] >> So, I think it's so completely out of [24:46] control. The pace of it and the [24:47] relentlessness. [24:48] >> Micron is bigger than Johnson and [24:49] Johnson. [24:50] >> Okay. So, so, so look, I'm I'm a I'm a [24:53] you know, I used to semiconductor [24:55] >> analyst last 16 days. [24:57] >> Mhm. [24:57] >> 35% for the semis. 16 days. It is the [25:03] best rolling 16 day. I know it's a [25:05] random number. best rolling 16-day [25:08] period in the history of the SMH. Never [25:11] before. [25:12] >> Yeah. [25:12] >> Uh and I understand the reasons. I'm not [25:14] I don't live in a cave, but like [25:16] >> people are will just buy anything [25:18] semi-related. [25:19] >> I think when you look when you look at [25:20] semis and you look at tech, you really [25:22] have to look at it like even software [25:24] look at software X Microsoft and with [25:26] Microsoft. When you look at semis, you [25:28] know, your tech book is going to look [25:29] like it grows more slowly and is more [25:31] expensive than the tech index unless [25:33] you're overweight Micron because Micron [25:35] trades at four and a half times next [25:36] year's earnings and is growing like [25:38] 100%. Right? So, you know, we know it's [25:42] cyclical, but [25:43] >> you got to see something that comes [25:45] along and challenges [25:48] probability [25:49] of that outcome. And I don't know [25:52] >> them earning enough, [25:52] >> right? That is right. as long as I [25:56] It's hard to see right now, but you [25:58] know, the pianos don't hit you in the [26:00] face, they hit you in the back of the [26:01] head. [26:01] >> Nvidia has grown earnings substantially [26:04] in east each of the last four quarters. [26:07] Stock has not gone up. [26:08] >> I think the stock will go up and go up a [26:10] lot. [26:10] >> I know, but I'm saying you two things [26:12] can be true. [26:14] >> You can have a stock price that just [26:15] refuses to go along with incredible [26:17] fundamental news, [26:19] >> which is all we've ever seen. [26:20] >> Estimates plus or minus. I don't know if [26:22] somebody can I'm sure somebody will [26:24] comment on this but like they were [26:26] roughly 50 bucks in earnings earnings [26:28] per share for next year before they [26:29] reported and they're roughly a hundred [26:31] now. [26:32] >> So the magnitude one of the things we're [26:34] doing right now we're researching is [26:36] >> look at all the companies where two [26:37] years earlier the analyst estimates were [26:39] most off like ever on earnings high [26:42] >> and those are those are the best stocks [26:43] >> and this guy yeah both in both [26:45] directions. looking at ones where they [26:46] way off too high too just to see if [26:47] there's a pattern but like this is one [26:49] of the bigger free cash flow estimate [26:51] misses ever in 25 years in the market. [26:53] >> I want to so when you say it's crazy [26:54] like yeah the price action is massive [26:56] but it's also one of the crazier [26:58] >> because it's such a huge change and [27:01] nobody knew it was coming [27:02] >> like rough rough order magnitude people [27:04] had like like a a billion and a half in [27:07] free cash flow for next year and it was [27:09] like three and a half billion over two [27:10] years and now it's 80 billion over the [27:11] two like the magnitude is like zeros [27:14] off. Yeah, [27:15] >> Adam, I want to do one last thing on uh [27:16] on software before before we leave that. [27:19] >> So, you talk to a lot you have a lot of [27:20] hedge fun customers. [27:22] >> I'm imagining that nobody wants to touch [27:23] software, although I'm sure there's a [27:25] lot of dip buyers that got their hand [27:26] burned, but Service Now, for example, so [27:28] they report this number uh number of [27:30] customers with $5 million ACV. John, [27:32] chart 3, please. And they went from 434 [27:35] customers paying $5 million up to 630 in [27:40] Q1 with a 97% retention ratio. Now the [27:44] their margins came down, but this is [27:46] still a good business 100%. The problem [27:48] is nobody sits on the macro. I mean, [27:50] you're gonna have to manage all this, [27:51] >> but the stock is down 18% today. Isn't [27:54] that scary? They did 22% revenue growth. [27:57] They hit the numbers and the stock still [28:00] lost 20% of its value after being down [28:03] 50s something%. Isn't that scary? [28:05] >> So when you talk to your clients like [28:06] are they what's their view? Is everybody [28:08] like I this I can this is not [28:09] investable. How do I how do I buy this? [28:12] >> So only thing I'd parse and what you [28:14] asked me is I think it really depends if [28:16] you're a long only or a hedge fund, [28:18] right? Most hedge fund money like they [28:20] don't have to own any of this stuff. [28:21] Let's do long or they can pay off, [28:23] right? So, it's really more the long [28:25] only guy who's, you know, is what he is. [28:27] He's a software like why does GM make [28:29] cars? Like, you know, like the software [28:31] he's got to pick winners, losers in the [28:32] group and identify how to like [28:33] outperform the software benchmark, [28:35] right? And the PM's job is to figure out [28:37] what exposure to the aggreate group [28:39] should be. So I I think most analysts [28:41] are going to say I want to own stuff [28:42] where the revenue is accelerating and [28:44] you know if you look at a 2 x two grid [28:46] of like you know beat on revenue beat on [28:48] earnings missed on re the worst bucket [28:50] is what now reported which is you're [28:52] fine on revenue and you miss on earnings [28:54] because the market doesn't know where [28:54] the clearing margins are but you just [28:57] exposed the fact that like your margins [28:58] in the out year are lower [28:59] >> and margins came down their guidance [29:01] margins came down [29:01] >> so it's not trading 18% lower today it [29:04] is it might be trading 4% lower on 2030 [29:07] like you have to warm yourself up to [29:08] that idea of like the uncertainty on the [29:10] margin profile just changed. There are [29:12] assets including now could be one of [29:14] them and I'm just not smart enough to [29:15] know that this could be like a great [29:17] entry point in a two or three year. But [29:19] I need to see some price action that we [29:21] all know are going to shake our head. [29:22] Yes. Where a company misses and doesn't [29:23] go down [29:26] the stock doesn't move. [29:27] >> I haven't seen a single penalty for [29:29] missing that hasn't been harsh. Today [29:31] was the first day where I thought a [29:33] couple beatings were good. URI Texas [29:36] Instruments up massive and you know but [29:39] if we we track this thing the penalty [29:41] for missing versus reward for beating [29:42] ratio and not only has it been very [29:44] skewed toward the penalty harsher but [29:45] it's like cheap stocks missing are going [29:47] down more than expensive stocks that are [29:49] missing. [29:49] >> So what type of market does that happen [29:50] in [29:51] >> um [29:52] >> a top a toppy market [29:54] >> like yeah I I think the good news I [29:57] guess is more companies are beating than [29:58] missing. So that's why the market's [30:00] fine. But like if more companies start [30:02] missing, like I we can't buy stuff where [30:05] we don't have any evidence. Like the [30:07] best thing ever is like you know the old [30:08] days like Caterpillar misses and it's [30:10] unch and you're like all right game on [30:11] like I I mean missing is unch [30:16] is annihilated, right? Yeah. [30:18] >> Put this tech multiple compression chart [30:19] up. This is a thing. What do you guys [30:22] make? What do you guys make of this? Uh [30:24] I think it's seven. Yeah. Here we go. Um [30:26] so let me narrate this for the people [30:28] that are listening not watching we're [30:30] starting in 2020 uh right around co time [30:33] we were at 16 times for tech forward PE [30:37] ratio peak out in the 2021 bubble at [30:40] 28.7 [30:42] fall to a low of 18.5 during the year of [30:44] efficiency 2022 [30:46] then we rally through 2024 we hit an [30:50] alltime not alltime all time in this [30:52] chart 32 times forward earnings drops [30:55] early 2025 to 21, back to 31 at the end [31:00] of 2025, one of the best years ever. And [31:03] now here we sit at 19. Huge D-rating on [31:06] forward earnings [31:07] >> very quickly, [31:08] >> very fast. Uh, very unexpected. I don't [31:11] remember reading any strategist. [31:13] >> Micro's estimates are up 100%. I mean, [31:15] >> is that all this is? Is is the growth [31:17] rate growing faster than [31:18] >> if the estimates are for 43% growth in [31:20] earnings this year? Then that that you [31:23] can have multiple being high because the [31:25] E went down or because the E was not the [31:27] P went up. And in this case, it's more [31:29] the [31:29] >> E is going up really fast and pricing. [31:31] >> I'll give you one nugget. If you look at [31:32] the S&P 500, the whole 500 Q126 versus [31:36] Q125, year-over-year growth, 45% of the [31:39] entire S&P 500's growth was from Micron [31:42] and Nvidia. If you believe this this [31:45] geopolitical risk leads to slower [31:48] economic trajectory, markets are going [31:50] to pay up for that growth and you're [31:52] going to see that go right back up [31:53] >> because if there are less companies [31:55] growing, they'll go right back to the [31:57] old playbook. [31:58] >> Or just the E if the E comes in and it's [32:00] on multiple the stocks will be 40% [32:02] higher like or or or micron will be up [32:04] or whatever. So it's it's a it's it's a [32:08] multivariable world and you just showed [32:10] one variable or whatever the course is. [32:12] >> Yeah. What were you telling client? What [32:13] did you make of the the stairstep lower [32:15] during during the war? The fact that the [32:17] market just wouldn't puke. [32:20] >> What was that telling you? I know it's [32:21] hindsight now, but [32:22] >> it made me more bullish. [32:24] >> Same. [32:25] >> Yeah. [32:26] >> We didn't have like a we didn't have a [32:27] panic. We went lower. [32:29] >> I came