McKay Capital Markets

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  • Earnings, Energy, and AI

    If you are not terribly familiar with why earnings reports are important, and able to move markets the next few paragraphs will lay that out—if you are familiar feel free to skip down.

    We are moving into the thick of earnings season. Quarterly reporting acts as the market’s essential reality check, bridging the gap between speculative expectations and actual financial performance.

    By providing a transparent window into a company’s cash flow, margins, and debt every 90 days, these reports allow investors to continuously recalibrate their valuation models. This regular flow of data reduces “information asymmetry”—ensuring the public knows as much as the insiders—and forces a periodic validation of management’s long-term strategy.

    Ultimately, these reports serve as an anchor, ensuring that stock prices remain tied to fundamental economic value rather than just sentiment.

    Investors often rely on analysts, who set expectations for company performance. The base that these expectations are built off “Management Guidance” which is a company’s official forecast of future financial performance (i.e. revenue, earnings, margins).

    Three of the best words to hear during earnings are “beat and raise” where the companies prior quarter outperformed, or beat, the street (analyst) expectations, and management raises their guidance, in releasing updated forecasts for better future performance.

    If earnings are missed, you may want to dig deeper into any discrepancies in performance quarter over quarter, evaluate the broader sector or market to see what could have driven the change, and whether it is a short-term condition, or a shifting trend that will cause headwinds moving forward.

    Metrics for valuation multiples will vary sector to sector but largely earnings per share (EPS) and revenue will broadly be the indicators that you read or hear when earnings are being reported.

    THIS WEEK:

    This week’s portion of the earnings cycle has been a study in the market’s prioritization of guidance over performance, as investors grapple with shifting trade policies and “Greenland-related” macro volatility.

    Intel (INTC) and Netflix (NFLX) both delivered bottom-line beats for Q4, yet saw their stocks tumble 15.1% and 7.0% respectively after issuing cautious Q1 2026 outlooks.

    This “guidance-first” sentiment similarly penalized 3M (MMM) and GE Aerospace (GE), which slid 8.3% and 5.4% on the week despite solid earnings beats, as the market reacted poorly to 3M’s conservative profit forecast and GE’s tepid 1% revenue growth projection. Abbott Laboratories (ABT) faced the steepest fundamental rejection, dropping 10.8% after a revenue miss in its diagnostics segment overshadowed its EPS achievement. Conversely, Prologis (PLD) emerged as the week’s rare outlier, gaining 2.9% as management’s robust 2026 Core FFO guidance provided the long-term “anchor” that sentiment-driven peers lacked.

    A LOOK AHEAD:

    Over the next two weeks six of the Mag7 firms will report their latest earnings, with Nvidia reporting at the end of February. As such the below will act as something of a scouting report on each of the Mag7 firms. Additionally, a rundown on Taiwan Semi-Conductor or TSMC, a major upstream partner in the AI space, who reported phenomenal earnings with a Beat and Raise quarter. This should not be interpreted as a research report but a 30,000 foot view of firm offerings, competitive advantages, and threats to market share.

    The Platforms & Ecosystems

    Microsoft (MSFT)

    • AI Function: Leading the Agentic AI shift through Copilot and their partnership with OpenAI. They are automating the white-collar workflow, transforming Azure from a storage cloud into an AI-first intelligence engine.
    • Moat: Massive enterprise distribution. Every Fortune 500 company is already a customer, making their AI upsell a natural evolution.
    • Threats: High CapEx spending on data centers may weigh on margins if AI productivity gains don’t materialize as quickly as projected.

    Tesla (TSLA)

    • AI & Robotics: A Robotics and AI company disguised as a carmaker. Their Optimus humanoid robot and FSD (Full Self-Driving) are the core of their $1.3T+ valuation.
    • Integration: Heavily vertically integrated, now designing their own AI chips (AI5/AI6) to reduce dependence on NVIDIA.
    • Threats: Declining automotive margins (down to 16%) and the high “Musk Premium” which ties the stock price closely to the CEO’s public narrative. Regulatory hurdles in the robotaxi space have given Waymo (GOOGL) an early, albeit limited, battle for market share.  

