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U.S. Treasury Yields Hold Steady as Markets Await Fed Signals and Key Inflation Data

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U.S. Treasury yields were broadly unchanged on Tuesday as investors returned from the Presidents’ Day holiday to a light trading session, with attention turning to Federal Reserve minutes and delayed economic data that could shape the near-term interest-rate outlook.

The benchmark 10-year Treasury yield dipped less than one basis point to 4.054%, while the 30-year bond yield eased 1 basis point to 4.689%. The policy-sensitive 2-year note yield rose 2 basis points to 3.43%. One basis point equals 0.01 percentage point, and yields move inversely to prices.

With liquidity thinner than usual at the start of the week, bond traders appeared reluctant to take large positions ahead of a series of potentially market-moving releases.

All Eyes on FOMC Minutes and PCE

The focal point for markets this week is the release of minutes from the Federal Open Market Committee (FOMC) meeting on Wednesday. Investors will scrutinize the document for clues about policymakers’ assessment of inflation, labor-market conditions, and the appropriate timing of future rate adjustments.

Particular attention will be paid to whether officials expressed concern about sticky services inflation or signaled growing confidence that price pressures are sustainably easing toward the Fed’s 2% target.

Friday’s release of December’s personal consumption expenditures (PCE) index — the Fed’s preferred inflation measure — is expected to be the week’s most consequential data point. Unlike the consumer price index (CPI), the PCE gauge adjusts for changes in consumer behavior and carries a heavier weighting in the Fed’s policy framework.

A softer-than-expected PCE reading could reinforce expectations for rate cuts later this year. Conversely, a firmer print may push back the timeline for easing and reprice short-term yields higher.

Housing data for November and December, due Wednesday, will also offer insight into how the sector is responding to elevated borrowing costs.

Market Pricing and Yield Curve Dynamics

According to the CME FedWatch Tool, traders are assigning roughly a 90% probability that the Federal Reserve will keep its benchmark rate unchanged within the 3.50%–3.75% range at its upcoming meeting.

Money markets are currently pricing in modest easing later in the year, but expectations remain data-dependent.

The slight uptick in the 2-year yield — the maturity most sensitive to shifts in monetary policy expectations — suggests investors are cautious about positioning too aggressively for imminent cuts.

Meanwhile, the spread between the 2-year and 10-year yields remains inverted, with the 2-year below the 10-year, reflecting expectations that policy rates may decline over the medium term as growth moderates. Yield-curve inversions have historically been viewed as recession indicators, though the lag between inversion and economic slowdown can be extended.

Macro Backdrop: Balancing Growth and Inflation

The Treasury market is navigating a complex macroeconomic environment. Inflation has moderated significantly from prior peaks, yet certain components — particularly services and wage growth — have shown resilience.

At the same time, growth indicators have delivered mixed signals. Consumer spending has held up better than expected in recent months, while business investment and housing activity have remained more subdued under the weight of higher financing costs.

This cross-current has kept longer-dated yields relatively range-bound. The 10-year yield near 4% reflects a balance between expectations of eventual policy easing and persistent concerns about structural inflation pressures, fiscal deficits, and elevated Treasury issuance.

Beyond monetary policy, investors are also watching the federal government’s borrowing needs. Elevated fiscal deficits require continued heavy issuance of Treasury securities, particularly at the long end of the curve. Increased supply can exert upward pressure on yields if demand does not keep pace.

Foreign demand for Treasuries, particularly from major holders such as Japan and China, is another factor influencing long-term yield stability. Any shifts in global reserve allocation or currency-hedging costs can affect cross-border flows into U.S. debt.

With the bond market closed on Monday and economic data compressed into the latter half of the week, trading volumes on Tuesday were subdued. However, analysts caution that volatility could rise sharply following Wednesday’s FOMC minutes and Friday’s PCE release.

For now, the Treasury market appears to be in a holding pattern, balancing expectations of eventual policy easing against persistent inflation risks and heavy government borrowing, awaiting clearer signals from incoming data and Federal Reserve communications.