into the Euro. [32:30] >> So that's that's actually what kept us [32:32] invested completely through that. Now, [32:34] we we did upgrade quality. Like I said, [32:37] when you get any volatility, it's a [32:39] great opportunity to kind of pivot to a [32:41] higher quality name in the same sector [32:44] that's not getting derated as much or [32:46] has shown more resilience in their in [32:49] their [32:49] >> you say, wait a minute, we can now own [32:51] this. [32:52] >> Yeah. Especially if you're especially if [32:54] you're a long only relative investor in [32:57] a certain class whether that be [32:58] dividends value growth and you're kind [33:01] of managing to a benchmark in a [33:03] portfolio construct and you can say okay [33:06] now I can own this I could never own [33:08] this I mean for so long we never owned [33:10] Nvidia until it traded below 30 times [33:13] earnings we waited it and we missed a [33:16] lot in doing that but boy did we buy it [33:19] at the right time [33:20] >> and it's been so If you can still employ [33:23] your discipline and when volatility [33:25] creates the opportunity to upgrade [33:27] quality and you can move from X to Y, [33:30] you do it. And that leads to a lot of [33:32] outperformance. [33:33] >> Volatility though to your point within a [33:35] reasonable [33:36] >> within a reasonable band [33:37] >> like like not a freef fall where all of [33:40] a sudden it's like wait a minute [33:41] >> that's that whole different atmosphere [33:43] thing. We didn't get that. We didn't get [33:45] that this year. [33:45] >> And you won't get it from geopolitical [33:47] you get those from financial issues. [33:49] >> Right. So this credit issue that we kind [33:53] of I don't really believe, you know, I [33:55] know a lot of people do, but I've been [33:57] an ardent defender of the equity that [34:01] sits beneath it and the economy being [34:03] strong enough that these private equity [34:05] firms are not walking away from these [34:08] businesses and the credit's going to be [34:09] fine. And the market's kind of telling [34:11] you a little more, at least the more [34:14] public markets, that spreads are [34:16] remaining contained. And listen, a lot [34:18] of the credit in private credit sits at [34:20] the highest tier of the capital stack. [34:22] So you got to wipe out a lot before [34:24] they're wiped out, right? Yeah. [34:26] >> So, so from from my lens, it is that [34:31] >> that is more of a concern than anything [34:34] because that's the liquidity that feeds [34:36] the ecosystem that we all thrive off of. [34:39] Now, now I will say that if you cannot [34:42] raise [34:44] money going forward, we talked about [34:46] this on on the other show. The reality [34:49] of it is is if your forward ability to [34:51] raise capital from private investors has [34:54] been impaired and that was your growth [34:56] strategy, right? Toast. And though [35:00] they're not coming back right away, but [35:01] the institutions are staying in because [35:03] they see that they see the value of [35:05] this. You're going to be more discerning [35:07] because you have to be because you don't [35:10] have as much capital. And so the strong [35:12] are going to get stronger. They're going [35:13] to get financed. And the weak are going [35:16] to require more investment. And some of [35:17] them will get it. [35:18] >> Buy KKR. Maybe buy some KKR. [35:21] >> I I've I've thought I've thought about [35:24] Look at this. Some Blackstone. [35:25] >> Yeah. Yeah. I know. [laughter] I mean, [35:26] maybe Blackstone. I meant Yeah. I didn't [35:28] I didn't know which one you're going to [35:29] show, but I I tax so not me. the the [35:34] team tax law sold Blackstone. I got a [35:36] lot of [ __ ] on it on the show because I [35:38] always such a champion of these things, [35:39] but it was just tax laws. [35:41] >> What? So, you bought something else. [35:42] >> We didn't buy something else in the [35:44] space, but we would likely go back in to [35:46] Blackstone. [35:47] >> All right. So, Blackstone got whacked [35:48] off today. It's down 6%. And this is the [35:50] private credit fundraising on a gross [35:52] basis by quarter. Okay. Um down almost [35:56] in half, not quite 3.3 billion in the [35:58] prior quarter, down to 1.9 billion. This [36:00] is growth, not net. Okay. So I I I don't [36:02] think there were outflows. Um so a [36:04] dramatic dramatic slowing but not to say [36:06] about this. [36:06] >> This is the media narrative pausing [36:10] people who are about to allocate [36:12] >> 100%. I mean it's so human nature and [36:15] advisers we're advisers to say hey do do [36:19] I do I want to try to take advantage of [36:21] this or do and steer into the eye of the [36:24] storm. Most people don't do that. most [36:27] investors and I the success that we've [36:30] had as a company period is identifying [36:34] areas where forward returns are headed [36:37] higher [36:37] >> but pricing has not come down under it's [36:40] a flow storm that's it [36:41] >> so so that that's right but let's use a [36:44] different example in when we had the [36:46] tech crisis and in venture companies [36:48] having trouble raising money and it [36:50] rerated down and they pivoted to venture [36:53] debt [36:54] there was an enormous opportunity in [36:56] venture debt because they didn't want to [36:58] sell equity at those levels. And if you [37:00] steered into that storm just in a [37:03] different way, right? What it led to is [37:06] higher forward returns. And you see that [37:09] episodically in markets. So I think one [37:11] of the one of the great challenges that [37:13] advisors have is keeping investors [37:17] invested and how you do it is by [37:20] identifying the high optionality within [37:24] the underlying uh crisis, [37:27] >> right? [37:27] >> They will have a greater probability of [37:29] success on the other side. If I but if I [37:32] read a head if I read a headline that [37:34] said 6 months from now great news or it [37:37] would say horrible news [37:39] uh all all of these uh leverage loans [37:43] are now trading 20% cheaper than that [37:46] where they were. The thrust of that [37:48] article would be written as a way to [37:50] bash the private credit industry right [37:53] in. [37:53] >> But then I would say I love it. I [37:56] haven't bought any of this [ __ ] yet. [37:57] This is my opportunity. [37:59] >> I don't think I agree with you. I don't [38:01] think most people think that way. Number [38:03] one, and for financial adviserss in [38:05] particular, what do you think most of [38:07] their clients would say back to them? [38:09] Hey, let's buy let's buy some of this [38:12] asset class that the Wall Street Journal [38:14] is screaming bloody murder over on the [38:16] cover of the newspaper. Why would we [38:18] want to do that? That sounds crazy. [38:19] >> And I would say, did you see [38:21] Blackstone's partners step in to buy, [38:24] you know, take a gigantic chunk of their [38:26] own money and buy this? You think [38:28] they're doing that because they have [38:29] massive concerns about the asset class? [38:33] >> Kick. So, you just bought 10 million [38:34] bucks of stock. That's why I mentioned [38:35] kick. I didn't know the but they bought [38:38] the push back push back I got was [38:40] somebody's like, "Yeah, well guys got a [38:42] billion dollars." I'm like, "Yeah, but [38:42] people don't like throw 10 million out [38:44] on purpose." Like, you know, the [38:46] person's singling, [laughter] [38:49] >> but right now the pricing the price with [38:51] a few obvious examples, it's not like [38:54] that leverage loan market is in [38:56] distress. It isn't. [38:57] It's not like there are these massive [38:59] discounts, [39:00] >> but the narrative gets sucked in and [39:02] pushed out so quickly. [39:03] >> I think I like the equities better than [39:04] the products would be my would be my [39:06] comment. [39:07] >> Oh, for sure. I would [39:08] >> I like the equities better. I'd rather [39:10] be a GP. [39:11] >> That's I mean, [39:12] >> if I could buy KR and Blackstone [39:14] a year ago from on a on a private credit [39:18] project and I was looking at it, I was [39:19] like it was like [39:20] >> unlevered um 13% private credit return. [39:22] I was like, "Sorry, I don't want to be [39:25] like the annoying uh client, but uh [39:28] who's lending to me at 13% on levered?" [39:30] Cuz like how many I mean, what is this? [39:31] Is it like nail salons and orange count? [39:33] Like who who needs 13% for me? Like this [39:35] this math doesn't make sense. So like [39:37] the stocks are probably, you know, on a [39:38] two-year view, you know, better deal, [39:40] but the stocks are cut in half. The [39:41] credits, the private credit is still [39:42] trading one for one. [39:44] >> That's my point. You're not getting a [39:45] discount in the underlying. You sure are [39:47] getting a discount if you come in at the [39:49] GP level. Buy the stocks. So, all right. [39:52] You want you want to do this chart with [39:53] the highs? [39:54] >> Yeah. So, there's So, part of the [39:56] narrative over the last couple of weeks [39:57] is, yeah, we're it hitting all-time [39:59] highs, which is awesome. Feels good. [40:01] Feels better than being down, [40:03] >> but there's not a ton of stocks making [40:07] 52- week highs. So, this chart is from [40:10] Jason Gford, sentiment trader. So, he's [40:12] looking at the S&P 500 return after the [40:15] first, it's specific, but whatever. [40:16] after the first record high in one month [40:19] and under 5% of issues are at a 52- week [40:22] high. That's kind of odd. Under 5%. [40:24] >> And it's it's a mixed bag to down. It's [40:26] it's it's not great. [40:28] >> Uh positive 33% of the time, one month [40:30] out, 33% of the time, two month out, 42% [40:33] of the time, 3 month out, six month out. [40:34] I mean, these are not great numbers. And [40:36] it's not and it's not like one time. [40:37] This happened Oh [ __ ] In 29. All right. [40:40] Uh 83 90 29 93 95 2015 and 20. Do you [40:46] want me to [ __ ] on this or do you want [40:48] to please? Okay. [40:49] >> Um, [40:52] I'll