    Meta (META)

    • AI Function: Utilizing AI for hyper-personalized ad targeting and “Smart Glasses” (Ray-Ban Meta) that act as an AR/AI interface.
    • Integration: Meta is spending an estimated $91B in 2026 CapEx to build an independent AI compute stack to bypass reliance on external mobile OS platforms.
    • Threats: Regulatory pressure in the EU, a slowdown in spending by major Chinese retailers TEMU and Shein, which have historically driven significant ad volume could hit growth, additionally with significant CapEx, margin compression is a risk if spend and revenue grow asymmetrically.

    Apple (AAPL)

    • AI Function: Edge AI. Apple is focusing on Apple Intelligence and an overhauled Siri (codenamed “Campos”) that runs on-device to protect privacy.
    • Moat: An install base of 2.35B users. This gives them a “last mile” advantage—they own the interface the consumer actually uses.
    • Threats: Slow innovation perception compared to AI-first peers and heavy reliance on iPhone sales in a softening China market.

    Alphabet (GOOGL)

    • AI Function: Deeply vertically integrated with their own TPU (Tensor Processing Units) and the Gemini model. They are a leader in autonomous vehicles via Waymo, which is now seeing expanded deployment in U.S. cities.
    • Threats: Facing stiff AI competition and regulatory scrutiny that may impact its long-term competitive edge. Battling Tesla for robotaxi market share. Waymo leads in deployment at the moment but has significantly higher cost per vehicle in production.
    • Moat: Data dominance. Google Search and YouTube provide the largest training sets on earth for multimodal AI.

    Amazon (AMZN)

    • AI & Robotics: The gold standard for Warehouse Automation. Their fleet of mobile robots and AI-driven forecasting (SCOT) has fundamentally changed the economics of logistics.
    • Moat: Flywheel Effect. AWS provides the AI infrastructure (Bedrock) to others, while Amazon uses that same tech to lower its own delivery costs.
    • Threats: Antitrust scrutiny and rising labor costs that force even faster (and more expensive) automation pivots.

    The AI Infrastructure & Foundational Layer

    NVIDIA (NVDA)

    • AI & Automation: The undisputed king of the AI era, providing the “Compute” bedrock via GPUs and the CUDA software stack. They are moving rapidly into Physical AI and robotics through their Omniverse and Isaac platforms, which allow for the simulation and deployment of autonomous machines.
    • Integration & Moat: Highly vertically integrated in the software-hardware stack. Their “Blackwell” and upcoming “Rubin” architectures create a cycle where software lock-in makes switching costs prohibitive for cloud providers.
    • Threats: Increasing custom chip development from their own customers (AMZN, GOOGL) and potential regulatory caps on advanced chip exports.

    TSMC (TSM)

    • Competitive Position: The world’s forge. They hold a near-monopoly on the advanced nodes (3nm, 2nm) required for every major AI chipmaker.
    • Recent Outperformance: TSMC recently delivered a monster Q4 2025 report on Jan 15, 2026, with $33.7B in revenue (beating guidance) and a massive gross margin of 62%.
    • Key Advantage: Unmatched scale and Process Leadership. They are the ultimate “picks and shovels” play—when NVDA or AAPL wins, TSM wins by default.
    • Threats: Geopolitical concentration in Taiwan and the extreme capital intensity required to build new fabs ($52B–$56B planned for 2026).

    THE ENERGY ISSUE

    As the Artificial Intelligence market continues to mature, the most critical bottleneck to monitor isn’t the availability of high-performance GPUs, but rather the availability of power. AI workloads—particularly the massive training clusters for LLMs—require energy profiles that are far more volatile and intense than traditional IT. We are seeing a structural shift where a single high-density AI data center can demand upwards of 100 MW to 300 MW, roughly equivalent to powering a small city.

