Five Undervalued Stocks After Earnings: Morningstar 2026 Analysis

Strong earnings do not automatically create an attractive stock. A company can report record revenue, beat Wall Street’s expectations and raise guidance, yet still offer little margin of safety if the share price already assumes years of near-perfect execution. The reverse is also true: a stock can fall after a solid quarter because investors are worried about capital spending, temporary margin pressure or a difficult comparison, even though the underlying business remains durable.

That tension is the useful way to examine five companies highlighted by Morningstar after the latest earnings season: Microsoft, Alphabet, S&P Global, Charles Schwab and Northrop Grumman. They operate in very different industries, but the investment argument around each one rests on the same basic question. Is the market price discounting too much risk relative to the cash the business can plausibly generate over time?

The answer is not obvious. Microsoft and Alphabet are committing extraordinary amounts of capital to artificial-intelligence infrastructure. S&P Global is adapting its data and ratings franchises to a world in which generative AI may change how customers search for information. Schwab is benefiting from asset growth and trading activity while remaining exposed to interest rates and client cash behavior. Northrop Grumman has a record backlog and exposure to long-duration defense programs, but those programs carry cost, schedule and contract-accounting risks that can quickly pressure margins.

At approximately 11:40 a.m. Eastern time on August 3, 2026, all five stocks traded below the long-term fair-value estimates discussed or published by Morningstar. The apparent discounts ranged from roughly 13% to 19%. Those figures are useful starting points, not conclusions. A fair-value estimate is an analyst’s discounted-cash-flow judgment, not an observable fact, and a modest change in revenue growth, margins, capital intensity or the discount rate can materially alter the result.

Market-price data in this article were checked on August 3, 2026, at approximately 11:40 a.m. Eastern time. Intraday prices can change rapidly and may be delayed.

Key Takeaways

• Microsoft: Fiscal fourth-quarter revenue reached $90.0 billion and Azure grew 43%, but the valuation case depends on AI infrastructure producing durable growth without permanently depressing returns on capital.
• Alphabet: Google Cloud revenue rose 82% in the second quarter and operating profit expanded sharply, while unusually large investment gains distorted reported net income and heavy capital spending pushed quarterly free cash flow below zero.
• S&P Global: Revenue and earnings grew after adjusting for the Mobility Global spin-off, and the company’s ratings, indices and proprietary datasets retain strong competitive advantages. The central debate is whether AI weakens those advantages or makes the company’s data more valuable.
• Charles Schwab: Record quarterly revenue, $13.08 trillion of client assets and strong asset gathering support the scale story, but interest-rate sensitivity, client cash sorting and market-dependent activity remain material risks.
• Northrop Grumman: A $104.7 billion backlog and raised guidance provide unusual visibility, while cost adjustments on missile and space programs show why backlog is not the same thing as guaranteed profit.
• Valuation: Morningstar’s estimates imply that the five stocks were moderately undervalued on August 3, but the discounts are not large enough to eliminate company-specific execution risk or broader market risk.

Why “Undervalued After Earnings” Is a More Difficult Claim Than It Sounds

Earnings releases create an illusion of precision. Revenue is reported to the nearest million dollars, earnings per share to the nearest cent and growth to a tenth of a percentage point. The market reacts within seconds. That precision can obscure the larger uncertainty: a stock’s value reflects years of future cash flows, while a quarterly report covers only three months and often contains accounting items that say little about the long-term economics of the business.

The phrase “undervalued after earnings” therefore requires two separate judgments. The first concerns business quality. Does the company possess durable advantages that allow it to earn attractive returns, defend pricing, retain customers and reinvest at sensible rates? The second concerns price. How much of that quality is already embedded in the stock, and how sensitive is the valuation to assumptions that may prove wrong?

Morningstar’s framework explicitly separates those ideas. Its economic-moat assessment concerns the durability of competitive advantages, while its fair-value estimate attempts to calculate the present value of expected future cash flows. The firm also applies an uncertainty rating because a dollar of estimated value is less dependable when outcomes vary widely. Morningstar explains that its stock rating compares market price with fair value while adjusting for uncertainty. That distinction matters here because all five companies have defensible franchises, but the range of possible outcomes is not the same.

Microsoft’s future depends partly on how quickly cloud and AI workloads expand and whether customers accept prices that support the cost of data centers, chips and electricity. Alphabet’s future includes similar infrastructure questions plus the more disruptive issue of whether generative AI changes search behavior. S&P Global relies on trusted data, embedded workflows and regulatory recognition, yet AI could lower the cost of producing basic analysis. Schwab’s earnings respond to rates, securities-market levels and client cash allocations. Northrop Grumman’s programs can run for decades, but a single unfavorable cost estimate on a fixed-price development contract can erase profits that took years to build.

A 15% discount is not the same across those businesses. If Microsoft’s normalized free cash flow compounds at a high-teens rate for years, a 15% discount may be meaningful. If AI infrastructure turns out to be more competitive and less profitable than expected, the same apparent discount may disappear. If Northrop’s backlog converts into production revenue at improving margins, its discount may look conservative. If cost overruns persist, the backlog may offer less economic protection than the headline number suggests.

This is why the five names are better treated as case studies in valuation than as a simple shopping list. Each one illustrates a different way that a high-quality company can become mispriced—and a different way that an apparently attractive valuation can disappoint.

The Rate Backdrop: The Federal Reserve Is No Longer a Passive Detail

The latest Federal Reserve decision matters to all five companies because the discount rate used to value future cash flows is tied, directly or indirectly, to interest rates. At its July 28–29 meeting, the Federal Open Market Committee kept the federal-funds target range at 3.50% to 3.75%. The vote was 9–3, with three members preferring a quarter-percentage-point increase. The official FOMC statement described economic activity as expanding at a solid pace while inflation remained elevated.

The unusually divided vote and Chair Kevin Warsh’s limited guidance left investors with more uncertainty than a conventional “hold” decision might imply. Reuters reported that bond-market moves after the announcement included a steeper Treasury curve and a rise in longer-term yields, reflecting concern about inflation, fiscal conditions and the Fed’s willingness to respond. Market-implied expectations subsequently leaned toward at least one rate increase, although those probabilities can change quickly with incoming data.

Higher long-term yields can weigh on the present value of distant cash flows, which is especially relevant for technology companies whose valuations depend heavily on profits expected years from now. They can also raise financing costs for corporations and consumers, affect market activity, alter the profitability of financial institutions and influence federal budgeting. The effect is not uniform.

For Microsoft and Alphabet, a higher discount rate tends to reduce the value investors assign to long-duration growth. Those companies have strong balance sheets and are not dependent on external financing to survive, but the market still compares their expected return with the return available on government bonds and other assets. A higher risk-free rate means growth must be stronger or more certain to justify the same multiple.

For Schwab, interest rates affect both sides of the business. Higher rates can support yields on interest-earning assets and net interest revenue, but they can also encourage clients to move idle cash into higher-yielding money-market funds or outside products. That process, often called cash sorting, can reduce the amount of low-cost bank deposits available to fund the balance sheet. The direction of the benefit depends on the level and shape of rates, the mix of client cash and the company’s asset-liability management.

For S&P Global, rates affect debt issuance, structured finance, refinancing activity and the valuation of financial assets. A higher-rate environment can suppress issuance in some periods, although refinancing needs and market volatility can also generate demand for ratings, data and benchmarks. The company’s diversification across ratings, market intelligence, indices, commodities and mobility data has historically reduced—but not eliminated—cyclicality.

Northrop Grumman’s exposure is more indirect. Government borrowing costs affect the fiscal backdrop, yet national-security budgets are driven by geopolitical priorities, congressional decisions and long procurement cycles rather than by one quarter’s Treasury yield. Higher rates also influence pension accounting, supplier financing and the discounting of future program cash flows. The main valuation issue remains execution, but the macro environment shapes the multiple investors will pay for that execution.

The Fed’s July decision therefore reinforces a disciplined approach. Investors cannot assume that lower rates will rescue an expensive valuation, nor can they treat a rate increase as automatically negative for every company. The relevant question is how the rate path interacts with each business model.

The Broader Earnings Message: Growth Is Strong, but Capital Is Becoming More Expensive

The latest earnings season has produced unusually large contrasts. Some of the strongest revenue growth has come from cloud computing, AI infrastructure, advertising and defense programs. At the same time, many of those growth engines require more capital than the market once expected.

That change is clearest in technology. The dominant cloud platforms are no longer discussing AI as a software feature that can be added with modest incremental cost. They are building data centers, acquiring accelerators, securing electricity, developing proprietary chips and financing multi-year capacity commitments. Revenue is growing, but so are depreciation, operating expenses and the amount of cash tied up before the demand is fully monetized.