just start by saying I don't think [40:54] this kind of stuff is helpful for [40:56] predicting subsequent return. This is [40:58] not statistically significant. The [40:59] market's way more concentrated, [41:00] different than it used to be. You guys [41:01] are financial advisors. I'm not, but I [41:03] can empirically show you that any kind [41:05] of breadth metrics do not effectively [41:07] help you make money. They're usually [41:08] volatility gauges. So if I were one of [41:11] Rob's adviserss or Rob and somebody said [41:13] I'd like to time my market entry here. I [41:16] would say you will destroy value using [41:17] this kind of data over your career. Um [41:19] whether it's VIX or moving average [41:21] conversions versus probabilistic uh [41:24] forward return uh studies in general. [41:26] >> I know this isn't statistically [41:27] significant. I know it's not like you [41:29] know it's all like how relevant is the [41:31] 1929 data to 2026 second half. Like all [41:35] you really said is that there's some big [41:36] stocks that are up a lot. But not, you [41:37] know, and not all of them are okay. [41:39] Good, good debunk. Let's let's take a [41:41] quick look at, [41:42] >> but it like I want to just cate like [41:44] that could work right now. I'm just [41:46] saying if you gave me a thousand of [41:47] these charts over the next few years, [41:48] I'll take the under more than 500. [41:50] >> I actually don't think anybody invests [41:51] based on that. I think people use that. [41:54] >> You want invested in equities. You don't [41:55] want to make one month market calls. [41:57] >> I think people use stuff like that to [41:59] justify something that they're already [42:00] going to do anyway. When it comes time [42:02] to buy, I promise you, when it comes [42:04] time to buy, none of your clients are [42:06] going to want to buy. [42:08] >> So, if they were super smart and got out [42:10] at exactly the right time, [42:13] >> they've got to stay in the game. The [42:15] question is how you're positioning [42:17] within staying in the game. And I think [42:20] it's gotten a little tougher because of [42:22] the index concentration and you have [42:24] markets. So, you can't kind of you can't [42:27] kind of pick your spots within that in [42:29] many cases. And so a lot of times you [42:32] can use math to marry both technicals [42:35] and fundamental factors in a way that [42:38] can, you know, maybe put you in a better [42:40] position on either side of that move. [42:42] >> And and you guys know better than me. [42:43] Like it all is a function of like how [42:45] rich the person is and how much assets [42:47] they want. You know, if you got Mr. Mrs. [42:48] rich bags who are 80 with 200 million [42:50] bucks of Microsoft stock. Like they're [42:51] solving a different problem than some [42:53] guy, you know, it's all a function deal. [42:55] What's the charity? What's the tax? Like [42:56] so I it's really hard to make a blanket [42:58] statement about that. But like I [42:59] definitely wouldn't be deploying saying [43:00] like let me sell my my S&P exposure. [43:03] >> Let me let me give breath metric from [43:05] 1929. [43:06] >> You might like this, you might not. Tell [43:08] me if this makes sense to you. John [43:09] chart Todd Sone shared this. The [43:12] semiconductor [43:14] uh sector is 16% of the market. The S&P [43:18] Energy, [43:20] healthcare, staples, and utilities are [43:24] 19%. Talking about touching tips, these [43:26] things are very close. [43:27] >> Why isn't that why isn't [43:30] why isn't that rational? [43:32] >> Why is this not rational [43:33] >> right now? I'm asking you guys, what is [43:36] the profit? What is the profitability of [43:38] these staples and utility stocks? Well, [43:40] if okay I would guess you would know [43:42] better than me that if you add up the [43:44] profitability just earnings and maybe [43:47] that's not the right metric of energy [43:49] healthcare staples and utilities [43:50] especially healthcare in there it would [43:52] dwarf semis but maybe not because of [43:54] Nvidia. [43:54] >> Well here here's the thing I'm sorry you [43:57] love it. [43:57] >> I I didn't mean it is [44:00] >> what is happening to forward guidance is [44:03] really what is the driver the prices are [44:06] following what's the 2030 distribution [44:08] of outcomes. Yeah. and and what's the [44:11] constitution of the the S&P is a quirky [44:13] index like you know it's 35% the grade [44:16] eight you know Broadcom plus the other [44:17] seven um it's probably 60% an AI ETF [44:21] semi ETF I mean if you take like G [44:23] Vernova and Vistra and Constellation and [44:26] uh eaten [44:29] derivative beneficiaries of industrials [44:32] what he said right it's about the [44:33] forward expectations like that could be [44:34] wrong it could modify itself but like [44:36] yeah what what you just said is semis [44:37] have been better than energy stocks yeah [44:39] no [ __ ] So, but like is there [laughter] [44:40] an up is there an upward balance? The [44:42] >> probability you were gonna show a chart [44:44] that I wasn't going to [ __ ] on was [44:46] incredibly low. [laughter] [44:48] >> Is there especially from a competitor? [44:51] >> I don't even I don't even know what that [44:52] is. [44:52] >> Is there is there an upward bound to to [44:54] this? [44:55] >> Of course. [44:55] >> What is it? [44:56] >> 6 months before estimates uh to prove to [44:59] be too high. [45:00] >> Okay. I have to disclose though we are [45:02] happy consumers of strategic. [45:04] >> Yeah. is a great guy and I like I I'm [45:05] not there's no there's no crit I'm [45:07] there's a big world lots of people doing [45:08] interesting stuff but like I just think [45:10] when it comes to like statistical [45:11] significance or this kind it's an [45:12] interesting observation but like it kind [45:15] of makes more sense to me like you said [45:16] you asked me a while ago like is this [45:17] the craziest thing you've ever seen like [45:19] I've seen a lot of crazy stuff not [45:20] really it's more crazy to me when like [45:22] zero revenue stuff goes crazy or you [45:24] know like that's a little bit more weird [45:26] to me than um Micron Trade's at four and [45:29] a half times next year's earnings the [45:30] earnings are 100% higher than they were [45:32] a few weeks ago and there's a shortage [45:33] as far I can see in their core product [45:35] and you can't produce anything without [45:37] >> how does a price how does a price find [45:39] balance [45:40] >> like I know it's when buyers and sellers [45:41] you know sort of match up but like how [45:43] should investors think about I can't buy [45:45] this now [45:46] >> so SanDisk micron like [45:48] >> how do we [laughter] [45:50] usually [45:52] >> this is just the fact of the matter the [45:54] price movement once it starts until [45:57] something knocks it off that that [45:58] trajectory an object stays all the time [46:02] >> I do And it and it's absolutely [46:05] >> You know what I say all the time and I [46:06] say this on the show especially people [46:08] say I took a profit. I took a profit. [46:11] Nothing wrong with taking a profit and [46:12] then I look at the [46:13] >> sure there is you pay taxes. [46:15] >> That's a great buy signal. [46:16] >> I look at the chart and the chart always [46:18] looks like this grind higher and my [46:21] comment is like okay but why today? Why [46:24] don't you just trail it? If you're [46:26] nervous throw it throw a like a 10day [46:29] moving average stop loss. trail it [46:31] behind the share price and let the [46:33] market take you out. Why are you [46:35] deciding that this [46:36] >> just evaluate the sell X post and say [46:38] did my sell work versus some some [46:39] comparable basket bait adjusted and and [46:41] that destroys value [46:44] I'm saying like do real work like do [46:46] evaluate whether that trading decision [46:48] makes sense like I I'm with and we're [46:49] all agreeing I just you know we do this [46:51] for a living I get people's portfolio [46:53] >> saying you have a stock that's been [46:54] going up for three years [46:55] >> I'll say today's the day you took a [46:56] profit [laughter] I'LL SAY IT I'LL SAY [46:58] IT DIFFERENTLY I'll say it differently [47:00] do you think if you buy stocks that were [47:02] just up 100% today you'll make more [47:05] money or should you buy stocks that were [47:07] just down 50% dependent obvious for sure [47:10] obviously to who not obvious to everyone [47:13] who cares what it already did all you're [47:15] trying to think about is what do I do [47:17] today and what's going to happen in the [47:18] foreseable [47:19] >> care what it already did if it's gone [47:22] parabolic and you're the last [ __ ] [47:24] buying it if it's a grind higher that [47:27] went that took time I can buy that chart [47:30] and I do and I do [47:31] >> not a stock that doubles in three months [47:33] that's [47:34] It's the rate at which it went up. [47:36] >> Actually, that I'm not saying I'm [47:38] surprised, so there's no surprise in my [47:39] voice, but you actually had a good idea [47:41] there and we'll study that. We can look [47:42] at like stocks that have gone up. [47:44] >> Oh, I've already done this [47:45] >> 100%. And [47:46] >> I'll send I will send you my work on the [47:47] subject. It's called the best stocks in [47:49] the market. I will not get bullish on a [47:51] stock that just went from 30 to 60 in a [47:54] week. I understand it could go to 90, [47:56] but if you just don't do those and focus [47:59] on the stocks that climb, but that's [48:02] institutions. [48:02] >> You know what? You can't study that [48:03] because a lot of the stocks that go from [48:05] 30 to 60 today, that's the meme [ __ ] and [48:07] that didn't exist in the back test. [48:08] >> Okay. So, we can study that. We can [48:10] study every different No, no, no. I'm [48:13] just saying challenge me, dude. [48:16] >> My point is there was the Reddit boards [48:18] were not here in the 80s. [48:19] >> Can we do something that you just wrote [48:21] up? Uh, spin-off playbook. [48:23] >> Yeah. [48:23] >> Okay. This