    This power crunch is creating a significant temporal mismatch between the tech and utility sectors. While a state-of-the-art AI facility can be planned and built in under two years, the high-voltage transmission lines needed to feed it often take 15 to 30 years to permit and construct. In the U.S. alone, nearly 2 TW of clean energy is currently trapped in interconnection queues. Without coordinated reform, this energy deficit risks deflating the AI valuation bubble as computing supply remains physically constrained by a grid that was never designed for this level of sustained, high-density industrial load.

    Short-to-Medium Term Solutions (1–3 Years)

    In the immediate term, hyperscalers like Microsoft, Amazon, and Google are pivoting toward behind-the-meter (BtM) and bridging strategies to bypass grid delays.

    • On-Site Generation: Tech firms are deploying dedicated natural gas plants and fuel cells directly at data center sites to ensure 24/7 reliability while waiting for grid hookups.
    • Operational Efficiency: The rapid adoption of liquid cooling is no longer optional; it is a necessity for racks exceeding 30–40 kW to maintain hardware longevity and reduce thermal energy waste.
    • Grid Modernization: Deployment of advanced software tools could unlock up to 175 GW of existing transmission capacity without building new lines, providing a critical buffer for the 2026–2028 timeframe.

    Long-Term Strategic Solutions (5–10 Years)

    To sustain growth through 2035, the industry is betting on a fundamental restructuring of energy generation and storage.

    • Small Modular Reactors (SMRs): Because AI clusters require continuous, “firm” baseload power, companies are aggressively exploring factory-built SMRs. These 5 MW to 300 MW reactors can be installed directly on AI campuses, scaling in modular increments as compute demand increases.
    • Next-Gen Geothermal: Leveraging technology from the shale revolution, next-generation geothermal could supply up to 40 GW of clean, 24/7 power by 2035, offering a carbon-free alternative to traditional baseload sources.
    • Innovative Energy Storage: The development of structural battery composites—materials that function as both load-bearing building components and energy storage—may revolutionize how data center infrastructure manages power density over the next decade.

    WRAPPING UP:

    A few things to keep in mind—earnings are important, and informative, but in my opinion, they are a datapoint amongst a set that should be weighed in all investment decision making processes. If you are investing for the long-term look at them as a progress report, not the whole story. If you have any interest in the power solutions listed above we will likely go into a deeper dive on what those would look like in the coming months, there are also a wealth of videos by energy experts explaining in basic terms that make complex solutions very digestible, I highly recommend exploring the topic as it has the potential to be a major market factor over the medium to long term. Finally, AI will be a common theme here, as it is a cornerstone of the current market environment, I encourage anyone who has not to experiment with Chat-GPT, Google Gemini, Anthropic’s Claude, and any other number of LLM platforms, the more comfortable you are utilizing the technology moving forward the more valuable you will be if, and more likely when, it is adopted in your profession in some form, or fashion.

    DISCLOSURE:

    This material is provided for informational and educational purposes only and does not constitute investment advice, a recommendation, or an offer or solicitation to buy or sell any security or investment strategy. The views expressed are those of the author as of the date of publication and are subject to change without notice.

    The author is a financial professional and may hold positions in, or manage client accounts that hold positions in, the securities discussed. Such holdings are subject to change at any time without notice. While the author strives to present information in a fair and balanced manner, no representation is made that this commentary is free from bias, and readers should be aware of potential conflicts of interest.

    The information presented is derived from publicly available sources believed to be reliable, but accuracy and completeness are not guaranteed. Past performance is not indicative of future results. All investing involves risk, including the possible loss of principal.

    This commentary does not take into account the investment objectives, financial situation, or particular needs of any specific person. No advisor-client relationship is created by the receipt or review of this material. Readers should consult with a qualified financial, legal, or tax professional before making any investment decisions.