Microsoft’s fiscal 2026 results showed both sides of that equation: Azure growth accelerated, commercial commitments expanded and cloud demand remained strong, while property and equipment climbed sharply and management continued to spend heavily to relieve capacity constraints. Alphabet’s second quarter showed even more dramatic Cloud growth, but capital expenditure exceeded operating cash flow for the quarter, producing negative reported free cash flow. That does not prove the spending is wasteful. It does mean that valuation must incorporate the timing and return of that spending rather than simply extrapolating revenue.

The issue extends beyond the cloud platforms. Storage and semiconductor companies are benefiting from AI-related demand, but their pricing power can be cyclical. A shortage can produce exceptional margins; a supply response can reverse them. Energy-services companies such as Baker Hughes are pursuing data-center power opportunities, which may diversify demand but also expose them to a new set of execution and capital-allocation choices. The market’s rotation within the AI trade is partly a debate over which businesses capture durable economic rents and which ones merely experience a temporary volume surge.

Financial-data companies face a different capital question. S&P Global does not need to build hyperscale data centers, but it must invest in product development, data rights, workflow integration and AI tools while defending margins. Its value lies less in raw computing capacity than in trusted datasets, regulatory recognition, installed workflows and the cost to customers of switching. AI can increase the utility of those assets if it makes proprietary information easier to query. It can also make generic research cheaper, pressuring products that do not contain differentiated data.

Schwab’s capital is largely financial rather than physical. Its balance sheet, deposit funding, securities portfolio and bank loans determine how client assets translate into revenue. A rising market can increase asset-based fees and trading activity without a comparable rise in operating expense, creating attractive operating leverage. A reversal can work the other way. The record quarter therefore should be analyzed alongside the composition of earnings and the sensitivity to rates and market levels.

Northrop’s capital intensity is embedded in factories, engineering talent, inventories and program development. The government may ultimately fund much of the production, but contractors can still absorb costs when fixed-price assumptions prove too optimistic. Defense demand can be structurally strong while individual contracts generate disappointing returns. The company’s backlog offers revenue visibility, not an unconditional guarantee of margin.

Across all five stocks, the central question is no longer whether demand exists. It clearly does. The question is what it costs to serve that demand and how much of the economic value accrues to shareholders after capital spending, depreciation, compensation, taxes and financing.

Microsoft: Exceptional Demand Meets an Exceptional Capital Program

The quarter was stronger than a simple headline can capture

Microsoft’s fiscal fourth quarter, ended June 30, 2026, delivered $90.0 billion of revenue, an increase of 18% from the previous year. Operating income rose 18% to $40.6 billion. GAAP net income increased 31% to $35.8 billion, and diluted GAAP earnings per share rose 32% to $4.81. The company’s official earnings release also reported $59.3 billion of Microsoft Cloud revenue, up 27%, and Azure growth of 43%.

Those numbers matter because Azure is the most important bridge between Microsoft’s established software franchises and its AI ambitions. The company already possesses distribution through Office, Windows, Dynamics, GitHub, security products and a vast enterprise sales organization. Azure provides the infrastructure layer, while Copilot and other applications provide potential monetization at the software layer. The strategic promise is that Microsoft can earn revenue at several points in the stack rather than depending on one model or one product.

The quarter also demonstrated the power of contracted demand. Microsoft reported commercial remaining performance obligations of $678 billion, up 84%. Remaining performance obligations are not the same as recognized revenue, and the timing can extend over years, but the figure provides evidence that customers are making large commitments. It also gives management more confidence to invest in capacity.

Segment results reinforced the breadth of the company. Productivity and Business Processes generated $37.8 billion of revenue, up 14%. Intelligent Cloud produced $39.3 billion, up 32%. More Personal Computing declined 4% to $12.9 billion, showing that not every part of the portfolio is expanding, but the slower segment now accounts for a smaller share of the company’s economic narrative.

Why the competitive advantage remains formidable

Microsoft’s moat is not simply that it sells popular software. Its products are embedded in corporate workflows, identity systems, databases, developer tools, security policies and employee habits. Replacing a single application may be possible; replacing the entire architecture is expensive, disruptive and risky. That creates switching costs.

The company also benefits from scale. It can spread research, security, compliance and infrastructure costs across a customer base that few competitors can match. Its enterprise sales force can bundle products and negotiate broad agreements. Azure gains from the same relationships that support Microsoft 365, and Copilot can be distributed to users who already work inside Microsoft applications.

Network effects are less direct than in a social network, but they exist in developer ecosystems, file formats, productivity collaboration and partner integrations. The more businesses standardize on Microsoft tools, the more valuable it becomes for consultants, software developers and employees to support those tools. This does not eliminate competition from Amazon Web Services, Google Cloud, open-source software or specialized applications. It gives Microsoft multiple defenses when a competitor attacks one product.

Morningstar’s $600 fair-value estimate reflects that durability. In its published explanation, the research firm has modeled long-term growth led by Azure, Office 365, Dynamics 365, LinkedIn and emerging AI adoption. At the August 3 intraday price of $487.68, the stock traded about 18.7% below that estimate.

The implied discount is meaningful but not enormous. Morningstar has also indicated that its $600 valuation corresponds to demanding multiples, including an adjusted price-to-earnings ratio around 39 times for fiscal 2026 in the assumptions it published before the latest quarter. A high-quality business can deserve a high multiple, but the valuation leaves less room for a sustained slowdown than a conventional “value stock” might.

The capital-spending question cannot be treated as a footnote

Microsoft’s most important risk is not that AI demand disappears overnight. It is that the cost of satisfying demand rises faster than the profit generated from it. The company’s net property and equipment reached approximately $313.1 billion at the end of fiscal 2026, up from about $205.0 billion a year earlier. That increase reflects data-center construction, servers, networking equipment and other infrastructure.

Capital spending initially appears on the cash-flow statement and balance sheet rather than immediately reducing operating income. The expense is recognized through depreciation over time. That accounting pattern can make near-term operating results look stronger than the ultimate economic burden if investors focus only on revenue and current margins. It can also understate the value of an investment that creates productive capacity for many years. The relevant measure is the return on that capital over its useful life.

There are several reasons Microsoft could earn attractive returns. Demand may remain constrained by supply, allowing high utilization. Customers may use more Azure services once they adopt AI workloads. Copilot subscriptions can monetize infrastructure through recurring software revenue. Microsoft’s proprietary models, partnerships and custom silicon may lower unit costs. The company can also allocate workloads across a global footprint and negotiate electricity and equipment purchases at scale.

There are equally credible reasons for caution. AI models may become cheaper and more interchangeable, pushing prices down. Customers may optimize usage after an initial experimentation phase. Competition among Microsoft, Amazon and Google may prevent infrastructure margins from reaching historical software levels. Accelerators can become obsolete quickly, shortening useful lives. Power and permitting constraints can delay deployment. Depreciation will rise as newly built assets enter service, potentially pressuring margins even if demand stays strong.

The latest quarter offered evidence of demand but did not settle the return question. Microsoft raised some growth expectations, yet Morningstar held its fair value at $600 because higher growth was offset by lower margin assumptions associated with Azure capital expenditure. That is a sensible analytical response: faster revenue growth does not necessarily create more value when it requires proportionally more capital.

Earnings quality was strong, but one-time items still require attention

Microsoft’s reported GAAP net income included investment and other items that should not be confused with recurring operating performance. The company disclosed a gain related to its Anthropic investment, while also recording expenses and impairments in other areas. Such items can move quarterly earnings without changing the long-term cash-generating ability of Office or Azure.

Operating income and segment trends therefore provide a cleaner view than headline net income alone. Even there, investors should distinguish between current utilization and capacity built for future growth. Strong demand can temporarily support margins when supply is constrained, while a wave of new capacity can later change the economics.

Cash flow is the final test. Microsoft’s scale and profitability provide a substantial internal funding advantage. It can finance investment without relying on dilutive equity issuance or fragile debt markets. That lowers financial risk compared with smaller AI companies. It does not make the capital free. Every dollar spent on infrastructure has an opportunity cost and must eventually earn an acceptable return.

The supporting case for Microsoft

The bullish interpretation is straightforward. Microsoft is one of the few companies with the customer relationships, capital, technical expertise and product distribution needed to turn AI from an experimental technology into an enterprise standard. Azure’s 43% growth, the expansion in contracted commitments and the continued strength of Microsoft Cloud suggest that demand is broad rather than confined to one product launch. The company can monetize infrastructure, models, developer tools, security and end-user applications.