is original Adam Parker [48:26] research. [48:27] >> Uh, [48:30] variant. I'm gonna quote I'm gonna quote [48:31] you to you and then I'd I'd love for you [48:34] to I'd love you to go off King. [48:35] >> Hopefully this isn't as bad as my [48:36] healthcare call. [48:38] >> No, no, no, no, no. [48:39] >> You [snorts] said in 2025, the median [48:41] spin-off reached a 26-year peak [48:44] transaction size of 3.3 billion across [48:48] 11 transactions. So far this year, only [48:51] one spin-off has been completed. Comcast [48:54] spun off Versent. Okay. Um [48:56] >> channel you and I both go on. [48:58] >> That's right. Um, but two have been [48:59] announced, MSGS and GPC, which he'll [49:03] tell us about. Several more are rumored. [49:05] 20 spin-offs were announced in 2025 that [49:08] have yet to be completed, and six of [49:10] these companies are midcap or larger. In [49:12] today's research, we provide context [49:14] around the spin-off performance, analyze [49:17] historical market reactions, and supply [49:19] our playbook for the future. I want to [49:21] say one thing before you go. [49:22] >> What is a spin-off? I love spin-offs. [49:25] Dating back to my time as a retail [49:27] broker, telling stories, begging for [49:29] money. We pitched [laughter] the parent [49:32] companies of spin-offs ritualistically. [49:36] Almost didn't matter what it was because [49:38] the pitch to the people on the other end [49:40] of the phone was you own threecom, guess [49:43] what? You're also going to get palm. [49:45] Like that would be and people wait I get [49:47] >> people love catalysts. I get two love a [49:50] catalyst and I get two stocks for the [49:52] price of one. They didn't understand the [49:54] fact that the price of the parent would [49:55] adjust on IPO day. They just love they [49:58] love the idea [49:59] >> remain co. [50:00] >> Wait for Adam for real. I know where I [50:02] come from. Adam, why do people uh why do [50:04] companies spin spin-off companies? [50:06] >> Usually I think the primary share [50:08] >> would be tax would be a tax reason, [50:10] right? It's usually a tax reason. So [50:11] like if you meaning meaning like if I'm [50:14] uh we both used to work in Morgan if I'm [50:16] Morgan Stanley and I sell Discover [50:18] because I made a ton of money on it. If [50:19] I if I sell it I to somebody else I have [50:23] to pay taxes on it. If I spin it there's [50:24] a massive tax. So there could I would [50:26] say that's the primary driver but it [50:28] could be unlock value. Do you think [50:30] there's an underappreciated asset? You [50:32] it could be that there's [50:34] >> new management of the spin co which will [50:36] be more focused on that one capital [50:38] structure optimization disinergy like [50:40] there's a list but [50:41] >> valuation [50:42] >> but I would say yeah I would say taxes [50:44] are usually the driver now I I guess [50:47] like there's there's a lot of things you [50:49] first of all like what you used to sell [50:51] I would say empirically show is not a [50:53] good idea. [laughter] [50:54] >> The spin co do I'll go back to I'll go [50:57] back to 1998 and apologize to people. [50:59] >> Yeah. Uh the spin co typically on [51:01] average do better than the main coast. [51:02] But you know it's an interesting point [51:04] you're making. You made me think of [51:05] something really kind of interesting [51:06] which is um one of the signals that [51:08] works in quan and it's kind of pesky and [51:10] it works is is a signal called low [51:12] price. [51:13] >> So we think about how stupid that is [51:15] like low price means it's no denominator [51:18] like just generally like stocks with a [51:20] lower price stocks with a higher price. [51:22] And you could study that [51:22] >> retail people like to buy low. [51:24] >> They think it's like $2 is better than [51:26] four independent of like denominator. [51:29] >> Yeah. Buy low. [51:29] >> So your [laughter] your logic could have [51:31] been two stocks instead of one is kind [51:33] of funny. It probably used to work. [51:35] >> It did work. [51:36] >> Yeah. [laughter] But but recently in the [51:38] last decade plus since there's been like [51:40] computers um [laughter] you know the [51:42] spin codes usually do better because [51:44] typically when they spin them um they [51:46] they know the numbers and the estimates [51:48] are pretty achievable for the next [51:49] couple quarters. They have a path toward [51:50] margin expansion or something. the [51:51] market likes and usually they're [51:53] spinning something in a different [51:54] industry. So, you know, there's some [51:56] some rationale. I I think, you know, we [51:58] have a lot of clients that are law firms [51:59] and and boards and managements of [52:01] companies and I think they're just all [52:02] looking to unlock value. If you're a 40, [52:04] 30, 50 billion market cap company, 20, [52:06] 30, 40, you're sort of thinking like, is [52:08] there a plan I can get like big? Can I [52:09] get to 100 billion someday? How do I do [52:11] it? How do I unlock value? And so, [52:13] you're just looking at transactions. [52:14] You're just saying like, can I buy [52:15] something? Can I sell something? Can I [52:16] do something with my capital structure? [52:18] And I think more importantly, if you're [52:20] a good person, you probably want to be [52:21] perceived as a good steward of capital [52:23] over your tenure managing the company. [52:24] So I I think spin codes are top. [52:27] >> You're saying the spin is better than [52:28] the parent or the parents? [52:30] >> On average, the spin is better than the [52:31] remain co [52:33] but on average is tricky because some of [52:34] these are so specific. [52:36] >> I think [52:38] generally you want to buy the spin co, [52:40] not the remain. [52:41] >> Okay. Yeah. Um, I mean it makes sense to [52:43] me just anecdotally thinking about some [52:45] of the big winners from spin-offs that I [52:47] like Zoetis coming out of Fizer. [52:50] >> G Verno monster was a monster. Like some [52:53] of these I think of our 10 baggers and I [52:56] remember what they came out of. [52:57] >> The original 12month performance out of [52:58] the UTX spin where you got, you know, [53:00] Carrier and and and Otis and was a 20 [53:03] was it a 2025 spin or 2024? [53:06] >> Maybe 2022, I think. [53:08] >> Yeah, a couple years. Yeah. [53:09] >> Okay. this I mean this is this but [53:10] >> we we just think generally like if [53:11] you're a human being analyzing stocks [53:13] like where where can you add value [53:14] machines are going to kill you in a lot [53:16] of places but humans are going to add [53:17] value whenever there's like a management [53:19] decision-m creating or destroying value [53:21] so I love analyzing stuff like M&A [53:24] show I know I know you had any [53:26] >> all right John let's go through this you [53:27] could just narrate for us like briefly [53:29] what each of these [53:30] >> I'm surprised you find this is super [53:31] interesting I I I just I I mean thanks [53:34] for anytime you throw our our work on [53:35] the screen I'm I'm [53:36] >> triariat ladies and gentlemen [53:38] >> I'm all in thank Yeah. Uh, no, I just I [53:40] I guess I just think that like [53:42] >> the law firms and the bankers are [53:45] pitching management teams on doing stuff [53:47] and one of the things that they they can [53:49] point to success for is is spinning. I [53:52] and I just surprised there haven't been [53:53] more. You can tell on the left there's [53:54] been 20 30 of these things a year and [53:56] there's only been a couple recently and [53:57] I just feel like there could be a wave [53:58] of these things going forward. Generally [54:00] midcap companies do it, not mega cap [54:02] companies. It's going to [54:03] >> look at the return look at the returns. [54:05] Uh, Spin Co. is black. Remain color is [54:08] blue. And I mean, [54:08] >> yeah, maybe maybe I don't know what the [54:10] next slide is. Can you show me what else [54:11] you download? Uh, a couple more. Maybe [54:13] go flip ahead. How many did you put [54:14] take? [54:15] >> Every single thing. [54:16] >> Keep going. Keep going. I'll show you [54:17] the [laughter] [54:18] >> even the ones you didn't publish. I [54:19] found them. [54:19] >> One more. One more. Keep go. See what [54:21] you have. Keep going. So, I think [54:22] there's like a line chart. Yeah. The one [54:24] on the right here is the mean industry [54:26] group relative return. So, this is how [54:27] the stock did versus its industry [54:28] because I didn't want it to be like [54:29] SanDisk was awesome and you're not [54:31] normalizing for the industry, right? So [54:33] the black line is the typical spin co [54:35] performance and that x-axis is the [54:37] number of days. So like kind of 252 [54:39] trading days in a year. So two years out [54:41] the average spin beats its industry by [54:43] 10% and the average remain kind of lags [54:45] by a couple. So [54:46] >> I mean that is statistically significant [54:48] number and that's robust across sectors [54:50] >> pretty much. Yeah, pretty much. [54:52] >> Okay. Yeah. [54:53] >> Love it. Well done. Well done. [54:55] >> Now Rob, would you like to unveil your [54:57] research on spin-offs? [laughter] [54:59] >> I we we don't have that in the bag. It's [55:01] It's Triarians really. [55:03] >> Well, but no, but you know, whatever. [55:04] >> Why would Why would we do it twice? [55:07] >> Uh, I wanted to ask you about some of [55:09] your favorite stocks this summer. Um, so [55:12] let's you you you and your team gave us [55:15] a couple to talk about. Let's let's hear [55:16] what you think. [55:16] >> Hold on. We're skipping spring. Is this [55:18] like these are only going to work in the [55:19] spring? [55:19] >> Yeah, only for only for the summer. [55:22] >> Don't buy these until the [laughter] [55:22] summer. [55:24] >> Outside. I don't know if I can operate [55:27] with that level of precision. However, I [55:30] think it's a balanced way to think about [55:32] how you invest at this time in possibly [55:35] going into summer. And it's a marriage [55:37] of, you know, putting