    The views expressed do not take into account the specific financial situation, risk tolerance, or investment objectives of any individual reader. Reading this material does not create an advisor-client relationship. Investors should conduct their own research or consult with a qualified financial professional before making investment decisions.

    -John McKay, CFA

  • 2025 Market Wrap Newsletter:

    The following piece is market commentary and based on the opinions and research of the writer. The information below is for educational and informational purposes only and should not be considered personalized investment advice or a solicitation to buy or sell any securities. While the author is a financial professional, the views expressed here are personal opinions and do not reflect the unique financial situation, risk tolerance, or investment objectives of any specific individual. Reading this blog does not create an advisor-client relationship.

    With 2026 underway, a look back at the previous year reveals a landscape that was far more resilient—and volatile—than many predicted. 2025 was defined by a shift from inflation anxiety to policy adaptation, as markets navigated a new regime of tariffs, deregulation, and the continued maturing of the AI boom.

    Macroeconomic Pillars of 2025

    The year’s macro story was a tug-of-war between restrictive trade policies and supportive monetary shifts. 

    • The Policy Pivot: After a rocky start influenced by the “Liberation Day” tariff announcements the market powered forward through the summer. Following a record-breaking 43 day government shutdown, and a modest fourth quarter GDP Growth projections land around 1.9% for the year.
    • The Fed Cuts: The Federal Reserve executed a series of three 25-basis-point cuts in the second half of the year, bringing the target range to 3.50%–3.75%. Crucially, the Fed ended Quantitative Tightening (QT) on December 1, signaling a return to a more “neutral” liquidity environment.
    • The AI Capex Engine: Artificial Intelligence moved from a speculative theme to a fundamental driver of corporate earnings. Research indicates that roughly 60% of 2025’s GDP growth was linked to the AI buildout, particularly in data center expansion and industrial power infrastructure.

    2025 Market Performance 

    In 2025, the U.S. equity market recorded its third consecutive year of double-digit gains, characterized by a transition from speculative AI hype to fundamental earnings-driven growth. Despite significant early-year volatility—including a “near-bear market” in April triggered by reciprocal tariff announcements—major indices staged a powerful recovery to finish near record highs.

    Major Index Performance

    The market remained resilient, with all three major indices finishing in positive territory for the year:

    • Nasdaq Composite: Led the indices with a 20.2% return, fueled by the persistent strength of technology and communication services.
    • S&P 500: Gained 17.9%, marking the third straight year of double-digit returns (following 26.3% in 2023 and 25.0% in 2024).
    • DJIA: Followed with a 13.0% gain, supported by a late-year rotation into diversified market giants as tech momentum cooled slightly in the fourth quarter.

    S&P 500 Sector Returns

    For the third year in a row, growth-oriented sectors dominated the market, though early signs of a rotation into industrials and financials emerged:

    • Information Technology (+24.0%): The top performer in 2025—Continued its winning streak as the backbone of the global AI infrastructure buildout.
    • Communication Services (+23.1%): Following information Technology Comm outperformed in 2025 driven by the massive monetization of AI-powered advertising and search tools.
    • Industrials (+19.4%): Outperformed the broader index due to its critical role in power production and data center construction for AI hyperscalers.
    • Laggards: All 11 sectors ended the year in the green, though Real Estate (+3.2%) and Consumer Staples (+1.6%) were the weakest performers.

    Magnificent 7 Commentary

    A notable divergence occurred within the “Magnificent 7” group in 2025. While the group contributed 42% of the S&P 500’s total return, only two members—Alphabet and NVIDIA—outperformed the broader index.

    • Alphabet (GOOGL) (+65.9%): The standout winner of 2025, completing a “redemption arc” by proving AI could enhance rather than disrupt its core search and advertising margins. Gemini 3 was released late in 2025 driven by Googles TPU processors, creating a massive upswing late in the year.
    • NVIDIA (NVDA) (+34.9%): Remained the primary “pick-and-shovel” play, becoming the first company to surpass a $5 trillion market capitalization during the year. Nvidia continues to grow at an incredible pace. There has been negative sentiment about Nvidia’s valuation in recent months, for what its worth, Nvidia still trades at a lower P/E than Costco. 
    • Underperformers: Amazon (+4.8%), Apple (+12.0%), and Meta (+10.5%) all underperformed the S&P 500 as investors became more selective about immediate AI profitability.