Its traditional businesses also provide resilience. Microsoft 365, server products, Dynamics, LinkedIn and security services create recurring revenue that can fund innovation. Enterprise switching costs reduce the risk that customers abandon the ecosystem merely because a rival offers a cheaper model. If AI increases the value of productivity software and cloud computing, Microsoft may capture a larger share of customer technology budgets.

The skeptical case for Microsoft

The skeptical interpretation begins with expectations. A company valued in the trillions of dollars must create an extraordinary amount of incremental profit to deliver exceptional shareholder returns. High growth from a large base is difficult to sustain, and the market already recognizes Microsoft’s quality.

AI infrastructure may prove more capital-intensive and less differentiated than the software franchises that built Microsoft’s historical margins. If customers can switch models or clouds easily, competitive pricing may transfer much of the benefit to users. Regulatory scrutiny could constrain bundling or acquisitions. Security failures could damage trust. The company’s partnership structure and investments introduce additional accounting and strategic complexity.

The stock’s apparent discount therefore rests on a demanding but plausible combination: sustained high-teens revenue growth in major businesses, strong customer retention, successful AI monetization and margins that remain near historical levels despite a vastly larger asset base. The quarter made that combination more credible. It did not make it certain.

Alphabet: Cloud Acceleration Is Real, but So Is the Cash-Flow Burden

Google Cloud changed the shape of the quarter

Alphabet reported second-quarter 2026 revenue of $119.8 billion, up 24% year over year. Google Services revenue rose 15% to $94.5 billion. Google Search and other advertising revenue increased 17% to $63.3 billion, while YouTube advertising revenue grew 13% to $11.1 billion. The most dramatic result came from Google Cloud: revenue advanced 82% to $24.8 billion, and segment operating income rose to $8.8 billion from $2.8 billion a year earlier.

The figures in the official second-quarter earnings release demonstrate that Alphabet is no longer relying solely on search advertising to justify its AI investment. Cloud is becoming a major profit contributor, and its growth rate suggests that customers are adopting infrastructure and AI services at scale.

The operating performance was also strong at the consolidated level. Operating income rose 30% to $40.8 billion, and the operating margin expanded to 34% from 32%. That margin improvement is important because it shows that Alphabet’s current revenue growth is not being purchased entirely through operating expense. The more difficult issue appears in the cash-flow statement.

Reported net income was not a clean measure of the quarter

Alphabet reported net income of $112.2 billion and diluted earnings per share of $9.11. Those figures were dominated by a roughly $99.0 billion gain on equity securities. The company stated that the gain increased net income by about $77.1 billion after tax and added approximately $6.26 to diluted earnings per share.

That does not make the gain unreal. It does make it different from recurring profit generated by search ads, subscriptions or cloud services. Equity-security values can change sharply, and the gain says little about the operating trajectory of Google Search or Cloud. Investors evaluating the quarter should focus on operating income, segment performance and cash generation rather than annualizing headline EPS.

This distinction also illustrates why earnings comparisons can mislead. A screen that ranks stocks by reported price-to-earnings ratios may show Alphabet looking unusually inexpensive after a large investment gain. A normalized valuation removes nonrecurring gains and estimates the earnings power of the operating businesses. That process requires judgment, particularly when investment holdings are economically valuable but volatile.

Capital expenditure exceeded operating cash flow in the quarter

Alphabet generated $39.1 billion of operating cash flow in the second quarter and spent $44.9 billion on capital expenditures, producing negative free cash flow of about $5.9 billion under the common definition of operating cash flow minus capital spending. One quarter does not establish a permanent pattern, and the timing of infrastructure payments can be uneven. Still, the result is a clear warning against treating revenue growth as costless.

The company is building capacity across data centers, networking, chips and AI systems. Management has also indicated that 2026 capital spending will be exceptionally high. Morningstar’s post-earnings analysis maintained a $433 fair-value estimate while acknowledging market concern about capital expenditures expected to exceed $200 billion for the year.

At $374.00 on August 3, Alphabet traded about 13.6% below that estimate. The discount is smaller than Microsoft’s and S&P Global’s in the same snapshot. Investors are therefore being asked to accept considerable execution risk with a moderate, rather than extreme, margin of safety.

Alphabet’s AI position is broader than the search debate

The most common bear case for Alphabet is that generative AI will weaken the economics of search. Traditional search results present links and advertisements in a format that has produced exceptional margins. An AI answer can require more computing, may reduce the number of outbound clicks and can change the placement or relevance of ads. New competitors may also capture queries that once defaulted to Google.

That threat is real, but it is incomplete. Alphabet owns assets across the AI stack: custom chips, data centers, cloud infrastructure, foundation models, developer tools, consumer applications, Android, YouTube and the world’s largest search-advertising system. It can use AI to improve ad targeting, automate campaign creation, answer more complex queries and sell infrastructure to outside customers. Google Cloud’s 82% growth provides evidence that the company is monetizing AI beyond its own consumer products.

The company also possesses data and distribution advantages. Billions of users interact with Google products, giving Alphabet opportunities to introduce new interfaces without requiring customers to adopt an unfamiliar brand. Advertisers already use its auction systems, measurement tools and campaign workflows. Developers and enterprises can access AI models through Cloud. Those advantages do not guarantee that margins will remain intact, but they reduce the probability that Alphabet becomes irrelevant in an AI transition.

The search franchise still finances the transition

Search and other advertising revenue of $63.3 billion in one quarter remains the core economic engine. The franchise benefits from user habit, distribution agreements, advertiser demand and the enormous volume of commercial intent expressed through queries. When a consumer searches for a product, service or destination, the query often reveals immediate purchasing interest. That makes search advertising unusually measurable and valuable.

AI could enhance that system by allowing users to ask more complex questions and by helping advertisers create better campaigns. It could also cannibalize some traditional searches or increase the cost of answering them. Alphabet’s challenge is to change the product before a competitor does while preserving the economics that fund the change.

The company’s network advertising revenue was slightly weaker, showing that not every advertising channel benefits equally. YouTube remains a distinct asset, with video advertising, subscriptions and creator relationships that provide another route to attention. The combination of Search, YouTube and Android gives Alphabet multiple consumer touchpoints, but it also attracts regulatory scrutiny over competition, default placement and data use.

The balance sheet is strong, but financing choices deserve scrutiny

Alphabet ended the quarter with approximately $242.5 billion of cash and marketable securities and about $98.2 billion of debt. That is a formidable liquidity position. The company also raised significant capital through equity and debt during the quarter and established an at-the-market equity program, according to its release.

External financing is not inherently negative when a company can invest at high returns. It becomes a concern when capital spending rises faster than internally generated cash and the return on new assets is uncertain. Alphabet’s unusually large investment gains complicate the picture because they strengthen reported equity and earnings without directly funding the operating returns investors expect from Cloud and Search.

The key question is whether the infrastructure being built today becomes a scarce, highly utilized asset or a rapidly depreciating commodity. Google’s custom tensor processing units may provide cost and performance advantages. Its engineering scale may improve utilization. Cloud contracts may create recurring demand. Yet the industry is expanding so quickly that supply, model efficiency and pricing could change before current investment fully pays back.

The supporting case for Alphabet

The supporting case is that Alphabet has already demonstrated an ability to turn AI into revenue and profit. Cloud growth accelerated, Cloud operating income more than tripled and Search continued to expand despite years of predictions that new interfaces would destroy it. The company’s operating margin improved even as it invested heavily.

Alphabet also has strategic optionality. If the highest returns accrue to infrastructure, it owns Cloud and custom chips. If they accrue to models, it owns Gemini and related technology. If they accrue to consumer applications, it owns distribution across Search, YouTube, Android and other services. If they accrue to advertising, it owns the auction and measurement systems that connect businesses with users.

Morningstar’s $433 valuation assumes that these advantages will support long-term growth while the company navigates capital intensity. The August 3 discount suggests that the market is not pricing a perfect outcome, even though the margin of safety is narrower than for some of the other names.

The skeptical case for Alphabet

The skeptical case is that the company is spending at a pace that changes the economics of the business before investors know what the mature AI market will look like. Negative quarterly free cash flow is not dangerous for a company with Alphabet’s balance sheet, but it is a signal that the transition is expensive. If model prices fall, customer workloads shift or competitors match performance, the return on infrastructure may disappoint.

