S&P 500 and Nasdaq Hit Record Highs: Can the AI Rally Continue Into Earnings Season?

Wall Street has reached another record, but the more interesting development is happening beneath the share prices: profit expectations are rising too. The S&P 500 and Nasdaq Composite closed at all-time highs on October 6 as investors looked ahead to earnings season. My assessment is that the AI rally has a credible earnings foundation, although its next advance will depend on companies turning infrastructure spending into durable profits and cash.

Let's break down what powered the records, what earnings forecasts already assume and how valuations could change the outcome. We will also examine the Fed risk and what this means for Indian investors following US markets.

Why did the S&P 500 and Nasdaq reach record highs?

The latest rally had more than one engine. AI enthusiasm supported stocks while easing Treasury yields and steadier crude prices offered relief from the interest-rate and inflation concerns that had troubled markets. The approaching reporting season gave investors another reason to focus on company profits.

Marvell’s higher revenue outlook and AMD’s plan to increase chip supply added company-specific support to AI optimism. Both are forward-looking signals that still need to become reported results.

The contrast with the Russell 2000 matters. A record in a major index can coexist with weakness elsewhere, so the headline does not establish that every part of the US market is improving.

Sources: Associated Press, “How major US stock indexes fared Tuesday 10/6/2026”; The Wall Street Journal, “U.S. Stocks Rise as AI Momentum Builds”; Yahoo Finance historical S&P 500 data. 

The S&P 500 gives larger companies more influence through its weighting by the market value of publicly available shares. That means a strong move in a few large businesses can lift the index even when many smaller constituents struggle.

There is a second distinction worth making: the record above belongs to the Nasdaq Composite. The Nasdaq-100 is a different index, built around the largest eligible non-financial Nasdaq-listed companies. A fund tracking one should not be assessed using the other’s headline level.

Tuesday’s trading offered both encouragement and caution. Reuters reported gains in ten of the S&P 500’s eleven sectors, with utilities leading. Across Nasdaq-listed stocks, however, advancing shares only narrowly outnumbered declining shares, by about 1.01 to one.

That is a useful way to read the rally: sector participation improved during the session, but the Nasdaq record was stronger than the performance of the average listed stock. One good day also cannot establish a lasting change in market breadth, which simply means how widely stocks participate in an advance.

What does Wall Street expect from Q3 earnings season?

The strongest argument supporting the records is that analysts expect a substantial increase in profits. The exact forecast depends on the provider and the date, so different estimates should remain separate rather than being presented as one supposedly precise consensus.

These are forecasts for the July-to-September quarter, not the final reported result. Their shared message is strong expected earnings growth, while their differences reflect separate estimate sets and observation dates.

Sources: FactSet, “S&P 500 Earnings Season Preview: Q3 2026”; Reuters, “S&P 500, Nasdaq reach record closing highs as focus pivots to earnings”; Financial Times, “Robust AI spending sets investors up for another bumper US earnings season.”

FactSet also projected revenue growth of 12.3% and said analysts raised the quarter’s per-share earnings estimates by 1.4% between June 30 and September 30. That combination is more useful than a profit forecast alone: it suggests stronger expected sales alongside improving profit expectations.

However, AI should not receive credit for every dollar of that growth. Reuters’ LSEG breakdown identified energy as the strongest expected earnings-growth sector, followed by technology. An index combines businesses with different drivers, including commodity prices, financing conditions and consumer demand.

The financial question is therefore more demanding than whether companies report a good quarter. Results need to support the expectations already embedded in share prices and management needs to explain why growth can continue beyond this reporting period.

Imagine a company that reports strong profit growth but reduces its outlook because customers are delaying projects. Its historical result could look impressive while the stock falls. Markets price the expected future, so a backward-looking earnings beat is only part of the evidence.

This is why earnings season could support another advance even after records, but it could also expose disappointment. The relevant comparison is actual performance against current expectations, followed by the direction of future forecasts.

Do the latest AI company results support the rally?

There is already substantial reported business activity behind the AI investment cycle. Chip suppliers are recording sales, cloud providers are collecting revenue and infrastructure companies are securing long-term commitments. These are different stages of the same commercial chain, however, rather than interchangeable evidence of profitability.