    Expectations:

    I am very optimistic in 2026, early structural headwinds from Institutional rebalancing, a new Federal Reserve regime, and uncertainty with the legality of the administrations tariff policy will likely cause volatility during the first two quarters of 2026. Ultimately I think we will see continued growth in the AI space as ROI becomes more apparent. If we see the Fed cut rates, Financials are well positioned to outperform, as M&A activity should pick up along side an attractive slate of potential IPOs before year end.

    With that being said, AI is the theme that drove the market for much of 2025.

    In basic terms, AI is the application of computers to complete tasks that would normally need human thinking to complete. This is done by consuming, immense amounts of data and information, recognizing patterns to solve problems or prompts. It is difficult to find a sector that will not be impacted by AI adoption.

    · The Death of “Drudge Work” (Professional Services): AI has evolved from a summarization tool into an active agent. In legal and corporate sectors, AI can now analyze a 100-page lease, identify conflicting clauses, negotiate terms via email, and update billing systems autonomously. This allows professionals to focus on high-level strategy, leading to documented productivity gains of over 20% in firms like JPMorgan.

    · The Documentation Revolution (Healthcare): AI is directly tackling physician burnout by using ambient listening to automatically generate clinical notes and billing codes during patient visits. By saving doctors an average of 15 hours per week on paperwork, hospitals are increasing revenue through higher patient throughput while reducing wait times.

    · Compute-Powered Discovery (Science & Energy): AI “design engines” are revolutionizing R&D by simulating millions of virtual experiments. In drug discovery, this is compressing the timeline for cancer treatments from 10 years down to three. This massive need for “compute” is also fast-tracking clean energy, as tech giants invest billions into nuclear and renewable projects to power the next generation of data centers.

    We will be staying on top of use-cases and ROI metrics as adoption becomes more widespread.

    While the technology is truly incredible, it is not without setbacks. Energy is a key constraint on the continued growth of AI. The data centers that are the backbone of the industry, consume immense amounts of energy. This drives up the cost of electricity for the population, which has created some public backlash and ultimately pushback from local governments on new datacenter development. Additionally as growth continues there is a supply issue, both creating enough energy, and transmitting on the current grid. This issue has not gone unnoticed and should lead to updated infrastructure and much needed overhaul of domestic energy policy. I will touch more on that in my next post which will include a comprehensive breakdown of the firms that are driving AI forward.

    Portfolio Management Concepts: Dollar-Cost Averaging

    Dollar-cost averaging (DCA) is a disciplined investment strategy where you systematically invest fixed amounts of money at regular intervals, regardless of market conditions. Rather than attempting to “time the market” with a single lump-sum investment—which carries the risk of investing right before a downturn—DCA spreads your entry over time to reduce portfolio volatility and lower your average cost per share if prices fall. Most people already utilize this strategy through automated 401(k) contributions, which allow for “set it and forget it” wealth building that removes the emotional stress of daily market fluctuations.

    The primary benefit of this approach is risk reduction; while you may give up some immediate upside during a market surge, you protect yourself against the “poor timing” of a sudden crash. By “legging into” the market incrementally, you ensure that at least a portion of your capital is deployed at lower prices during market dips. This strategy is equally effective when withdrawing funds during retirement, as it prevents you from selling off too much of your portfolio during a temporary market low.

    Wrapping up:

    If you found this interesting or helpful, please forward on to friends and family. I will use this site to provide continued market commentary, touch on additional portfolio management and personal finance items, and provide in-depth analysis on major economic themes. Any feedback is appreciated. 

    -John McKay, CFA