together the [55:39] highest conviction names that are at [55:41] their all-time highs, right? [55:43] >> No question. married with some [55:46] beneficiaries of that in in energy, NRG [55:49] specifically, and and married with uh [55:52] you know, energy uh you know, producers [55:56] that I think could benefit from further [55:58] crisis in the Middle East. And then for [56:01] the sake of Adam, we put in Gilead [56:03] because we think you got to have a [56:05] healthcare name in there. Um, and so [56:07] you're you're you're putting weight on [56:09] two different skis and adding something [56:11] a little different that I think is [56:12] reasonably attractive. [56:13] >> Yeah. Broadcom here, king of uh this [56:16] from your team, king of custom silicon, [56:18] data center, networking, infrastructure, [56:20] position to win as hyperscalers spend [56:22] more. Uh, I mean, this stock has [56:24] obviously been a huge winner. I know you [56:26] guys have made a lot of money with it. [56:27] You still like it here? We [56:29] >> we do. It's it's the object in motion [56:31] stays in motion. and they're on track [56:33] for 60% revenue growth this year. They [56:36] have industry-leading profitability. [56:39] Uh they're a leader in both C custom [56:41] silicon data center networking hardware. [56:44] >> The market is not stupid. [56:45] >> Could you have more taking this taking [56:47] this stock to where it's taken it? [56:48] >> No, not at all. I think where the market [56:50] was stupid was in April of 23 where you [56:54] had all the other names doing what they [56:56] were doing and this one was left behind [56:58] and it was trading as a teenager. [57:00] >> Oh my god. I just said it's a trillion. [57:02] It's two. [57:03] >> Yeah, it's it's it's unbelievable. [57:06] >> Lam research is 4.0. [57:07] >> I love this. I love this stock. It's up [57:10] >> we wrote it up for best stocks in the [57:11] market last August. I think it's up 170% [57:14] since then. [57:15] >> I want to point out we wrote it up at an [57:17] all-time high. [57:18] >> People were ang like angry like now [57:21] you're saying you like it. It's up [57:23] however much. It's up another [57:26] >> I always like stocks at higher prices [57:27] than I used to not like. It's up 297% [57:31] over the last year. [57:32] >> I mean, they basically control their [57:34] entire [57:35] >> cause monopoly. They're essential in the [57:38] chip manufacturing [57:40] uh equipment. [57:41] >> What's what's NR what is NRG? [57:44] >> So NRG's a derivative beneficiary of [57:47] what's happening in AI power is the [57:49] bottleneck. You know, [clears throat] [57:50] Vista Energy as well. We were on Vista. [57:53] We had such a move. It was I think the [57:55] number one performing stock. I'm trying [57:57] to think of the [57:57] >> EST. That thing was insane. [57:59] >> And we bought it in January at the end [58:01] of the year and it moved so much that we [58:03] decided to diversify because NRG was [58:05] lagging. So we we we kept Vistra. We [58:09] added NRG under the same portfolio [58:12] theme. It's down from its highs in [58:14] February. It's down about [58:15] >> taking natural gas and and getting that [58:18] into the electricity that the data [58:20] center needs. [58:20] >> They they need it. and they're big in [58:23] this bring your own power deals where [58:25] they sell directly to the data centers [58:28] which is kind of a unique and novel [58:30] strategy and I think it's I think it's [58:32] going to work and it's trading at 16 [58:33] times [58:34] >> uh right now [58:35] >> APA [58:37] >> APA is more of a [58:38] >> blast from the past for me [58:39] >> yeah just in ENP name it is up 58% year [58:44] to date it's off 14% from its recent [58:47] high [58:47] >> you need Iran to stay up to stay long [58:49] this stock or do you like it either way [58:51] you need things to not open quite as [58:54] quickly. I think this is going to be a [58:57] beneficiary of America doing what we're [59:00] doing from a production standpoint and [59:03] it's a great combination of a lot of [59:05] diversified production across regions [59:08] products. They have a healthy loyal [59:11] healthy total yield 12% between buybacks [59:14] and dividends. It trades at seven times. [59:17] It's crazy. This is an interesting [59:20] business to us. And then lastly, Gilead, [59:23] which has [59:23] >> You did that for Adam? [59:24] >> Well, yeah. [59:25] >> Diversification. [59:27] >> Diversification. [59:28] >> No, the stock looks stock looks great. [59:30] It's actually been a strong in this [59:32] group with the group has sucked for a [59:34] while, but this is one of the this is [59:36] one of the winners. I think you have to [59:37] have some exposure in this space. Again, [59:39] this is the upgrade in the quality. [59:42] They're dominant in HIV. They're doing [59:44] unbelievable things in oncology. They [59:48] have 50 drugs in various stages of [59:50] development. They're enormous. So, and [59:53] you have to be enormous to be able to to [59:55] to do what they're doing. And there's [59:58] upside in their pipeline based on [60:00] progress. So, we tried to think, I asked [60:02] the team, this is not me, I'm going to [60:04] take no credit. This is Jay Peters. This [60:06] is Cameron Dawson. This is Brian Nick, [60:09] our investment team. They're super. And [60:12] I asked them, I I said, I want a [60:13] balanced view where you have option. We [60:15] can ride the current wave we're riding. [60:17] You have optionality to the crisis. So [60:20] three names ride the current wave, [60:22] right? Power and then the two semis. You [60:25] have option to crisis in the Middle [60:26] East. And then we get some stability [60:28] where you're not going to have a lot of [60:30] price performance. We want a healthcare. [60:32] >> Are you surprised that the health care [60:34] stocks aren't getting any credit in [60:37] advance of being perhaps the biggest [60:41] beneficiaries of utilizing AI? So, look, [60:44] it's been our [60:45] >> Why aren't people [60:46] >> It's been on our barriers overweight [60:47] call. It's been a terrible call, unlike [60:49] the soft one. This this been a bad call. [60:52] And um I um trying to figure out like [60:55] what could untether me from the thesis. [60:56] I'm trying to be like intellectually [60:58] honest like could anything change my [60:59] mind [61:00] >> long term should be no by the way. [61:02] >> Yeah. And I I'm I'm worried about it [61:03] because I don't want to be the jerk who [61:04] just [61:05] >> Is that your thesis that AI is going to [61:07] be bigger for these companies than most? [61:09] So what the market's telling me is [61:12] there's a 0% chance healthcare is the [61:14] best performing sector over the next 5 [61:15] years and I think it's like 30 or 40%. I [61:17] just start with like I want to arbitrage [61:19] that difference. I think the whole point [61:20] of all of this [ __ ] is that we live [61:22] longer and we're more productive while [61:24] we're alive. [61:25] >> So if I take that premise [61:27] >> I don't understand how healthcare [61:29] revenue per share is going every year [61:30] 30s in a row in SB500. We have lots of [61:32] old people that demand services tool [61:34] diagnostics drugs managed care [61:35] hospitalization whatever that's steady. [61:37] We have tons of businesses with lots of [61:39] employees, low margin, and lots of [61:41] revenue. Meaning, as long as I can [61:43] predict my customer employee behavior, [61:44] margins should go up. It's a classic AI [61:46] productivity potential. They do, as he [61:48] just pointed out beautifully, have low [61:50] correlation to AI semis. So, you don't [61:51] want to buy low correlation, meaning [61:53] like they suck, but there are a bunch of [61:55] healthcare stocks, Lily and others that [61:57] are up 10% or more in the last 6 months [61:58] and are uncorre [62:02] I'm very tethered to the thesis and [62:04] bullish and I do think to me, which [62:06] names do you like? is not working. [62:07] >> McKesen, Cardinal, Sincora, Quest, Lab [62:10] Corp, you know, even stuff that blew up [62:11] recently because like you're you're [62:14] still young. You can't go to the doctor [62:16] and not end up sending something to [62:18] Labcore Quest. There's zero chance they [62:20] won't grow above GDP. And there's still [62:21] dudes with like when we were kids with [62:23] the glass microscope with the thing like [62:25] the efficiency potential is massive, [62:27] >> right? And I would even say manage care. [62:28] Uh had a good point this week stock was [62:30] finally up like I run a business. Let me [62:32] tell you, [62:32] >> I'm not brave enough. [62:33] >> Let me tell you who raises pricing on me [62:35] 9% every year. And guess who doesn't [62:37] give me 9% more services. So like I [62:39] think they're going to earn more money [62:40] in 2030 and I don't think there's any [62:42] political will from either side to [62:44] change the algo. If you tell me that [62:46] some parties going to come in and [62:48] implement massive austerity then I'll [62:50] change my mind. [62:51] >> So it sounds like healthcare away from [62:53] big pharma. [62:54] >> I think there's still some good big [62:55] pharma. I mean I'm not against you know [62:58] and other stuff. [62:58] >> Lily is unbelievable. [63:00] >> But I'm not embedding yet. Um, what I'd [63:02] like to do is be correct on a five-year [63:05] view and then there's all kinds of like [63:07] computational chemistry ETFs that retail [63:09] guys are buying and I'd like to sell my [63:11] correct overweight into that euphoria 5 [63:13] years from now. But that's I got a lot [63:15] of good shit's got to happen before I [63:16] get to that call. [63:17] >> Uh, I want I want to ask I want to ask [63:20] you I want to ask you about um about New [63:23] Edge and founding the firm and uh Adam, [63:28] by all means, chime in. Like when I [63:30] first met you, you were uh UBS. You had [63:33] one of the biggest teams in the firm. [63:35] >> Mhm. [63:35] >> You were not talking about going [63:37] independent, but I'm sure you were [63:38] thinking about it as most