Market Movers & Shakers

Last week’s holiday-shortened trading saw U.S. stocks close in the green, with the major indices logging five consecutive sessions of gains to finish out the month. Increased odds of a December interest rate cut from the Federal Reserve helped to bolster risk assets. Hawkish signals from Fed Chair Powell and the October FOMC minutes pushed the probability of a December rate cut below 30% in mid-November, but a dramatic reversal occurred after NY Fed President Williams made dovish comments on November 21st, accelerating the odds of a cut to now 87%, according to the CME FedWatch tool.

November proved to be a volatile month with U.S. equities delivering mixed results. The S&P 500 posted its seventh consecutive monthly increase, eking out a 0.13% gain despite a mid-month drawdown of nearly 5%. Market leadership broadened in November as the average stock outperformed, driven by a rotation out of particular mega-cap technology stocks and AI related names that garnered much of the momentum earlier in the year. The equal-weight S&P 500 added nearly 2%, the S&P 600 index of small-caps advanced 2.5%, and the S&P 500 Low Volatility index gained 3.6%. On the flip side, the Nasdaq underperformed, declining 1.51% and snapping its seven-month winning streak. A bulk of the Magnificent 7 stocks posted declines for the month, with notable weakness in Nvidia (-12%) and Tesla (-5.8%), while Google’s parent company, Alphabet, bucked the trend and closed higher by 13.9%. Eight of the eleven sectors in the S&P 500 logged gains in November. Healthcare was the standout performer, closing higher by 9.14% driven by strength in pharmaceutical stocks like Eli Lilly (+24%) and Merck (+22%) while the Technology sector was the biggest laggard, closing lower by 4.36%, with Oracle (-23%) and AMD (-15%) shares seeing outsized declines.



Source: FactSet

Volatility surged earlier in the month as markets sold off the week before Thanksgiving. The VIX closed above 26 for the first time since April’s tariff-related selloff that took the market down nearly 20%. Extreme near-term fear caused the VIX curve to flip into backwardation, where the front-month VIX futures trade at a higher price than longer-term futures and become the most inverted since Liberation Day. In fixed income, Treasuries were mostly firmer with the curve slightly steepening as the U.S. 2-Year Treasury Note yield fell roughly 10 basis points to 3.50% while the yield on the U.S. 10-Year Treasury Note fell 7 basis points to 4.02%. However, recent commentary from Bank of Japan Governor Kazuo Ueda suggesting the BoJ could raise interest rates again as soon as this month caused JGB yields to rise sharply, with other global sovereign bond yields following suit. Meanwhile, WTI crude oil fell 3.5%, marking its fourth consecutive monthly decline, while Gold gained over 5% for its fifth straight monthly advance. The rout continued in the crypto complex as Bitcoin briefly fell below $81,000, losing more than a third of its value since its early October highs.



Source: FactSet

The AI trade became increasingly scrutinized throughout November as a growing number of market participants began to question the sustainability of recently announced spend commitments. OpenAI found itself at the center of these concerns given the disparity between the company’s reported $1.4 trillion in spend commitments and its estimated $13 billion in annual revenue. In response to a direct question about that gap, OpenAI CEO, Sam Altman, forcefully pushed back, stating that the company was on track to do “well more” than $13 billion in revenue and told investor Brad Gerstner “if you want to sell your shares, I’ll find you a buyer. Enough.” The exchange was widely viewed in a negative light as a testy and defensive moment and raised alarm bells regarding OpenAI’s ability to meet its longer-term commitments. These concerns were further exacerbated by comments from OpenAI’s CFO regarding potential “government backstops”, suggesting that private capital might not be sufficient to sustain current burn rates. Vendor financing and revenue circularity, where tech giants (like Nvidia) invest in smaller companies that immediately route that capital back to the investor in the form of compute or cloud spend, also started to receive coverage and criticism in mainstream financial media.