Search faces genuine disruption. Even if Google retains users, AI-generated responses may alter ad inventory, click behavior and traffic to publishers. Regulatory remedies could affect distribution agreements or data practices. The company’s equity investments add volatility to reported earnings and can distract from operating trends. Finally, a $4.5 trillion market value at the August 3 price requires enormous absolute profit growth, regardless of whether the stock trades below one analyst’s fair value estimate.

Alphabet’s quarter strengthened the case that it can monetize AI. It also made the capital-allocation debate more urgent. The stock is undervalued only if the new infrastructure earns returns that compensate for its cost and if Search adapts without losing its extraordinary economics.

S&P Global: A Data Franchise Tested by AI and a Major Spin-Off

The post-spin financial picture is stronger than the transcript suggests

S&P Global’s second-quarter results require careful reading because the company completed the spin-off of Mobility Global on July 1, one day after the quarter ended. Reported results still included the Mobility business, while management also presented pro forma figures designed to show the continuing company as if the separation had already occurred. Comparing the wrong set of numbers can create a misleading view of growth or margins.

On a reported basis, second-quarter revenue increased 10% to $4.15 billion. GAAP operating profit rose 17% to $1.81 billion, net income increased 14% to $1.22 billion and diluted earnings per share advanced 18% to $4.12. On a pro forma basis excluding Mobility, revenue was $3.68 billion, up 11%, operating profit was $1.76 billion, up 21%, and diluted EPS was $4.08, up 26%. The official earnings release also reported adjusted EPS of $4.83 and an increase in adjusted operating margin.

The distinction matters because the continuing S&P Global now has a different revenue mix. Ratings, Market Intelligence, Commodity Insights and Indices sit at the center of the valuation. Mobility Global is a separately traded company. Historical comparisons that do not adjust for the separation can overstate or understate growth, and investors should expect temporary complexity in financial models, corporate costs and capital allocation.

Morningstar’s August 3 transcript contained an obvious transcription error, rendering the fair-value estimate as “$55.” A Morningstar financial-services review published July 9 listed a $505 estimate for S&P Global. At the August 3 intraday price of $410.57, that would imply a discount of about 18.7%.

Why ratings remain a powerful business

The ratings franchise is often misunderstood as a conventional research business. Its economics depend on more than the ability to analyze a company’s balance sheet. Credit ratings are embedded in regulations, investment mandates, bond documentation, collateral rules and market practice. Issuers pay for ratings because investors and intermediaries recognize the scale, methodologies and historical record of the major agencies. Investors use the ratings because they provide a common language for credit risk.

That position creates intangible assets and network effects. A rating becomes more useful when many issuers, investors and regulators rely on the same framework. A new competitor may produce intelligent analysis, but it must also earn trust, obtain regulatory recognition, build a record across cycles and persuade market participants to incorporate its opinions into contracts and systems. Those barriers help explain the industry’s concentrated structure.

The business is not immune to cycles. Debt issuance can fall when rates rise, spreads widen or economic uncertainty increases. Structured-finance volumes can change sharply. Corporate refinancing waves can create strong periods, while quiet capital markets reduce transaction revenue. S&P Global also faces legal, regulatory and reputational risk because ratings influence investment decisions and because failures during past credit cycles remain part of the industry’s history.

Over a full cycle, however, nominal economic growth, refinancing needs, new issuance and pricing have supported expansion. The company’s scale allows it to invest in analytics and compliance while maintaining attractive margins. The July quarter’s growth suggests that the franchise remains economically strong despite higher rates and concerns about AI.

Indices and benchmarks compound through the financial system

S&P Global’s index business benefits from a different kind of network effect. The S&P 500 and other benchmarks are used in index funds, exchange-traded funds, derivatives, performance measurement and financial contracts. Asset managers and exchanges pay licensing fees, often linked to assets or trading volumes. As more capital tracks an index, the benchmark becomes harder to replace because investors, advisers and institutions coordinate around it.

This is a capital-light model. S&P Global does not need to own the securities in an index. It develops and maintains the methodology, licenses the intellectual property and supports the ecosystem. Market appreciation can increase assets linked to the indices, while new products create additional revenue streams. The exposure also introduces market sensitivity: falling asset values or lower derivatives activity can reduce fees.

The benchmark franchise illustrates why proprietary designation matters in an AI economy. A model can summarize the S&P 500 methodology, but it cannot unilaterally create the legal and commercial rights to use the S&P name in an investment product. The value resides in the recognized benchmark, governance process, brand and network of contracts—not merely in the text describing it.

Market Intelligence and Commodity Insights face the most direct AI debate

The Market Intelligence and Commodity Insights businesses provide data, research, pricing, software and workflow tools. These products are deeply embedded in investment analysis, risk management, banking, corporate strategy and commodity trading. Customers often pay recurring subscriptions, which can create switching costs because internal processes, models and compliance systems depend on the data.

Generative AI can affect these businesses in two opposite ways. It can reduce the cost of creating generic summaries, basic company profiles and routine analysis. Products that charge primarily for information that is widely available may face pricing pressure. Customers may expect faster answers and natural-language interfaces without paying more.

At the same time, AI increases the value of clean, structured, permissioned and reliable data. A sophisticated model is only as useful as the information it can access and the confidence a professional user can place in the result. Financial institutions cannot base regulated decisions on an answer whose source, methodology and rights are unclear. S&P Global can combine proprietary datasets with AI interfaces, allowing customers to query information more efficiently while retaining source traceability.

The company’s strongest defense is therefore not that AI will fail. It is that AI will become an interface to trusted data rather than a substitute for it. The risk is that customers capture most of the productivity benefit, forcing S&P Global to provide better tools without materially higher prices. The opportunity is that the company expands usage, increases retention and sells higher-value workflow products.

The spin-off sharpens the capital-allocation story

Separating Mobility Global allows management to focus on financial information, benchmarks and ratings. It also changes the company’s cash-flow profile and creates questions about stranded costs, leverage, repurchases and the appropriate valuation multiple. Management expects more than $7 billion of share repurchases in 2026, according to its guidance.

Buybacks create value only when shares are repurchased below intrinsic value and when the balance sheet remains appropriately funded. If Morningstar’s $505 estimate is reasonable, buying stock near $410 could be accretive. If AI erodes long-term growth or if the post-spin cost structure is weaker than expected, the apparent discount may be overstated.

The company’s raised or maintained guidance provides some confidence. For 2026, S&P Global projected adjusted diluted EPS of $17.50 to $17.75 on the post-spin basis and organic constant-currency revenue growth of 6% to 8%. Guidance is not a guarantee. It is management’s current expectation, subject to issuance activity, market levels, expenses, foreign exchange and execution.

The supporting case for S&P Global

The supporting case is that S&P Global owns assets that are difficult to replicate: recognized ratings, globally used indices, proprietary datasets, pricing methodologies and deeply integrated customer workflows. These franchises require relatively little physical capital, generate recurring or repeat revenue and benefit from the growth of global financial markets.

AI may strengthen the model by increasing demand for authoritative data. The company can add natural-language tools to existing products, make analysts more productive and monetize information across more users. The post-spin company is more focused, and repurchases at a discount could increase per-share value.

The skeptical case for S&P Global

The skeptical case is that the market is correctly anticipating pressure on premium data products. If customers can use their own AI systems to combine public filings, alternative datasets and lower-cost providers, some subscription products may lose pricing power. Regulators could scrutinize ratings or index concentration. Debt issuance remains cyclical. The Mobility separation can create dis-synergies and make historical performance harder to interpret.

The stock’s moderate discount provides some compensation, but the valuation still assumes that S&P Global remains a high-margin compounder. The quarter supports that view. The next several years will show whether AI expands the company’s moat or exposes which parts of the product suite were protected mainly by an inefficient user interface.

Charles Schwab: A Scale Business Whose Earnings Move With Cash, Markets and Rates

The second quarter demonstrated operating leverage

Charles Schwab reported record quarterly revenue of approximately $7.07 billion, an increase of 21% from the prior year. Net income rose 32% to about $2.8 billion. GAAP diluted earnings per share increased 43% to $1.54, while adjusted diluted EPS rose 42% to $1.62. The company’s official release attributed the performance to asset growth, market levels, trading activity and continued business momentum.

Total client assets reached $13.08 trillion, up 22%. Core net new assets were $119.8 billion, up 49%. Schwab added roughly 1.4 million brokerage accounts during the quarter and ended with about 48 million client accounts. Daily average trades were 11.9 million.

These figures illustrate the scale model. Schwab spreads technology, compliance, custody, service and product-development costs across trillions of dollars of assets and tens of millions of accounts. When assets and activity rise, revenue can grow faster than expense. That operating leverage helped drive the sharp increase in earnings.