people at [63:40] large firms often do. [63:42] >> Mhm. [63:42] >> What have you learned since coming into [63:45] the RAIA space? [63:46] >> Obviously, you've built a massive [63:48] platform, big firm, hired a lot of [63:50] people, met a lot of people. What are [63:52] like some of the things that you you [63:54] think uh you've you've learned in the [63:56] last couple of years since doing that? [63:57] Well, first off, [63:58] >> was it four years ago? [63:59] >> Uh, five [64:00] >> five years. Okay. Five five years ago. [64:02] And we've grown from 8 billion to 105 [64:05] billion in assets. So amazing. It's been [64:07] it's been a [64:08] >> It's not as good as Micron. It's not as [64:09] good as micro as it is, but pretty good. [64:11] >> But I I I think that the things that [64:13] I've I've learned are one, there's a lot [64:16] of noise in the ecosystem. Not everybody [64:19] says can do what they say they can do. [64:22] And what that does is it creates a lot [64:24] of paralysis in this migration that [64:27] we're seeing from from advisers at big [64:30] firms to advisers at more entrepreneur. [64:33] I mean look at what you've done here. I [64:34] walk into this office and think oh my [64:37] god this is great. I mean you're adding [64:39] value in a different way and you're [64:42] adding value by sitting center. And when [64:46] you're a client of a the street versus a [64:49] competitor of the street, you have a [64:51] structural advantage that's very [64:53] meaningful. You don't have one arrow [64:56] that you can pull out of your quiver. [64:57] Let's say you were doing a loan for [64:59] somebody. You're going out to multiple [65:01] providers. You have tools. [65:03] >> So if you're sitting at Goldman Sachs, [65:04] you're doing that loan through Goldman [65:06] Sachs. If you're a customer of Goldman [65:07] Sachs, give me a quote. Okay, I'm going [65:10] to go to RBC. See what they say. [65:12] >> You're not with them. across from them. [65:15] And yet, New Edge is a gigantic client [65:17] of Goldman, JP Morgan, all the different [65:20] banks, all the different capital markets [65:22] groups, all the different asset [65:24] managers. And I do think size and scale [65:27] matters. There's something else that's [65:28] kind of happened in the industry. And I [65:30] don't want to mask the good fortune and [65:32] luck that I had in doing this in 2000. [65:35] just as this was taking off at the [65:37] higher end uh not 2020 at the higher end [65:41] of the market during co um it looks [65:45] easier than it is. [65:46] >> Oh, I couldn't agree more. [65:48] >> Say say more about that [65:49] >> and you need a good partner. So I did [65:52] not start New Edge. We did an LBO of a [65:56] business with a tremendous partner in [65:58] Parthonon Capital and that operating [66:02] business threw off cash flow. Again, it [66:04] was an infrastructure business providing [66:07] institutional-grade infrastructure in [66:08] the 401k industry to Fidelity, John [66:12] Hancock, paychecks, creative planning, [66:14] and they had a great business, but they [66:16] wanted to do something else. So, we [66:17] bought the business and we took built a [66:20] wealth business on that same [66:22] infrastructure that was bulletproof, [66:25] cheating, starting halfway up the [66:27] mountain. I didn't have to go in and [66:29] worry about, did I had a tech team? I [66:31] had not only a tech team, but I had [66:33] profitability to hire the best and [66:35] brightest. Okay. So, the good fortune [66:38] that came from that simple decision of [66:41] not worrying about how my computer was [66:42] going to turn on in the morning. That's [66:44] why I love these entrepreneurs that do [66:46] this grassroots and bootstrap this [66:49] unbelievably hard. [66:50] >> It's way it's way harder than it looks. [66:52] >> And now you have partners that can help [66:54] you get from A to B. So when I think [66:56] about what we do is we have a fully [66:59] evolved ecosystem where you can join us [67:01] and use the platform turnkey here's [67:03] everything you got all the support the [67:05] compliance the anything you need or we [67:09] are going to sponsor you in your [67:10] entrepreneurial endeavor and we have the [67:13] best business in the world to do that [67:14] that's run by my partner Alex Gos. We [67:17] also had some very fortunate hires and [67:20] partners in this business. Um Chuck [67:22] Warden who was the founder of the [67:24] business that we bought, Parthonon who's [67:26] the private equity firm, John Strauss [67:28] who ran every major private bank on Wall [67:30] Street, JP Morgan, Morgan Stanley, uh [67:34] UBS ran them all. Bob McCann joined us. [67:38] So we had UBS and and Meil Lynch. So, we [67:41] had these credentialed folks that when [67:44] you're looking off the cliff and you're [67:46] an advisor and you're you're getting [67:48] ready to jump, you still can't see the [67:51] bottom. [67:52] Okay? And you want to know that there's [67:54] knowledge, knowhow, and people down [67:57] there that are going to help you [67:59] navigate every decision, whether you're [68:01] starting your own thing on our platform [68:04] that's run by Alex. [68:06] >> To that point, like somebody coming [68:07] somebody coming out of an environment [68:11] like a Bank of America or a Morgan [68:13] Stanley, [68:14] >> there might be things they don't love [68:16] about those banks, but the one thing [68:17] that's undeniable is they have a ton of [68:18] support. like [clears throat] they don't [68:20] wake up in the morning. [68:22] That's what was missing in the [68:23] marketplace is this fully supported DNA. [68:26] And so I'm no longer the CEO. You [68:28] introduced me as the CEO. I am the [68:30] founder. Okay. So I made a big hire last [68:34] year. [68:34] >> You hired somebody to talk to the to to [68:38] speak to that CEO role so that you could [68:41] be Rob Sin. [68:42] >> I can be Rob C. [68:43] >> I did I did the same thing. [68:44] >> So it is a it is a great thing. We hired [68:47] James Jesse. You know him from Morgan [68:49] Stanley days, I'm sure. James Jesse ran [68:52] Morgan Stanley International, right? But [68:54] then he went with Devesh and helped [68:55] start Iconic. Okay. Wanted to come back [68:58] east coast. That was our good fortune. [69:01] We also because of the because of the [69:03] profitability from the business that we [69:05] bought were able to hire people like [69:07] Cameron Dawson who I think is one of the [69:09] most fascinating thought leaders [69:10] [clears throat] [69:11] in in the industry. So when you marry [69:15] all those things together and you can [69:17] create an entrepreneurial environment [69:19] that is doing the right thing and trust [69:22] me net present value of doing the right [69:24] thing creates more value than anything. [69:27] So great technology. They're not rolling [69:29] out enterprise anthropic. Not a single [69:33] firm yet. They're trying it. They're [69:35] test. We are fully rolled out. [69:37] >> They're not using tech of better price, [69:39] execution, visibility in the assets. [69:41] They're not partnering with Adam. [69:43] They're not partnering with Tom Lee. [69:45] They're not working with families. [69:46] They're not surrounding those families [69:48] with high-end intellectual capital. And [69:50] they don't have access to each other's [69:53] [ __ ] And we have access to everything. [69:56] And so when you have a better mousetrap, [69:59] it is undeniable [70:01] that the migration will happen when [70:03] there's more confidence and less [70:05] confusion. But everybody tries to tell [70:08] that story and not everybody can deliver [70:11] that story. And as such, advisors [70:13] haven't moved in mass yet. Once a few of [70:16] the big ones fall, as you know, [70:18] >> you think the you think the the [70:19] wirehouse exodus hasn't even really [70:21] started? [70:22] >> It's it's it's here. Wow. Because I so [70:26] the corner [70:26] >> I know like I know five guys that were [70:29] five billion plus dollar teams duos just [70:33] at one firm that have left in the last [70:35] two years [70:36] >> that how many more [70:38] >> that started that started about two [70:39] years ago you can't believe our pipeline [70:43] >> you just can't and the the one thing [70:45] that I would say is firms that can't [70:47] address the entrepreneur that wants to [70:50] have their own CIO not Cameron and fir [70:53] and others that want to have that. [70:56] >> Yeah, [70:57] >> we have those bookends in a leader that [71:00] has operated in the wires and in the [71:02] probably one of the best firms in the [71:04] independent space and iconic. [71:07] I think that is confidence inspiring and [71:09] I think you know we've become a partner [71:12] of choice. I mean it's growing if you [71:14] have advisers if you have advisers in [71:17] your ecosystem. [71:18] Let's say you had [71:19] >> By the way, I just want to say that was [71:21] like a highlight of this this great [71:23] speech was just electric. [71:24] >> Yeah. I'm just saying I mean passionate [71:26] about this. [71:27] >> No, I loved it. I just think like you [71:28] you you I'm not saying the stock part [71:31] wasn't great, but I'm just saying like [71:32] the EQ IQ combo that just came out from [71:34] describing this business was was [71:36] electric. [71:36] >> That's why I do more. [71:38] >> I'll be serious. I mean, I'm serious. [71:39] You felt it, right? It was all of a [71:40] sudden a few fuse got awesome. If you [71:42] have an adviser who's a card carrying um [71:45] new edge like all the way in who comes [71:48] to you guys and says you know what this [71:50] has been great but what I really want is [71:52] to have my firm under its own name my [71:54] own CIO so now you have a place where [71:57] that person can go where they don't have [71:58] to leave [71:59] >> come in straight [72:00] >> so I think that's powerful [72:01] >> right turn left turn we have businesses [72:04] over here that we bought into card [72:07] carrying businesses remember when we buy [72:09] you in You are owning the same stock [72:13] that we did in the LBO. No