These periods have different end dates, so the table is evidence of the investment cycle rather than a comparison of identical quarters. AMD’s Data Center segment includes CPUs and GPUs, while Microsoft’s cloud figures include services beyond AI. Neither should be described as pure AI revenue.

Sources: Nvidia’s Q2 FY2027 earnings release, 26 August 2026; AMD’s Q2 2026 earnings release, 4 August 2026; Microsoft’s Q4 FY2026 earnings release, 29 July 2026.

The next distinction is who receives the money and who needs to earn a return on spending it. A cloud company’s purchase of computing equipment becomes business for a supplier. That transaction does not by itself establish that the cloud company’s eventual customers will spend enough to justify the investment.

Microsoft provides a useful example of how to examine both sides. In its June-quarter earnings call, the company reported capital expenditure of $41 billion, including finance leases. It separately reported operating cash flow of $55.4 billion and cash paid for property and equipment of $35.8 billion.

The cash calculation is $55.4 billion minus $35.8 billion, producing $19.6 billion. Subtracting the broader $41 billion capital-expenditure figure would mix cash payments with lease-related additions and give the wrong free-cash-flow calculation.

Positive free cash flow shows that Microsoft’s overall business remained cash-generative despite heavy investment. It does not isolate the return on its newest AI assets. That requires evidence about revenue, customer usage, operating costs and the useful life of the equipment.

This is the article’s central test: follow spending through to the customer who ultimately pays. Supplier revenue confirms that infrastructure is being built. Sustained usage and cash generation help establish whether that infrastructure is economically productive.

The latest Google - Constellation announcement extends this chain to electricity. On October 6, the companies announced a long-term agreement supporting additional output from existing nuclear units rather than the construction of a completely new nuclear plant.

The agreement demonstrates a commitment to future electricity supply, but the capacity has not already arrived. Its timetable also shows why power availability can constrain the pace of infrastructure deployment.

Source: Constellation and Google’s joint announcement, 6 October 2026.

This broadens the potential beneficiaries of AI beyond semiconductor companies. It also introduces a subtle risk: owning chips, cloud platforms and AI-linked power companies can still leave a portfolio dependent on the same spending cycle. Different sector labels do not necessarily mean different sources of demand.

Are record stock prices supported by valuations?

A higher index level does not automatically mean investors are paying more for each dollar of earnings. The price-to-earnings ratio (P/E) measures that relationship. A forward P/E uses estimated earnings for the next twelve months rather than profits already reported.

The snapshot was published on October 2 and predates the October 6 record. It should not be relabelled as the record-day valuation. On its stated basis, the market traded below its five-year average and close to its ten-year average.

Source: FactSet, “S&P 500 Earnings Season Preview: Q3 2026,” published 2 October 2026.

That challenges the assumption that a record index must be historically expensive. It also leaves a major qualification: the earnings denominator is a forecast. If analysts overestimate future profits, the apparent valuation support can weaken without any initial change in prices.

An index average also cannot settle the valuation of an individual AI stock. Some companies may carry demanding growth expectations while others trade at lower multiples. The S&P 500’s P/E should not be applied to the Nasdaq Composite, the Nasdaq-100 or a semiconductor company.

To understand the next move, separate earnings growth from the multiple investors are willing to pay. In a simplified model, price equals earnings per share multiplied by P/E. A rising profit figure can be partly offset by a falling valuation multiple.

The following scenarios use a hypothetical starting P/E of 19 times as a convenient reference near the dated FactSet snapshot. They are not index targets, earnings forecasts or estimates of the precise October 6 valuation.

The middle calculation is (1.15 × 17.5 ÷ 19) − 1 = approximately 5.9%. The downside case shows that profits can rise while prices fall if investors reduce the multiple sufficiently.

My reading is that the rally has a more credible valuation foundation than the record headline alone implies. Further gains would be better supported by sustained earnings upgrades than by assuming investors will indefinitely pay higher multiples. The strongest outcome is improving profits accompanied by evidence that those profits can persist.

How could the Fed and bond yields affect the AI rally?

Company results will not arrive in isolation. Interest rates affect borrowing costs and the value investors assign to future cash flows. When safer assets offer more attractive yields, equities may need stronger earnings growth or lower prices to remain competitive.