Morningstar raised its fair-value estimate to $124 from $117 after the quarter, citing stronger wealth-management assumptions, better-than-expected results and the passage of time. At $105.77 on August 3, the stock traded about 14.7% below the new estimate.

Schwab is not simply an online broker

Trading commissions once defined the public image of brokerage firms. The modern Schwab earns revenue from a broader system: net interest income, asset-management and administration fees, trading revenue, advisory services, bank products and lending. The company serves self-directed investors, independent advisers and wealth-management clients. Its custody platform gives registered investment advisers access to infrastructure they would struggle to build independently.

The broad model creates cross-selling opportunities. A client may begin with a brokerage account, hold cash, purchase Schwab funds, use advice, borrow against securities or move retirement assets onto the platform. The company can invest in technology once and distribute it across channels. A large asset base also supports low product fees, which can attract more assets and reinforce scale.

That cost advantage is one source of Schwab’s economic moat. Another is switching friction. Moving a financial relationship is possible, but clients may hesitate to transfer holdings, tax records, payment instructions, adviser relationships and banking services. Independent advisers face an even larger operational change if they move custody platforms.

Client cash remains the central variable

Schwab’s business model benefits when clients leave cash in low-cost deposit accounts that the company can invest or lend at higher yields. When market rates rise, clients have a greater incentive to move that cash into money-market funds, Treasury securities or other higher-yielding alternatives. The result is cash sorting.

Cash sorting does not necessarily mean assets leave Schwab. A client who moves money from a bank sweep into a Schwab money-market fund may remain within the platform. The economics change because Schwab earns an asset-management fee rather than a wider interest spread. The balance-sheet funding mix can also change, influencing liquidity and borrowing needs.

The second-quarter numbers showed strong growth in bank loans, including margin lending. Margin loans reached about $165.1 billion, up sharply from the previous quarter, while bank loans totaled about $67 billion. Lending can enhance returns when collateral values are stable and credit losses remain low. It introduces risk if markets fall rapidly or clients become overleveraged.

Interest rates affect Schwab through several channels: the yield on securities and loans, the cost and stability of funding, client demand for cash products and the valuation of securities on the balance sheet. A steep yield curve can be helpful if assets reprice faster than funding. A sudden change in rates can create mark-to-market volatility and influence deposit behavior.

The company’s experience during the 2023 banking stress remains relevant. Schwab was not a failed bank, but investors became concerned about unrealized losses and deposit outflows. The episode demonstrated that even a well-capitalized brokerage can be valued like a financial institution when the market questions its funding. Since then, balance-sheet repair and asset growth have improved the picture, yet the sensitivity has not disappeared.

Market levels amplify both growth and risk

Schwab’s $13.08 trillion of client assets reflect net inflows as well as market appreciation. Rising equity prices increase asset-based fees and client wealth. They can stimulate trading, options activity, borrowing and advisory demand. The same mechanism works in reverse during a bear market.

Core net new assets are therefore more informative than total asset growth alone because they measure money attracted to the platform rather than gains caused by market performance. The 49% increase in quarterly core net new assets supports the argument that Schwab is gaining relationships, not merely riding the market.

Retention and service quality matter. Technology outages, poor execution, weak advice or confusing products can cause clients and advisers to reconsider the platform. The scale advantage can become a disadvantage if systems are slow to change or service deteriorates. Schwab must invest enough to serve growing volumes without allowing expenses to consume operating leverage.

Wealth management is a long-duration opportunity

Schwab’s opportunity extends beyond acquiring brokerage accounts. Aging investors, retirement rollovers and the transfer of wealth across generations create demand for advice and planning. The company can offer automated portfolios, managed accounts, financial consultants and access to independent advisers.

Wealth-management relationships tend to be stickier than transactional trading accounts. They can also produce recurring fees and deeper household relationships. Morningstar’s fair-value increase reflected stronger wealth-management forecasts, suggesting that the analyst sees more value in the long-term mix than a simple trading-revenue model would imply.

The challenge is to grow advice without undermining Schwab’s low-cost positioning. Investors increasingly expect transparent fees and fiduciary standards. Independent advisers, robo-advisers, banks and other brokers compete for the same assets. Schwab’s distribution and brand are advantages, but the company must demonstrate that its services justify their price.

The supporting case for Schwab

The supporting case is that Schwab combines scale, trusted custody, a broad product suite and strong asset gathering. Record revenue and earnings show how powerful operating leverage can become when markets, trading and net interest revenue align. Core inflows indicate continued customer acquisition. The company’s balance sheet has moved beyond the most acute concerns of the earlier rate shock.

Schwab can reinvest in digital tools, advice and lending while maintaining competitive pricing. Its platform becomes more valuable as more clients, advisers and assets participate. If revenue compounds near the rates Morningstar expects and expenses grow more slowly, earnings per share can rise faster than revenue.

The skeptical case for Schwab

The skeptical case is that the latest quarter benefited from favorable market and trading conditions that may not persist. Asset values can fall. Trading activity can normalize. Client cash can move toward lower-margin products. Margin lending can contract or produce losses in a sharp downturn. Regulatory capital and liquidity requirements can limit flexibility.

The stock also carries financial-sector complexity that a simple price-to-earnings ratio cannot capture. Earnings depend on the balance sheet, not just the customer platform. A moderate discount to fair value is helpful, but it does not eliminate the possibility that rates or markets move in a direction that weakens near-term profitability.

Schwab’s quarter supports the idea of a “growth at scale” business. The valuation case is strongest for investors who believe the company can continue gathering assets through multiple market cycles while managing cash and balance-sheet risk more conservatively than the market fears.

Northrop Grumman: Record Backlog, Strategic Programs and the Cost of Execution

The headline quarter was a beat and raise

Northrop Grumman reported second-quarter sales of $10.88 billion, an increase of 5% from the prior year. Operating income was $1.10 billion, and diluted earnings per share were $7.68. Adjusted free cash flow rose 54% to $978 million. The company received $20.0 billion of net awards and ended the quarter with a record backlog of $104.7 billion.

Management raised full-year sales guidance to a range of $43.75 billion to $44.25 billion and increased its mark-to-market-adjusted earnings-per-share guidance to $28.60 to $29.10. It maintained adjusted free-cash-flow guidance of $3.1 billion to $3.5 billion. The figures come from Northrop’s official second-quarter earnings announcement.

Morningstar’s $630 fair-value estimate implies a 13.3% discount at the August 3 intraday price of $546.01. That is the smallest discount in the five-stock comparison after Alphabet, but Northrop’s earnings visibility is unusually long because major defense programs can run for decades.

Backlog is valuable, but it is not profit

A $104.7 billion backlog provides evidence of contracted demand and supports production planning. It can help a contractor invest in facilities, suppliers and workers with confidence that programs will continue. The backlog also reflects the strategic importance of systems such as the B-21 Raider, Sentinel intercontinental ballistic missile, missile-defense components, solid rocket motors and classified programs.

Backlog must nevertheless be interpreted carefully. It represents expected revenue under contracts, not cash already collected or profit already earned. Funding can depend on annual congressional appropriations. Program quantities and schedules can change. Options may not be exercised. Most importantly, the margin on the work depends on execution.

Defense accounting often uses estimates of the total cost required to complete a long-term contract. When management concludes that a program will cost more than previously expected, it records an unfavorable estimate-at-completion adjustment. The accounting can reduce current profit even though the cash is spent over a longer period. If a contract is fixed price, the contractor may bear much of the overrun.

Northrop’s second-quarter results included unfavorable adjustments on the Stand-in Attack Weapon program and the GEM 63XL solid rocket booster. Defense Systems recorded a $68 million unfavorable adjustment associated with SiAW, while Space Systems recorded a $91 million unfavorable adjustment related to GEM 63XL. Those charges contributed to lower segment margins.

The lesson is not that the programs are failures. It is that advanced weapons and space systems contain engineering, testing, supplier and schedule risks. A contractor can have strong demand and still disappoint shareholders if the economics of the contract are weak.

The B-21 Raider is strategically important and financially complex

The B-21 Raider is intended to become a central part of the U.S. long-range strike and nuclear-deterrence architecture. Northrop’s Aeronautics Systems sales rose 13% in the quarter, supported by B-21, TACAMO and F-35-related work. The company and the Air Force have taken steps to expand production capacity, and Reuters reported that the first delivery is targeted for 2027.

Early-stage development programs can carry lower margins and greater uncertainty than mature production contracts. Engineering changes, testing discoveries, supplier constraints and inflation can affect cost. As a program moves into stable production, unit economics may improve through learning, scale and better absorption of fixed costs.