difference. [72:16] Not like some of the firms that had [72:18] failed in the past. We have the [72:19] advantage of being the vitamin water [72:21] versus the Gatorade, right? And all this [72:24] we second mover advantage and you know [72:26] it's it's it's been pretty powerful to [72:29] identify the flaws of our predecessors. [72:31] And what ends up happening is if you [72:33] just do the right thing for the [72:35] adviserss, meet them where they are. I [72:37] think you're advantaged in this too, [72:39] guys. [72:39] >> [clears throat] [72:39] >> You're a firm that was started by [72:41] advisers for advisor. That is a huge [72:43] advantage because why are you going to [72:46] do something that damages yourself now [72:49] what I recognized is there could be a [72:52] better daytoday nuts and bolts leader [72:55] than me. I am a champion of the organiz. [72:57] I have one concern. How do those [73:00] advisors that believed in this field of [73:04] dreams that we bought and built, how do [73:06] we drive value for them both in their [73:10] practice, in their in serving their [73:13] clients and then ultimately in the [73:15] equity value that they've taken on in [73:17] our company and I take that very [73:20] seriously and if it means shooting [73:22] myself. [73:23] >> Yeah. Well, I don't care. [73:24] >> So, this is a very this is a very big [73:26] thing. It's a very it's a very by the [73:28] way very well done. [73:30] >> Thank you. [73:30] >> If this is a very big thing at a certain [73:32] point you have to make the decision what [73:35] is my highest value to the firm. Is it [73:38] sitting in eight meetings a day and [73:40] micromanaging 50 people or is it being [73:44] me and bringing in professionals to [73:46] handle the [73:46] >> I think no matter what you do you have [73:48] to think about that right now. Like I [73:49] like you obviously it's I'm in a [73:51] different business and it's a small [73:52] scale but like we have guys who like [73:56] whenever I I've become very [73:57] self-conscious about this when I'm in [73:59] front of my computer typing and one of [74:00] the quant guys who works for me is [74:02] standing behind me I know they're [74:04] thinking like this guy doesn't know how [74:05] to use a computer [74:06] >> like the best use of Triariat's time is [74:09] not when I touch the keyboard [74:11] >> not when you are physically doing if I [74:14] am doing something they're like no don't [74:16] do that and so I started realize like [74:18] all right like we got and it's like and [74:20] all this AI stuff too like it's it's [74:22] like we got to be you know so I don't [74:23] know I I I mean that's an honestly I [74:26] >> I never you like but [74:28] >> I never really heard you articulate [74:29] that. I'm not surprised at all but it [74:31] was awesome listening to that. [74:32] >> You like the entrepreneurial part though [74:34] of what you're doing. [74:34] >> I love it. I I totally love it. I don't [74:37] like um [74:38] >> you know [74:38] >> you're not one of these guys that's like [74:40] just let me do my research like you [74:41] actually enjoy building the business. [74:43] >> I do. I like thinking about what the [74:44] enterprise is going to look like. You [74:45] know we have this newsletter business [74:46] that you know about Trictor. We've got [74:48] uh you know we'll probably end up doing [74:50] um you know some stuff on the asset [74:52] management side. I'm doing some stuff [74:53] with investor relations. I do stuff for [74:55] law firms and boards. I'm joining the [74:56] board of a public European company uh [74:58] next week is when it's official. So like [75:00] I'm just always trying to do new stuff [75:01] and learn stuff and and I I'm like kind [75:03] of uh I like doing the the work and I [75:05] like talking to people. [75:06] >> Do other guys who sit in your old seat [75:08] as chief strategists on Wall Street come [75:10] to you and say, "Hey, what's it like uh [75:14] being independent?" Like [75:15] >> it's a little bit like your [75:16] conversation. you were just having which [75:18] is like you you don't you you you might [75:22] have disgruntled issues with the big [75:24] firm and the bigness disease of the big [75:25] firm you work at [75:26] >> but you're getting a lot from them [75:27] >> but you're also getting a lot and so [75:29] when you go on your own like you're [75:30] going to be washing the dishes uh and [75:32] putting the mayo and the sandwiches the [75:33] first couple years and like you've got [75:35] to decide like a am I rich enough to [75:37] take the risk and if it doesn't work you [75:39] know or whatever there's like [75:40] considerations that go into it [75:41] >> Michael and I were literally licking [75:42] envelopes like like in in real life [75:45] >> I we we don't have a dishwasher at [75:47] Triarit and like all the young kids [75:49] don't understand that like I'm the one [75:50] who washes their mugs and that's like [75:52] today that's still like like so you know [75:55] so like whatever like you got to you got [75:57] to do that but like at the end of the [75:58] day um [76:00] >> for me it was worth it and I was a point [76:02] where I wanted to take a shot and I love [76:03] it but like I love listening to you you [76:05] guys talk about you know five year plan [76:08] >> everybody does it differently but I [76:10] don't know anybody that would say [76:12] anybody [76:14] I I want to go back [76:15] >> I wish I could go back I've never heard [76:16] It's like moving to Florida. Does anyone [76:18] say [ __ ] This is terrible. [76:20] >> You're talking [laughter] to You're [76:20] talking to a guy who's on a 720 tonight. [76:22] >> No, I know. [76:23] >> Hey, last last thing we wanted to last [76:25] thing we wanted to get to. [76:27] >> Uh BMNR. [76:28] >> You're okay. So Tom Lee launched What is [76:31] How do I explain it? [76:32] >> It's a Ether Treasury company. It's like [76:34] it's like a Micro Strategy for Ether. [76:36] >> All right. So Tom Lee launched you. [76:38] >> You got added shortly after [76:40] >> and they're doing that's what they're [76:42] doing, right? They [76:43] >> asset treasury company. I think Ethereum [76:45] is a bit different than Bitmine or [76:48] Bitcoin rather. Um, Ethereum bit BMR is [76:52] Bitmine. I, you know, when I looked at [76:55] this, I thought this was a charlatan's [76:57] game for a long time. I I even [ __ ] on [77:00] it on TV. [77:00] >> And then you said, "Let me in." [77:02] [laughter] [77:02] >> Well, then I started to do some work. I [77:05] I started listening to Tom and seeing [77:07] the things that [77:08] >> You thought micro strategy was [ __ ] [77:10] No, I just did thought the whole [77:11] ecosystem was Yeah, I was a [77:14] non-believer. I still think that now I'm [77:16] an evangelist and what changed and and [77:18] I'll help change your mind. What What [77:21] I'm seeing is a misunderstanding of what [77:24] certain parts of the crypto ecosystem [77:27] are. And I think people think is crypto [77:30] is like a coin. It's infrastructure. [77:35] It's a valueadded [77:37] network that you build apps on and [77:40] anytime you drive usage which is why BMR [77:43] bought Mr. beast visibility, usage to [77:46] the network. You can profit from the [77:48] network. And when you think about what's [77:52] happening in traditional finance, it's [77:54] fragmented. It's intermediared [77:58] and it's slow and it doesn't run 24 [78:00] hours. And every one of them's trying to [78:03] figure out how do we get to [78:05] tokenization, digitization, and they [78:08] don't know how to do it. Um, and [78:10] Ethereum flips that. It's the safest of [78:13] all of them. It's programmable. It's [78:16] real time. It's always on. And BMNR is a [78:20] holder. And why they got me involved is [78:22] there is a huge gap gap between [78:26] institutions that have capital. And uh [78:30] they need help to translate it, [78:32] structure it, and make it usable for [78:35] them in traditional finance. And the [78:38] next phase isn't about speculation. It's [78:42] about integration [78:45] of the financial services platforms onto [78:48] an entirely new architecture. Okay? And [78:52] when you start to see what's happening [78:54] in that community and you start to see [78:57] how it's being ignored by Tradfi is what [79:00] they call it. DeFi being ignored by by [79:03] TreadFi and there's there's a bridge of [79:05] the gap, [79:06] >> but I keep I keep hearing this. The New [79:08] York Stock Exchange just says they want [79:09] to be the capital of tokenized assets, [79:12] right? They want [79:13] >> So they they'll build that on Ethereum. [79:14] >> They will. [79:15] >> So why not if I just buy Ethereum if [79:16] you're bullish on it? [79:17] >> You can't. And that's the beauty of it, [79:19] right? That's the beauty of it because [79:21] what you're becoming when you when you [79:25] uh buy let's say BMR and I'm not [79:27] promoting BMR any any source of Ethereum [79:29] but that's what I know because that's [79:31] the company that I'm the lead [79:33] independent director on. They are doing [79:35] things so that you can earn what is [79:38] called a staking yield. You can make [79:40] investments into businesses that are [79:42] going to be beneficiaries. They call it [79:44] moonshots. They invested in Mr. Beast. [79:47] got you own BMNR, you get the benefit if [79:51] there is one of the investments that the [79:53] company is making. Yes, it's not just [79:55] the price of ETH going up. [79:56] >> And by the way, when you validate and [79:59] they have a whole business that they [80:01] call Maven, which is a validator of [80:04] transactions and you get paid to [80:07] validate, you are getting a 4% 3 4% [80:12] yield. And so [80:13] >> you're earning the gas fee. you're [80:14] earning the gas so you're becoming a [80:17] toll road and then what you want to do [80:19] is ensure usage and that's why I use [80:21] this as the example [80:24] >> apps are being developed so layer zero [80:27] is this is kind of the foundational [80:29] layer security and transactions happen [80:32] happen on that layer then layer two or [80:35] apps or DAPs is what