The Federal Reserve raised its policy-rate target range in September. Its October 7 minutes are the next scheduled opportunity to examine the discussion behind that decision.

The minutes describe a meeting that has already occurred; they are not a new rate decision. Their price impact depends on whether they reveal information that differs from investors’ expectations.

Sources: Federal Reserve statement dated 16 September 2026; Federal Reserve October 2026 calendar and FOMC meeting calendar. The IST time is converted from Eastern daylight time. Premarket context: Associated Press reporting on US futures, oil prices and bond yields on 7 October 2026.

If the discussion suggests more persistent inflation concerns than expected, Treasury yields could rise and put pressure on equity multiples. A more restrained policy outlook could provide relief, although neither reaction is automatic because markets also respond to new economic information.

There was already a reminder of this sensitivity on October 7. AP’s premarket reporting described lower US stock futures alongside rising oil prices and bond yields. Those moves did not undo the previous session’s closing records, but they showed that earnings optimism had not removed macroeconomic risk.

For companies building infrastructure, higher financing costs can also influence project economics. Power facilities and data centres require substantial upfront investment, so the same expected revenue can produce a less attractive return when funding becomes more expensive.

AI demand and interest rates can therefore pull valuations in opposite directions. Strong results may support earnings estimates while higher yields reduce the multiple investors will pay for them. That is precisely the trade-off illustrated in the valuation scenarios.

What should investors watch during earnings season?

The useful evidence will extend beyond whether a company beats a headline estimate. The next stage of the rally needs clarity about future revenue, profitability and cash commitments. Companies announcing more spending will also need to explain the demand and economics behind it.

Two confirmed reporting dates provide different perspectives on the US market. JPMorganChase offers a view beyond the AI supply chain, while Alphabet can help connect cloud demand with infrastructure investment.

These are selected confirmed events rather than a complete earnings calendar. The financial measures in the last column are the author’s monitoring framework, not forecasts of what the companies will report.

Sources: JPMorganChase investor-relations event calendar; Alphabet investor-relations Q3 2026 event page.

For chip companies, the central question is whether demand is becoming profitable shipments. Strong orders are encouraging, but delivery schedules, supply constraints and customer concentration affect when those orders become revenue. Margins then show how much of that revenue becomes operating profit.

For cloud platforms, revenue growth needs to be assessed alongside cash spending and the cost of operating the new capacity. More infrastructure can support sales, but it also brings depreciation, electricity costs and maintenance requirements. Faster revenue growth does not guarantee that returns on incremental investment are improving.

For the wider market, the test is whether earnings strength extends beyond businesses linked to the same infrastructure budgets. Banks, consumer companies and industrial businesses can help establish whether the economy supports a broader profit cycle. A durable improvement in equal-weight index performance would offer complementary price evidence.

My assessment would strengthen if companies deliver healthy underlying profits, raise forward expectations and demonstrate cash generation while participation improves. It would weaken if capital-spending announcements keep growing but customer monetisation, margins or cash flow fall behind. A series of earnings beats accompanied by weaker guidance would also challenge the case for further records.

What does the US AI rally mean for Indian investors?

For Indian investors, US markets offer exposure to overseas chip and cloud businesses with different economics from domestic technology services. That can broaden business exposure, but the growth of one does not automatically establish the earnings outlook of the other. Each company still needs to be assessed on its customers, profitability and valuation.

The currency translation is a separate part of the result. A dollar-denominated investment can have a different return when measured in rupees, even if the underlying stock or fund delivers exactly the same US-dollar performance.

There is also potential overlap between an S&P 500 fund, a Nasdaq-100 fund and individual AI stocks. Several holdings may depend on the same large companies or cloud-infrastructure budgets. Counting securities alone can therefore overstate the range of economic exposures in a portfolio.

Global companies outside the US can participate in the investment chain through manufacturing, memory, equipment and infrastructure. The economic benefit depends on their actual role and pricing power, however, rather than simply being associated with AI. The same principle applies to Indian businesses seeking work from global technology spending.

The record-high story remains constructive, but it is entering a more demanding phase. There is substantial reported revenue behind AI and a strong expected earnings season ahead. Continued gains are plausible if those expectations become durable profits and cash flows; weaker guidance or renewed pressure from rates could interrupt the advance even while AI adoption continues.