Amazon Rebounds After Historic Slide as $200 Billion AI Bet Faces Market Scrutiny

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Amazon’s plan to spend $200 billion in capital expenditures this year—nearly 60% higher than last year—has placed it at the center of investor concerns about AI-driven free cash flow compression.


A modest rally in Amazon shares on Tuesday ended one of the stock’s most severe losing streaks in nearly two decades, but it did little to resolve mounting investor unease over the company’s aggressive artificial intelligence spending plans.

The stock closed up more than 1%, snapping a nine-day slide that erased roughly 18% of its value between Feb. 2 and Friday — the longest stretch of consecutive losses since 2006. The decline wiped out more than $450 billion in market capitalization, underscoring how quickly sentiment has shifted around Big Tech’s AI capital expenditure cycle.

The selling pressure followed Amazon’s fourth-quarter earnings report, where management projected $200 billion in capital expenditures for the year. The figure is nearly 60% above last year’s spending and more than $50 billion higher than Wall Street had anticipated.

The bulk of the investment will go toward AI infrastructure — including data centers, custom chips, and networking hardware — to support generative AI services and cloud workloads within Amazon Web Services (AWS).

The size of the increase signals a decisive shift into infrastructure acceleration mode. It also aligns Amazon with peers including Alphabet, Microsoft, and Meta, whose combined capital expenditures could reach $700 billion this year as they race to expand AI capacity.

However, investors are increasingly focused on capital intensity. Large-scale infrastructure buildouts carry long payback periods and can suppress free cash flow in the near term. Markets that previously rewarded AI ambition are now demanding clearer evidence of monetization.

Alphabet and Microsoft shares fell more than 1% on Tuesday, each marking a fifth straight negative session. Meta edged slightly lower, reinforcing the broader rotation away from AI-heavy spending narratives.

AWS: Growth Engine or Margin Risk?

At the center of the debate is AWS, Amazon’s most profitable segment and a key driver of overall operating income.

Chief Executive Officer Andy Jassy defended the spending, telling analysts the investments will “yield strong returns on invested capital.” His thesis rests on the expectation that AI workloads will materially expand cloud demand, driving revenue growth and long-term margin expansion once scale efficiencies are realized.

Matt Garman, head of AWS, told CNBC that the capex increase positions Amazon to seize AI opportunities in the cloud. Management has also indicated that Amazon expects to double data center capacity by 2027 — a move that, if matched by demand growth, could accelerate AWS revenue meaningfully.

Andrew Boone of Citizens described that expansion target as an “underappreciated” catalyst, suggesting capacity additions may drive a reacceleration in AWS growth once deployed.

Still, analysts caution that investors will need tangible proof. Wedbush characterized Amazon as being in “prove it mode,” noting that elevated spending will remain an overhang until measurable returns become visible in revenue growth and cash generation metrics.

Valuation, Cash Flow, and Competitive Dynamics

The magnitude of Amazon’s capex has intensified debate over valuation discipline. Free cash flow is a core pillar of tech stock valuation models. If capex rises faster than operating cash flow, free cash flow can narrow or even turn negative, compressing valuation multiples.

The competitive environment adds its own challenge. With Alphabet, Microsoft, and Meta simultaneously expanding infrastructure, industry-wide supply growth could temporarily outpace demand, pressuring pricing power in certain AI services.

On the other hand, underinvestment carries strategic risk. AI models require immense computing resources, and insufficient capacity could constrain customer growth or shift workloads to competitors.

The calculus for Amazon is to invest heavily now to secure long-term dominance in AI-enabled cloud computing, even at the cost of short-term margin pressure.

Market Psychology and the AI Cycle

The recent sell-off reflects a broader shift in market psychology. In 2024 and early 2025, investors largely rewarded AI-related announcements. By early 2026, attention had turned to capital efficiency and return on invested capital.

The nine-day slide — the worst since 2006 — suggests the market is recalibrating expectations. Rather than questioning AI’s long-term potential, investors appear to be scrutinizing execution timelines and cost structures.