The supporting valuation argument assumes that Northrop’s margin profile improves as programs mature. Morningstar’s long-term forecast cited in the episode anticipated average top-line growth around 5.1% over five years and modest margin improvement as development work shifts toward production. That is plausible, but the path may be uneven.

Sentinel offers visibility and risk in equal measure

The Sentinel program is designed to replace the Minuteman III intercontinental ballistic missile system. It is one of the largest and most complex defense-development efforts in the United States, involving missiles, launch facilities, command systems, communications and extensive infrastructure across multiple states.

Programs of this scale create substantial barriers to entry. Few companies can assemble the engineering, security clearances, manufacturing capacity and supplier network required. Once a contractor is deeply embedded, switching becomes difficult and expensive. Those intangible assets and switching costs support Northrop’s wide-moat assessment.

The same complexity creates risk. Requirements can change. Construction can encounter delays. Costs can rise faster than appropriations. Government oversight can intensify. The program’s strategic importance makes cancellation less likely than for a discretionary product, but it does not guarantee attractive contractor returns.

Demand is being reinforced by geopolitics and production agreements

On August 3, after the Morningstar episode was published, Northrop announced two multi-year framework agreements totaling more than $3 billion with the U.S. Department of War and Lockheed Martin to accelerate missile-interceptor production. The company’s investor-relations release list described the agreements as a way to provide speed, scale and production certainty.

The announcement adds to evidence that governments and prime contractors are seeking more capacity for missiles and interceptors. Multi-year frameworks can support investment in facilities and suppliers because demand is clearer. The economic result will depend on pricing, contract terms and execution. A larger production commitment is valuable only if the company can deliver at margins that compensate for capital and risk.

International defense spending also offers potential growth. European and allied countries are rebuilding inventories and increasing procurement after years of underinvestment. Northrop can benefit directly through exports and indirectly through sales to U.S. programs designed to support allies. Export controls, political approvals and local-content requirements can limit the opportunity.

The balance between cash flow and investment

Northrop’s adjusted free cash flow of $978 million in the second quarter was strong, and the company maintained a full-year target of $3.1 billion to $3.5 billion. Cash conversion matters because defense accounting can recognize revenue before payment, while inventories and contract assets consume working capital.

The company is also investing in capacity. New facilities, tooling and supplier commitments may be necessary to meet demand. Those investments can create long-lived value if production volumes materialize. They can reduce near-term free cash flow and increase the cost of a program if schedules slip.

Capital returns must be balanced with that investment. Northrop pays a dividend and repurchases shares, but management cannot treat backlog as permission to distribute cash that may be needed for execution. The strongest capital-allocation strategy is one that funds high-return program capacity, maintains balance-sheet resilience and returns genuine excess cash.

The supporting case for Northrop Grumman

The supporting case rests on strategic necessity. The United States and its allies are committing to long-duration programs in stealth aircraft, nuclear deterrence, missile defense, space and advanced weapons. Northrop is one of a small number of companies capable of executing them. Record backlog, $20 billion of quarterly awards and raised guidance provide visibility that most industrial businesses cannot match.

If development programs transition into production and margin pressure eases, earnings and cash flow can grow faster than revenue. The August 3 missile-interceptor agreements reinforce the demand outlook. A valuation below Morningstar’s $630 estimate offers some compensation for execution risk.

The skeptical case for Northrop Grumman

The skeptical case is visible in the same quarter. Operating margin fell to 10.1% from 13.8%, partly because the prior-year comparison included a divestiture benefit but also because program charges reduced profitability. Cost estimates can change suddenly. Fixed-price development contracts can transfer technical risk to shareholders. Backlog can be politically secure while margins remain disappointing.

Defense budgets also face competing priorities and fiscal constraints. A program may be strategically important but funded more slowly than contractors expect. Supply-chain bottlenecks, labor shortages and inflation can pressure delivery. International opportunities introduce political and regulatory uncertainty.

Northrop is therefore not a simple geopolitical trade. It is a project-execution business with a highly attractive demand environment. The stock is undervalued only if management converts strategic importance into acceptable cash returns.

Comparing the Five Businesses: The Same Label Hides Different Economics

Calling all five stocks “undervalued” can make them sound interchangeable. They are not. The source of each company’s moat, the nature of its capital, the volatility of its earnings and the reliability of its valuation differ materially.

Microsoft and Alphabet offer the highest organic growth but also the greatest debate over capital spending. Their products can scale globally, yet the physical infrastructure supporting AI is changing the cash-flow profile. S&P Global grows more slowly but historically requires less physical capital and benefits from recurring data and licensing economics. Schwab’s growth depends partly on asset prices and rates, making its earnings more cyclical. Northrop’s revenue is backed by contracts and national-security priorities, but profitability depends on project management.

The companies also differ in how easily investors can observe demand. Microsoft discloses cloud growth and contracted obligations. Alphabet reports advertising and Cloud revenue. Schwab publishes client assets, accounts and net new assets. Northrop reports awards and backlog. S&P Global provides transaction and subscription metrics across business lines. None of those indicators directly equals economic value. Demand must be converted into cash at an acceptable return.

Another difference is the role of management estimates. Technology capital spending involves forecasts of utilization and product demand. Defense contract accounting requires estimates of total program cost. Financial firms estimate credit, funding and rate behavior. Data businesses estimate retention and the willingness of customers to pay. Every valuation contains assumptions, but the type of assumption determines what investors should monitor.

AI Spending and the Return-on-Capital Test

Microsoft and Alphabet are often described as beneficiaries of the same AI boom. That label conceals an important distinction between revenue growth and economic profit. Revenue can rise rapidly while free cash flow falls if the business requires even faster investment. Economic value is created only when the return on incremental capital exceeds the cost of that capital over time.

For a software company, historical returns can be exceptionally high because an additional copy of software costs little to distribute. Cloud computing is more capital-intensive because every workload consumes servers, networking and electricity. AI can be more intensive still, particularly during training and complex inference. If the price charged to customers reflects those costs and utilization remains high, returns can still be attractive. If model efficiency improves faster than demand or competitors add too much capacity, prices and utilization can fall.

Microsoft’s advantage is that infrastructure may pull through higher-margin software. An Azure workload can support Copilot, security, database and productivity revenue. Alphabet’s advantage is that infrastructure supports its own Search and YouTube products while also serving Cloud customers. Both companies can use custom chips to reduce dependence on outside suppliers and potentially lower cost.

The accounting will lag the investment cycle. Cash leaves when equipment and construction are paid for. Depreciation expense arrives as assets are placed in service. Revenue may ramp gradually. A period of rising capital expenditure can therefore depress free cash flow before it depresses operating margin. Later, depreciation can rise even if cash spending slows. Analysts who use only one measure can miss the sequence.

The most useful indicators are not one quarter’s capex total in isolation. Investors should watch utilization, cloud growth, pricing, remaining performance obligations, depreciation as a percentage of revenue, operating margins, free cash flow and management’s description of supply constraints. If growth remains strong while capital intensity stabilizes, returns may improve. If capex continues to outrun operating cash flow without a path to higher margins, the valuation case weakens.

S&P Global provides a useful contrast. Its AI investment is primarily in software, data organization and product development. The company can use the same proprietary dataset across many customers without building a separate data center for each one. Schwab likewise invests heavily in technology, but its marginal economics are driven by assets and financial spreads rather than computing consumption. Northrop’s capital is tied to production capacity and long-cycle programs, where returns depend on contract structure and execution.

AI is therefore not a single investment theme. It changes the return-on-capital equation differently for infrastructure providers, software distributors, data owners, financial platforms and industrial suppliers. Valuation should follow those economics rather than the popularity of the label.

How to Read the Fair-Value Discounts Without Treating Them as Price Targets

A fair-value estimate is best understood as a structured forecast. An analyst projects revenue, margins, taxes, reinvestment and cash flows, then discounts those cash flows to the present. The result may be expressed as a precise dollar amount, but the underlying inputs are ranges rather than certainties.

Morningstar describes its fair-value estimate as an assessment of long-term intrinsic value based on expected future cash generation. The methodology is more informative than a simple comparison with the average Wall Street price target because it forces an explicit link between operating assumptions and value. It remains vulnerable to model risk.

Consider Microsoft. A small change in the assumed long-term operating margin can move valuation materially because it applies to hundreds of billions of dollars of revenue. A change in the discount rate can have an equally large effect because much of the estimated value lies in future years. If Azure and AI growth exceed expectations while capital intensity normalizes, $600 may prove conservative. If margins settle below the model, it may prove optimistic.