Last month also saw the release of Google’s Gemini 3 AI model, which on certain benchmarks and tests performed better than OpenAI’s ChatGPT 5 model. Gemini 3 received high praise from industry experts, particularly given the fact that the model was trained on Google’s proprietary TPUs (Tensor Processing Units) rather than Nvidia’s GPUs. Analysts referred to the launch as a “DeepSeek Moment”, marking a significant shift in model efficiency. This development hints that Google’s proprietary TPUs could emerge as a strong competitor to Nvidia’s GPUs, and along with rising Chinese competition, suggests the current AI hardware monopoly may be beginning to fracture. Investor sentiment around Nvidia soured, highlighted by Softbank’s decision to liquidate its entire $5.8 billion stake. The loss of investor confidence was also mirrored in the price action of Nvidia’s stock following its quarterly earnings release, which saw a dramatic 800 basis point intraday reversal despite delivering robust results and upbeat forward guidance.



Source: FactSet

Concerns are mounting about existing AI capital expenditure plans that are increasingly eating up more and more of the cash flow of the large hyperscalers, prompting them to turn to debt markets to fuel the surge in spending. For example, Oracle’s free cash flow went negative for the first time in 25+ years last quarter and is now deeply in negative territory as the company projects $35 billion in AI capex in fiscal year 2026. Given the scale of Oracle’s AI bet, its credit default swaps (essentially protection against debt default) are now attracting significant attention from market participants. Meta and Google have also recently tapped debt markets to fund the frenzied AI buildout spend.



Source: FactSet

The dramatic shift in capital allocation plans across the major tech firms has unsettled investors for a number of reasons. These companies, historically asset-light, cash flow machines, are now shifting toward becoming asset-heavy burners of cash. This fundamentally alters the narrative, as the core shareholder return thesis, built on reliable free cash flow funding aggressive share buybacks, is now threatened. The high level of spending creates significant uncertainty around the return on investment for the AI buildout, largely because the useful life of expensive GPUs is very short before they degrade, or newer models render them obsolete. Despite the rapidly shortening chip cycle, hyperscalers have modified their depreciation schedules and accounting practices to extend the useful life of GPU assets on their balance sheets. This raises questions from investors about whether they might be understating depreciation. With all of this in mind, investors are beginning to question valuations based on historical, asset-light metrics, when capital is now being increasingly tied up in highly specialized, rapidly depreciating hardware, effectively transforming low-risk growth stories into high-stakes, high-capex gambles.

Updates & News*

In portfolio news, Accenture and OpenAI announced a new partnership in a deal that brings ChatGPT Enterprise to tens of thousands of Accenture employees. Accenture’s CEO, Julie Sweet, said the deal with OpenAI will “accelerate enterprise reinvention and business outcomes for [Accenture’s] clients.” Sticking with the AI theme, Nvidia announced it has purchased $2 billion of Synopsys’ common stock as part of a strategic partnership to accelerate computing and AI engineering solutions. Per CNBC reporting, as part of the multiyear partnership, Nvidia will help Synopsys accelerate its portfolio of compute-intensive applications, advance agentic AI engineering, expand cloud access and develop joint go-to-market initiatives. Synopsys, which provides design software for firms like Nvidia to develop complex semiconductor chips, said that its partnership with Nvidia will help it take workloads that used to run for weeks and reduce them to hours.

Elsewhere, two of Tandem’s holdings in the healthcare sector announced notable acquisitions in November. Abbott Labs agreed to acquire Exact Sciences in a deal valued at nearly $21 billion. Exact Sciences is a molecular diagnostics company best known for its Cologuard screening product, specializing in cancer detection and precision oncology to guide personalized treatment. The transaction gives Abbott exposure to the fast-growing cancer screening market, and per Abbott CEO Robert Ford, “[Abbott’s] vision here is really to build the premier cancer diagnostics company in the world.” Also making a splash in the oncology space, Johnson & Johnson announced the acquisition of Halda Therapeutics for $3.05 billion. Halda’s proprietary drug platform develops therapies for solid tumors, with a drug in clinical trials to treat prostate cancer, along with earlier therapy candidates for breast and lung cancer. The acquisition further strengthens Johnson & Johnson’s oncology pipeline.

Source: Source of all data is FactSet, unless otherwise noted.

*The transition level activity taken by Tandem is applicable to new manager-traded accounts and new money in manager-traded accounts, not the composite or firm-wide level. New manager-traded accounts and new money in manager-traded accounts are not automatically invested on the first day. Rather, they are transitioned into our strategy over a longer time period that is dependent upon market conditions, this process differs from Tandem’s model-provided strategies, where money is invested on the day the account opens. Strategy level activity is applicable to the composite and action is taken at the firm-wide level.

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