Tuesday’s rebound may signal technical stabilization rather than a full sentiment reversal. The durability of the recovery will likely hinge on forthcoming data: AWS revenue growth, AI service adoption rates, and free cash flow trajectory in subsequent quarters.

However, Amazon’s $200 billion spending plan places it at a pivotal moment. If AI adoption accelerates and AWS revenue scales with new capacity, the company could emerge with reinforced competitive leadership and expanded profit pools.

If returns are slower to materialize, margin compression and valuation pressure could persist, especially in an environment where investors are increasingly sensitive to capital discipline.

Adani Group Commits $100bn to Build World’s Largest AI-Ready Data Center Platform by 2035, Signaling India’s Ambitious AI Infrastructure Leap

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Adani Group announced on Tuesday that it plans to invest $100 billion over the next decade to develop renewable energy-powered, AI-ready data centers, aiming to create the world’s largest integrated data center platform and establish India as a major global player in artificial intelligence infrastructure.

Chairman Gautam Adani described the initiative as a cornerstone of India’s participation in what he called “the Intelligence Revolution — more profound than any previous Industrial Revolution.” The company stated that the $100 billion investment would generate a $250 billion AI infrastructure ecosystem in India by 2035, while catalyzing an additional $150 billion in spending across server manufacturing, sovereign cloud platforms, and supporting industries.

The announcement aligns with India’s broader push to become a significant AI hub in the Global South. It coincides with the ongoing AI Impact Summit in New Delhi (February 16–20, 2026), India’s first major international AI conference, featuring global leaders such as OpenAI CEO Sam Altman and Alphabet CEO Sundar Pichai.

Key Elements of the Adani Plan. Adani’s vision builds on AdaniConnex — its joint venture with U.S.-based data center operator EdgeConnex — which currently operates 2 gigawatts (GW) of national data center capacity. The company aims to scale this to 5 GW as part of the broader $100 billion program. All facilities will be powered by renewable energy, leveraging Adani Green Energy’s massive solar and wind portfolio to meet the enormous power demands of AI data centers.

The plan includes large-scale campuses across India, with strategic partnerships already in place. Google (Alphabet) announced in October 2025 a $15 billion investment over five years to build an AI data center hub in southern India, and Adani said it is in talks with other major global players to establish additional facilities. While specific names were not disclosed, the scale suggests potential involvement from hyperscalers seeking low-cost, renewable-powered capacity in Asia.

Market Reaction and Stock Performance

Adani Enterprises, the flagship listed entity of the Adani Group, rose 2.3% on the news, making it one of the top gainers on the benchmark Nifty 50 index. Adani Green Energy shares gained 1.8%. The positive response underlines investor enthusiasm for Adani’s pivot toward high-growth AI infrastructure, which complements its existing strengths in ports, airports, energy, and renewables.

However, Adani stocks remain volatile. Late last month, U.S. Securities and Exchange Commission (SEC) court filings revealed efforts to serve summons on Gautam Adani and nephew Sagar Adani in connection with a November 2024 New York federal indictment alleging bribery and fraud in a massive scheme involving solar energy contracts. India’s Ministry of Law and Justice twice refused to deliver the summons under the Hague Convention in 2025, complicating the case.

India’s Rising AI Role

India’s AI ambitions are accelerating rapidly. The government has set targets to become a global AI powerhouse, with initiatives like the IndiaAI Mission (?10,300 crore allocation) and plans for sovereign cloud infrastructure. But data centers are a critical bottleneck: India’s current capacity is around 1 GW, but demand from hyperscalers, domestic tech firms, and AI startups is expected to grow exponentially as the country aims for 10% of global AI compute share by 2030.

Adani’s $100 billion commitment, if fully realized, would dwarf current capacity and position India as a major alternative to traditional hubs like the U.S., Singapore, and Europe. The renewable energy focus addresses both sustainability concerns and the massive power requirements of AI workloads (a single large data center can consume as much electricity as a small city). The plan also aligns with India’s “Make in India” and “Atmanirbhar Bharat” (self-reliant India) initiatives, aiming to build domestic server manufacturing, cooling systems, and ancillary industries.