Alphabet presents another sensitivity. Search growth, Cloud margins, capital spending and the terminal value of the business all matter. The company’s investment portfolio should be valued, but volatile gains should not be confused with operating earnings. A model that mechanically capitalizes the latest reported EPS can produce a distorted result.

S&P Global’s valuation depends on ratings issuance, subscription retention, index-linked assets and post-spin margins. A one-percentage-point change in long-term organic growth may look small, yet it can materially alter the present value of a capital-light compounder. The market’s AI concern can be translated into a model through lower pricing, slower retention or higher product-development costs.

Schwab’s model is sensitive to net interest margin, client cash allocations, asset levels and operating expense. A valuation based on one strong trading quarter may overstate normalized earnings. A model that assumes permanently depressed cash profitability may understate the benefit of scale and eventual balance-sheet normalization.

Northrop’s value depends on backlog conversion, program margins, cash timing and the durability of defense budgets. A backlog dollar should not receive the same valuation as a dollar of recurring software revenue because the contract may require substantial capital and carry execution risk. Conversely, a funded defense program can provide greater revenue visibility than discretionary corporate technology spending.

The discounts in the valuation snapshot should therefore be treated as evidence of a debate, not a signal that a stock must rise to the estimate. They show that Morningstar’s operating assumptions are more favorable than those implied by the market price. The investor’s task is to decide which set of assumptions is more credible.

Why a 15% discount may be insufficient

A margin of safety protects against errors. The more uncertain the business, the larger the discount an investor may require. A 15% gap can disappear through an earnings miss, a higher discount rate or a modest reduction in long-term margin. It may be adequate for a stable, low-uncertainty franchise and inadequate for a rapidly changing business.

None of the five stocks is a distressed security. Their valuations reflect substantial confidence in business quality. The opportunity, if it exists, comes from the market being moderately too pessimistic, not from the companies being ignored. That distinction should temper expectations. Buying a great business at a reasonable price can produce attractive long-term results, but it is different from buying an asset at a deep liquidation discount.

Why the market can remain below fair value

Stocks do not move toward fair value on a schedule. A company can remain discounted for years because the risk is persistent, the catalyst is uncertain or the broader market demands a lower multiple. S&P Global’s AI concern will not be resolved in one quarter. Northrop’s program economics unfold over years. Schwab’s rate sensitivity changes with the cycle. Microsoft and Alphabet may need several investment cycles to demonstrate AI returns.

The market price can also be correct for reasons a model has not captured. New competition, regulation, management mistakes, technological change or geopolitical events can alter the future. Fair value itself should move when the facts change. An estimate that never changes is not evidence of discipline; it may be evidence that the analyst is ignoring new information.

The Strongest Combined Case for the Five Stocks

The most persuasive common argument is that the market is underestimating durable competitive advantages while overemphasizing near-term uncertainty. Each company has a franchise that would be difficult to reproduce from scratch.

Microsoft owns an enterprise ecosystem spanning infrastructure, productivity, security and development. Alphabet owns global consumer distribution, advertising systems, Cloud infrastructure and a deep AI research base. S&P Global owns recognized ratings, benchmarks and proprietary data. Schwab owns a scaled financial platform with trillions of dollars of client assets. Northrop owns capabilities and program positions that require decades of technical experience and government trust.

The latest results provide tangible support. Microsoft’s Azure growth accelerated to 43%. Alphabet Cloud grew 82% and produced $8.8 billion of operating income. S&P Global’s continuing-business revenue and profit rose at healthy rates after adjusting for the spin-off. Schwab set records for revenue and earnings while attracting substantial net new assets. Northrop posted record backlog and raised full-year guidance.

Those are not merely narratives. They are operating results that show customer demand, pricing power or scale. The market’s concerns are also visible: capital spending, AI disruption, rate sensitivity and program charges. The supporting case is that the companies have enough competitive strength to manage those challenges and that the current prices discount more damage than ultimately occurs.

There is also diversification across economic drivers. Cloud demand, digital advertising, credit issuance, asset gathering and defense procurement do not move in perfect alignment. An investor evaluating the group is not relying on a single product cycle, although Microsoft, Alphabet and S&P Global share some exposure to AI and information technology.

The Strongest Combined Skeptical Case

The most credible skeptical argument is that investors are paying premium prices for premium businesses at a moment when the cost of capital and the cost of growth are rising. The stocks may be below Morningstar fair value, but they are not conventionally cheap on every measure.

Microsoft and Alphabet are spending amounts that would have seemed extraordinary only a few years ago. Their cash flows must support not only current operations but a continual infrastructure race. The competitive landscape includes other well-capitalized companies, open-source models and customers seeking to reduce dependence on any one provider. Strong demand does not guarantee high incremental returns.

S&P Global’s moat is durable, yet AI may reduce the value of basic analysis and place pressure on subscription pricing. The company’s post-spin disclosures require adjustments, creating room for overly optimistic comparisons. Share repurchases can support per-share growth, but they do not solve a structural decline in product value if one emerges.

Schwab’s record results occurred in a favorable market environment. Asset values and trading activity can reverse. Its bank balance sheet adds a layer of risk that a pure software platform does not have. A future rate shock could revive concerns about funding or securities values.

Northrop’s demand is politically supported, but program execution remains unforgiving. The quarter’s margin pressure demonstrates that strong sales and awards can coexist with unfavorable contract adjustments. Government customers possess bargaining power, and strategic importance can lead contractors to accept difficult terms.

The common risk is that the market is not irrationally pessimistic. It may be applying a justified discount to businesses whose next stage of growth is more capital-intensive, regulated or operationally complex than the previous one.

What the Rest of the Week Can Reveal

The August 3 discussion also pointed to upcoming results from Advanced Micro Devices, SanDisk and Western Digital. Those reports will provide additional evidence about the AI infrastructure cycle. Semiconductor and storage suppliers can reveal whether demand is broadening, whether shortages are supporting prices and whether customers are maintaining aggressive capital plans.

SpaceX presents a separate test of market appetite. The company priced its June 11 initial public offering at $135 per share, raising about $75 billion through the sale of roughly 555.6 million shares at a reported valuation near $1.77 trillion. SpaceX is scheduled to report its first results as a public company after the market closes on August 4, according to its investor-relations announcement.

The report is important not because SpaceX belongs in the five-stock comparison, but because it concentrates several themes affecting the market: massive capital requirements, AI infrastructure, satellite communications, subscriber economics and the difficulty of valuing a business with extraordinary growth expectations. The expiration of lock-up restrictions on a large block of pre-IPO shares also creates potential supply in the market. Share eligibility does not mean every holder will sell, but it can affect short-term trading.

The results from these companies will help answer whether the current investment cycle is producing balanced economics across the supply chain. If cloud platforms grow rapidly while suppliers gain pricing power and customers keep increasing commitments, the cycle may have further room. If capacity expands faster than end demand, returns can compress even while reported revenue remains strong.

What Investors Should Watch Next for Each Company

Microsoft

• Azure growth and capacity: Whether growth remains above 40% and whether management continues to describe demand as supply constrained.
• Depreciation and margins: Whether the wave of data-center investment begins to pressure Cloud and consolidated operating margins.
• Commercial commitments: The growth and timing of remaining performance obligations, including the concentration of large contracts.
• Copilot monetization: Evidence that AI applications generate incremental subscription revenue rather than merely increasing infrastructure cost.
• Free cash flow: Whether operating cash generation keeps pace with capital spending over a full year.

Alphabet

• Google Cloud profitability: Whether Cloud maintains high growth while expanding margins and absorbing infrastructure cost.
• Search economics: Changes in query growth, ad pricing and monetization as AI-generated answers become more prominent.
• Capital expenditure: Whether spending above $200 billion in 2026 produces visible utilization and revenue growth.
• Normalized earnings: Operating profit and cash flow excluding volatile gains on equity securities.
• Regulatory outcomes: Remedies or rules that affect search distribution, advertising technology, app ecosystems or data use.

S&P Global

• Post-spin margins: Whether the continuing company removes stranded costs and delivers the expected profitability.
• Ratings issuance: Corporate, structured-finance and refinancing activity as rates and credit spreads change.
• Subscription retention: Pricing, renewal rates and customer usage in Market Intelligence and Commodity Insights.
• AI products: Evidence that new tools improve retention or revenue rather than simply adding expense.
• Repurchases: The pace and price of the planned 2026 buybacks relative to cash generation and leverage.