they're called [80:38] sorry I didn't mean to spit on everybody [80:41] um are being built to do functional [80:43] things, specialty nodes on that and it's [80:46] going to happen quicker, more safely. So [80:49] when you think about the threat that AI [80:52] has to everything in technology, wow, [80:56] wouldn't it be great to have this [80:58] immutable safety layer that sits beneath [81:01] that? And so I'm going to tell you, I [81:05] believe in this wholeheartedly. Now, [81:06] there's others like uh Salana that are [81:09] trying to do this more cheaply, but the [81:12] bulletproof version of this is this. Tom [81:15] Lee sees around corners. We already know [81:17] it. He's seen this years ago. Ethereum [81:21] as an asset. You can own the token which [81:24] will give you that yield. To your point, [81:26] Michael [81:26] >> Adam, how out of you? [81:28] >> He's not in yet. He's [laughter] not [81:29] out. [81:30] >> I um I I I'll go with a crazy pitch of a [81:33] different kind. [81:34] >> What does that mean? Uh, I'm going to [81:36] pitch a stock of a different kind. [81:38] [clears throat] [81:38] >> I'm going to try to I I think Nvidia [81:41] will be worth 10 trillion market cap by [81:43] the end of this decade. [81:44] >> Where is it now? [81:45] >> 4.8. [81:46] >> Okay. [81:46] >> Um, and um I think like it's [81:50] misunderstood a little bit. I think it's [81:52] um a sector. It's not a stock. I think [81:54] it's really hard to get off the CUDA. I [81:57] think it's really hard to get off the [81:58] CUDA platform. I I don't I don't think [82:00] that like it's you can do anything kind [82:03] of modeling wise in AI of scale without [82:06] >> everyone working in AI is on that [82:08] platform. [82:08] >> They they they lost money for 15 years [82:10] coding this CUDA stuff. Like the amount [82:11] of installed base that's there, they're [82:13] moving full speed ahead. Like it's just [82:14] going to be hard to get off it. They're [82:16] going to grow 15% a year for 5 years. [82:17] The revenue is going to double at least. [82:19] The cash flow is massive. And anytime [82:21] you get one of these like 12-month [82:22] periods where it like pauses out, it's a [82:25] good time to buy some before it like [82:26] flies out. I'm not selling any. Yeah. So [82:28] I I I I just [82:29] >> you and me got on that [82:32] like my my my view is like [82:36] >> yeah sure tactically I don't like it [82:37] when they blow out the quarter and the [82:39] price of sales like comes in and acts [82:41] but like I I just think they're going to [82:43] grow way faster. [82:44] >> Buy do you think they're going to ever [82:45] buy back uh a meaningful amount of [82:47] stock? They'd be seems like it's the [82:49] lowest valuation Nvidia has traded at [82:51] for a while. [82:52] >> Just just keep investing upstream and [82:53] downstream. They're gonna because trade [82:55] is the power side, right? like we talked [82:56] about earlier like so they got to they [82:58] got to make sure but like how can you [82:59] function and do anything without their [83:01] infrastructure so like just think of it [83:02] as a sector like stop telling me it's [83:04] 4.8 8 trillion. It's bigger than the [83:05] energy, healthcare, and utility. That [83:06] doesn't matter. What matters is it's a [83:08] sector that's massively fast growing to [83:10] the technology that matters. [83:10] >> The bare case on Nvidia was all these [83:13] deals are circular blah blah blah. No [83:16] one's saying that anymore. The bare case [83:18] is now [83:18] >> about how about all the big all the big [83:20] comp the bare case was I think one of [83:22] the bear cases that I don't like is like [83:23] oh all the capex come from hyperscalers [83:25] and it's it's like six companies. It's [83:27] like no it's not AWS like Amazon isn't [83:29] one company thousands of companies. So [83:32] it's it's not the right [83:33] >> rare cases that uh TPUs from Google and [83:37] other comput [83:39] it doesn't matter it's like it's okay [83:41] it's great like you know look you those [83:44] of us who have followed in you know [83:46] Jensen for 25 years would say like sure [83:48] there's a lot of like [ __ ] that he [83:50] spewed in the 25 years like I'm not [83:51] saying you know um but [83:56] >> like I I think there's really some just [83:58] the installed base of folks who are on [84:00] this platform and the investments they [84:01] it up and downstream. So like yeah, I I [84:03] don't see how you could be bullish on [84:04] the S&P 500 in a 3 to 5 year view and [84:07] not be bullish. [84:07] >> I was going to say if you think Nvidia [84:08] is 10 trillion, then surely you think [84:10] S&P is going to 10,000. [84:11] >> Yeah, they're both both uh I wrote the [84:14] S&P was going into 10,000 years ago. [84:16] It's [84:16] >> I wrote I wrote three years ago 2030 [84:18] 10,000 S&P and I [laughter] think it's [84:21] not conservative. It's not even like [84:22] weird math. It might be conservative. I [84:24] mean where where we you're talking 30 [84:26] 35% in four years. That's like far away [84:28] long-term returns at, [84:30] >> right? All right. Headlining number. [84:32] >> Guys, did we have fun on the show today [84:33] or what? [84:33] >> We did. Hey, I I heard at the beginning [84:36] of the show with Tom Lee, you were [84:39] making a little fun of me with my [84:40] accent. I'm wondering where he doesn't [84:44] do it. [laughter] Do it. Do it. [84:45] >> Come on. [84:46] >> I heard beginning of the show with Tom [84:49] Lee. You were making a little bit of fun [84:51] of me. [84:51] >> Did you get my By the way, did you [84:54] by the way? Why do you talk like you're [84:56] fogghorn leg horn if you're [laughter] [84:59] >> I don't even understand what [85:00] >> you know we have to see here [85:03] >> that's got to be the title of the uh you [85:05] guys [laughter] are always looking for a [85:06] title I think fog horn I think you just [85:08] got it [85:09] what happened is I got very confused [85:11] allowed to do it [85:12] >> I I got very confused I grew up 26 years [85:15] in Pittsburgh and then I moved to [85:16] Connecticut and they didn't mesh well so [85:19] I was a yinszer that kind of I [85:22] [laughter] kind of deinsed my I [85:26] Josh, I win our side bet on the number [85:27] of times he was going to mention Tom Lee [85:29] on this call. I had I had [laughter] I [85:31] had nine and he and he and he so I get a [85:33] little I get a little vague. [85:34] >> Can I say one thing to you? This is a [85:36] true story. I never and I never told [85:38] you. [85:40] >> You and I have had some of the all-time [85:42] great brawls on halftime report. All in [85:45] good nature. [laughter] But you and I [85:47] didn't know that. [85:49] >> I know that. I cuz I keep track. I write [85:51] them down each day. We've never had you [85:52] and I have never had one. [85:54] >> No. No. You You and I are golden. No, [85:55] but Rob and I are good, too. [85:57] >> Robick is Is what you're saying? Is this [85:58] coming out now? Is there laden? [85:59] >> Sometimes [laughter] Listen, we're Is [86:01] this where I get body? [86:03] >> No. No. You've been on the show for a [86:04] long time since we were in Anglewood [86:06] Cliffs. [86:06] >> Yeah. 13 years. There was one time where [86:11] you were saying something and I wasn't [86:13] even on the show, [laughter] [86:16] but I I was like tweeting at the judge [86:20] and the judge [86:22] texts me goes, "Why don't you come on [86:24] and you and Rob could have you and Rob [86:27] could have this?" I don't know if you [86:28] remember this. I was, people won't [86:30] believe me what I'm saying. I was [86:31] literally in the gym at a hotel. [86:33] [laughter] [86:34] I must have been in like Arizona or [86:35] something cuz I remember looking [86:36] outside. It was a sunny day. 12:00 in [86:38] the afternoon. I swear I was working [86:40] out. I swear to God. I go live on the [86:44] show. Other people are in this hotel gym [86:45] looking at me [86:46] >> wearing like Lulu [86:47] >> and I'm debating you. Anyway, this is [86:48] the point of the story. [86:50] >> Somebody that I'm friends with texted me [86:52] and said, "When you and Rob go at it [86:55] over a stock, not nothing ever besides a [86:58] stock." He goes, "It reminds me of [87:00] fighting with my brother." You guys [87:03] [laughter] are like brothers. I I never [87:04] told you that story, but I I truly I [87:07] think you're a brother. I really do. I [87:09] love the debates that we have. [87:11] >> Me, too. [87:11] >> We It sounds like these days we agree on [87:13] a lot of things. I agree with almost [87:14] everything you said today. And uh thank [87:16] you so much. [87:17] >> You know what? I agree with you. I agree [87:18] with 105 billion and a lot in the [87:20] pipeline. I agree with that. [laughter] [87:22] >> I very much agree with that. Do you [87:23] agree with that? Who could deny the [87:25] success? [87:25] >> Do you agree with that? [87:26] >> I agree. I [laughter] agree with Thank [87:28] you so much. It was fun with it was [87:30] really fun being here with both this [87:32] this a great program. We're going to [87:33] come back from dinner. We're going to do [87:35] the second half of the show. [laughter] [87:36] And guys, we we we appreciate you. Uh I [87:40] want to let everybody know they should [87:41] follow Adam and check out Triari [87:44] Research and TriCector Research, which [87:46] who is that for? [87:46] >> Trifecta Research is for advisers and [87:49] individuals. It's a $1,200 year. We do a [87:51] lot of like ETF analysis insights [87:53] videos, talk about what we learn from [87:54] institutions. So, [music] I'd love love [87:56] for people to join. [87:57] >> Awesome, dude. And if you want to learn [87:58] more about New Edge, go to newedge.com. [88:01] >> www.newedgewealth.com. at new [88:02] edgewealth.com. [88:03] >> new edgewealth.com. [88:05] All right, guys. Thank you so much for [88:06] watching. Thank you for listening. [88:07] Special thanks to Adam Parker. [88:09] >> Love being here. [88:10] >> Rob Sin, [88:12] thanks [applause] to you soon. Take it [88:14] easy. [music]