The projected $150 billion in ecosystem spending would create thousands of jobs and stimulate manufacturing in semiconductors, power electronics, and data center hardware.

The Challenges Ahead

Building 5 GW of AI-ready, renewable-powered data center capacity requires massive capital, land, power infrastructure, and regulatory approvals. India’s power grid faces constraints, and renewable integration at this scale will demand significant investment in transmission and storage.

Also, the ongoing U.S. SEC case and bribery allegations create reputational risk, even if they remain unresolved. Competition is fierce: global hyperscalers (Google, Microsoft, AWS, Meta) are expanding in India, while domestic players like Reliance Jio and Tata Communications are building large-scale data centers.

In addition, Adani Group’s aggressive expansion across ports, airports, energy, and now AI infrastructure has drawn scrutiny over debt levels and governance. The group’s ability to deliver on the $100 billion pledge while maintaining financial discipline will be closely watched.

However, the announcement reinforces India’s growing role in global AI infrastructure. With the U.S. facing power constraints in traditional data center hubs and Europe grappling with energy costs, India’s low-cost renewable energy, large talent pool, and government support make it an attractive destination.

The AI Impact Summit provides a high-profile platform for Adani to showcase the plan to global leaders. Participation from Altman, Pichai, and other executives underscores India’s rising relevance in the AI ecosystem. For investors, the news strengthens the case for Adani Group stocks as a proxy for India’s infrastructure and AI growth story. Adani Enterprises and Adani Green Energy have been volatile but resilient, reflecting confidence in Gautam Adani’s execution ability despite legal and geopolitical challenges.

Analysts expect India’s positioning as a creator and exporter of intelligence, not just a consumer, to buoy Adani’s $100 billion bet to become one of the defining infrastructure plays of the decade. Success would accelerate India’s AI ambitions, create a massive domestic ecosystem, and challenge established data center hubs worldwide.

Infosys Says AI Accounted For 5.5% Of Its Revenue In The December Quarter,

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India’s second-largest software services exporter, Infosys, said on Tuesday that artificial intelligence services accounted for 5.5% of its revenue in the December quarter, the first time the company has formally disclosed the contribution of its AI business.

The disclosure comes at a sensitive moment for India’s $283 billion IT services industry, which is confronting mounting investor concern that generative AI and autonomous systems could reshape — or erode — its traditional labor-intensive outsourcing model.

Infosys posted third-quarter revenue of 454.79 billion rupees ($5.01 billion), meaning AI-related work is now a measurable and growing revenue stream within the company’s portfolio.

Chief Executive Salil Parekh said the AI segment is “growing at a robust pace,” adding that its offerings include autonomous agents and embedded AI systems designed for physical devices and hardware environments. Parekh has previously stated that Infosys is working on 4,600 AI projects and has developed more than 500 AI agents.

Industry Under Pressure from AI Acceleration

The timing of the revenue breakout is of importance. Indian IT stocks have suffered their worst weekly decline in more than 10 months, amid fears that rapid advances in generative AI, particularly tools from companies such as Anthropic, could compress demand for traditional application maintenance, coding, and back-office services.

The recent sell-off has erased roughly $40 billion from the sector’s market capitalization so far in February, reflecting anxiety that automation could reduce billable headcount — the backbone of India’s outsourcing model for decades.

The core business model of Indian IT majors has historically depended on scale: deploying large pools of engineers to manage enterprise systems, modernize legacy infrastructure, and provide long-term support services. AI-driven automation threatens to alter pricing dynamics by reducing manual effort and accelerating software development cycles.

By quantifying AI revenue, Infosys appears to be signaling that it is not merely exposed to disruption but actively participating in the shift.

Competitive Positioning: Infosys vs. Peers

Infosys’ AI revenue share of 5.5% places it broadly in line with larger rival Tata Consultancy Services, which has said its AI services generate approximately $1.8 billion annually, or around 5.8% of total revenue.