Charles Schwab

• Core net new assets: Whether client inflows remain strong when markets are less favorable.
• Cash sorting: The mix between bank sweep deposits, money-market funds and other cash products.
• Net interest margin: How the rate path and funding mix affect interest revenue.
• Credit and leverage: Margin-loan balances, collateral quality and loss experience.
• Expense discipline: Whether technology and service investment can grow without eroding operating leverage.

Northrop Grumman

• Program adjustments: Any additional unfavorable estimates on SiAW, GEM 63XL, Sentinel or other development programs.
• Backlog conversion: The pace at which awards become sales and cash.
• Production margins: Evidence that B-21 and other programs improve economically as they mature.
• Free cash flow: Working-capital requirements and capital spending needed to expand production.
• Appropriations and contracts: Funding, multi-year agreements and changes in procurement quantities.

Frequently Asked Questions

What does “undervalued after earnings” mean?

It means an analyst believes the market price is below an estimate of the company’s long-term intrinsic value after incorporating the latest reported results. The phrase does not mean the stock is guaranteed to rise. The estimate depends on assumptions about future revenue, margins, cash flow, capital spending and risk.

Which of the five stocks had the largest discount to Morningstar fair value on August 3, 2026?

Using intraday prices at approximately 11:40 a.m. Eastern time and the cited Morningstar estimates, Microsoft and S&P Global each traded about 18.7% below fair value. Schwab’s discount was about 14.7%, Alphabet’s was about 13.6% and Northrop Grumman’s was about 13.3%. The ranking can change with stock prices or revised estimates.

Why did the Microsoft discount differ from the percentage mentioned earlier in the day?

Microsoft shares rose roughly 5% during the August 3 session. A fair-value discount narrows when the market price rises and the fair-value estimate stays unchanged. The episode’s percentage reflected an earlier price; the table in this article uses an intraday price near 11:40 a.m. Eastern time.

Is Morningstar’s fair value the same as a Wall Street price target?

No. Both are analyst estimates, but Morningstar describes its fair value as a long-term discounted-cash-flow assessment. A conventional price target often refers to an expected price over a shorter period, commonly 12 months. Neither is an objective or guaranteed future price.

Why can a company beat earnings expectations and still be undervalued?

A stock price reflects expectations before the report. A company may beat the consensus yet remain below an analyst’s estimate of long-term value because the market is worried about future margins, capital spending, regulation or cyclical risk. The opposite also occurs: a company can beat expectations and still be overvalued if the stock already assumes even stronger performance.

What is the main risk to Microsoft’s valuation?

The main risk is that AI and cloud infrastructure require more capital and produce lower incremental margins than investors expect. Competition, rapid equipment obsolescence, security problems and regulation also matter. Azure demand is strong, but the return on the new asset base will determine whether growth creates sufficient value.

What is the main risk to Alphabet’s valuation?

Alphabet must preserve the economics of Search while funding an exceptionally large AI infrastructure program. Generative AI can change user behavior and advertising formats. Capital spending may exceed free cash flow in some periods. Regulatory actions and volatile investment gains add complexity.

Why is Alphabet’s reported second-quarter net income misleading for valuation?

The $112.2 billion figure included an approximately $99.0 billion gain on equity securities. The gain increased after-tax net income by about $77.1 billion. It is part of reported GAAP earnings, but it is not recurring operating profit from Search, YouTube or Cloud, so analysts usually normalize it when estimating ongoing earnings power.

Can AI destroy S&P Global’s moat?

AI can pressure generic research and make basic analysis cheaper. S&P Global’s strongest assets are harder to replace: recognized credit ratings, licensed indices, proprietary datasets, pricing methodologies and embedded workflows. AI may increase the value of reliable data, but the company must prove that it can retain pricing power as customers adopt new tools.

Why is Schwab sensitive to interest rates?

Schwab earns substantial net interest revenue from loans and securities funded partly by client cash. Rates affect asset yields, funding costs and the incentive for clients to move cash into higher-yielding products. The result depends on the yield curve, deposit mix and balance-sheet management rather than simply on whether rates rise or fall.

Does Northrop Grumman’s backlog guarantee future earnings?

No. Backlog represents expected revenue under contracts and awards, subject to funding, options, schedules and performance. Profit depends on contract terms and actual costs. Unfavorable program adjustments can reduce margins even when backlog and sales are growing.

Which company has the most predictable revenue?

Predictability depends on the time horizon and definition. Microsoft has recurring software and cloud contracts. S&P Global has subscriptions and embedded benchmarks. Schwab has recurring asset-based and interest revenue but greater market sensitivity. Northrop has long-term government contracts but execution risk. Alphabet’s advertising is highly cash generative but can respond to economic and technological change. No single company is predictably superior across all conditions.

Are these five stocks diversified enough to form a complete portfolio?

No. The group spans technology, financial services and defense, but it remains concentrated in large U.S. companies and includes overlapping exposure to AI, capital markets and broad economic conditions. A diversified portfolio generally considers additional sectors, company sizes, geographies, asset classes and individual financial circumstances.

What evidence would weaken the undervaluation argument?

For Microsoft and Alphabet, slowing cloud growth combined with persistently high capital spending would be damaging. For S&P Global, weaker subscription retention or pricing would challenge the moat. For Schwab, renewed funding pressure or sustained asset outflows would matter. For Northrop, repeated cost overruns and lower cash conversion would weaken the case. A sustained increase in long-term interest rates could also reduce fair values across the group.

What evidence would strengthen the undervaluation argument?

Stable or improving margins alongside continued growth would be the most persuasive evidence. Microsoft and Alphabet need to show better returns on AI infrastructure. S&P Global needs to monetize AI-enhanced data products while preserving retention. Schwab needs continued asset gathering and balanced cash economics. Northrop needs backlog conversion with fewer adverse program adjustments and stronger free cash flow.

Final Assessment

The five stocks highlighted after earnings share two characteristics: each company controls a valuable franchise, and each faces a risk that the market cannot resolve with one quarter of data. Microsoft and Alphabet must prove that unprecedented AI spending creates durable returns. S&P Global must show that trusted data and benchmarks become more—not less—valuable when generative AI changes research workflows. Schwab must convert scale and client growth into earnings across different rate and market environments. Northrop Grumman must turn strategic demand and record backlog into cash without allowing program complexity to consume margins.

The latest evidence is constructive. Azure growth accelerated, Google Cloud produced extraordinary growth and profit, S&P Global’s continuing operations expanded, Schwab attracted substantial new assets and Northrop raised guidance. Those results explain why Morningstar continues to value the companies above their August 3 market prices.

The strongest concern is capital and execution. Revenue growth is valuable only when it produces sufficient cash after the investment required to generate it. Microsoft and Alphabet are testing that principle through data centers. Schwab tests it through a financial balance sheet. Northrop tests it through long-term contracts. S&P Global tests it through continued investment in proprietary data and workflow products.

At discounts of roughly 13% to 19%, the market is offering a moderate margin of safety, not immunity from error. The most important developments to watch are not short-term price moves. They are cloud margins and free cash flow, Search monetization, data-product retention, client cash behavior, and defense-program cost performance. Those operating indicators will determine whether the current gap between price and estimated value represents opportunity or a warning that the models are too optimistic.

This article is provided for general informational purposes and does not constitute financial, investment, tax, or legal advice.

Sources

• Morningstar: “5 Stocks to Buy That We Still Like After Earnings”
• Morningstar definition of fair-value estimate
• Morningstar: Why Microsoft Stock Is Worth $600
• Morningstar analysis of Alphabet’s second-quarter 2026 results
• Morningstar analysis of Charles Schwab’s second-quarter 2026 results
• Morningstar financial-services sector review, July 9, 2026
• Federal Reserve: July 29, 2026 FOMC statement
• Reuters reporting on the July 2026 Federal Reserve decision and market reaction
• Microsoft fiscal 2026 fourth-quarter earnings release
• Alphabet second-quarter 2026 earnings release
• S&P Global second-quarter 2026 earnings release
• S&P Global second-quarter 2026 earnings release filed with the SEC
• Charles Schwab second-quarter 2026 earnings release
• Northrop Grumman second-quarter 2026 earnings announcement
• Northrop Grumman investor-relations news releases
• Reuters: Northrop Grumman raises 2026 forecasts
• SpaceX announcement of second-quarter 2026 results and webcast
• SpaceX amended registration statement filed with the SEC
• Reuters: SpaceX prices its June 2026 initial public offering
• Nasdaq market data for Microsoft
• Nasdaq market data for Alphabet
• Nasdaq market data for S&P Global
• Nasdaq market data for Charles Schwab
• Nasdaq market data for Northrop Grumman

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