The figures suggest that while AI remains a minority contributor today, it is no longer peripheral. For investors, the key question is not only how fast AI revenue grows, but whether it can offset potential declines in legacy service lines.

Margin dynamics will also be closely watched. AI projects often command higher value-add but can require significant upfront investment in platforms, training, and partnerships.

Infosys on Tuesday also announced a collaboration with Anthropic to establish a dedicated center focused on building and deploying AI agents. The initiative will begin in the telecom sector before expanding into financial services, manufacturing, and software development.

The emphasis on “agents”, AI systems capable of autonomous task execution, reflects a broader industry pivot from chatbot-style interfaces toward workflow automation and decision-support systems embedded within enterprise environments.

By aligning with a frontier AI lab such as Anthropic, Infosys is positioning itself as an integrator of advanced models into enterprise-grade solutions, rather than attempting to build foundational models in-house.

Structural Implications for India’s IT Model

The evolution toward AI-led services raises deeper structural questions for India’s technology sector.

If AI tools significantly reduce coding and maintenance hours, traditional pricing structures based on effort and staffing may face compression. Companies will need to shift toward outcome-based pricing, platform-driven services, and domain-specific AI solutions.

At the same time, India’s large engineering talent pool and long-standing global client relationships could prove advantageous in the AI transition. Rather than displacing Indian IT firms, AI may accelerate their move up the value chain — from labor arbitrage to AI-enabled digital transformation.

Infosys’ announcement comes as India hosts the AI Impact Summit in New Delhi from February 16–20, highlighting the country’s ambition to play a larger role in shaping global AI development and deployment.

The summit underscores a broader narrative: India is not only a consumer of AI technologies but increasingly a deployment hub, systems integrator, and engineering center for global enterprises adopting AI at scale.

For Infosys and its peers, the coming quarters will test whether AI becomes a margin-enhancing growth engine — or a disruptive force that compels painful restructuring. However, the 5.5% figure, modest on the surface, signals that the transition is already underway.

When Dividends Dominate: Rethinking Nigeria’s Equity Market for the Next Generation of Companies

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Nigeria’s equity market is becoming increasingly concentrated in a relatively small group of heavyweight stocks. As of February 16, 2026, twenty six listed companies had crossed the N1 trillion market capitalization threshold, with a combined value of about N110.54 trillion.

Out of a total market capitalization of N122.13 trillion, this select group now represents roughly 85.5% of the entire market, an unusually high level of concentration. This underscores how overall exchange performance is now closely tied to the fortunes of a handful of blue-chip companies.

The banking sector has been the single most important driver of the SWOOT (stocks worth over one trillion naira) expansion. Fidelity Bank Plc, Wema Bank Plc, Ecobank Transnational Incorporated, and Dangote Sugar Refinery Plc all crossed the N1 trillion threshold this year.

Fidelity Bank’s valuation climbed to about N1.07 trillion after its share price rose to N21.30. Wema Bank surged 34.6% year to date, lifting its market capitalization to roughly N1.1 trillion. Ecobank Transnational Incorporated joined the league at about N1.04 trillion despite a recent moderation in its share price.

One reason for this dynamic is the market’s strong preference for dividend-paying stocks. Companies that consistently deliver attractive dividends tend to rise quickly in prominence because many investors approach the equity market almost like a fixed-income environment, focusing on income rather than long-term share price appreciation. While this model has rewarded banks and established industrial firms, it also narrows the pathway for emerging sectors to attract capital.

If Nigeria is to cultivate new categories of market leaders, the investment thesis must broaden. Under today’s logic, a company like US-based Amazon, unprofitable at IPO and not positioned to pay dividends, might have struggled to list or gain traction locally. To enable fintechs, logistics firms, and other innovation-driven businesses to scale into SWOOT (stocks worth over one trillion naira)-class companies, the market must evolve to value growth, reinvestment, and long-horizon innovation alongside dividends.