Wall Street Bulls Admit Tech Earnings Bubble as 60/40 Strategy Crumbles

Wall Street’s most reliable optimists just delivered a sobering assessment. The 60/40 portfolio. Long the bedrock of balanced investing. Now stands accused of fundamental failure. On the same August day this week, two heavyweights from opposing corners of finance reached parallel conclusions. One from the equity side. One from the macro view. Their combined message carries weight because neither has built a career on bearish calls.

Goldman Sachs chief global equity strategist Peter Oppenheimer authored a note conceding a point few bulls have voiced aloud. “There does not appear to be a valuation bubble, but there may be an earnings bubble” in the technology sector, he wrote, according to Fortune. The same day Apollo chief economist Torsten Slok declared the verdict in blunt terms. “The 60/40 portfolio is broken.”

Slok’s note, published on Apollo’s site, lays out the mechanics with clinical precision. “The 60/40 portfolio is broken because equity returns are driven by AI concentration rather than the business cycle, while bond returns are now driven by fiscal constraints rather than cycle dynamics.” Government debt projected to reach 175% of GDP only accelerates the shift. “Neither the 60 nor the 40 responds to what made it work in the first place.” The bottom line? The portfolio has lost its diversification benefit. Real risk surfaces if the AI trade reverses or deficits spark deeper concern. Stocks and bonds would then fall together. No hedge remains.

And yet the warning arrives against a backdrop of resilient markets. The equal-weighted S&P 500 has outperformed the cap-weighted version by more than 7.3% for the first time since 2009, Oppenheimer’s team observed in the same report. Market participation has broadened. Momentum from the largest names has unwound sharply. A healthy normalization, Goldman calls it, after years of extreme concentration in both capitalization and returns.

But normalization carries costs. Hyperscalers, those few companies pouring hundreds of billions into AI infrastructure, have seen their premium cash flows erode. Capital expenditure has surged. Debt and equity issuance have followed. Microsoft’s forward price-to-earnings ratio has already compressed from an AI-era peak of 35 times to 22.5 times today, data cited in JPMorgan’s mid-year outlook document shows. Aggregate free cash flow for the group, which peaked near $240 billion in 2024, heads toward $73 billion by the end of 2026. Free cash flow yield slips below 4% from 18% in 2023. The numbers tell a story of investment intensity that markets once rewarded but now question.

Slok has warned of higher rates for longer since at least 2023. His latest analysis ties the knot tighter. Sticky inflation lifts front-end yields. Hyperscaler borrowing pressures the middle of the curve. Treasury supply and reduced Federal Reserve buying push long rates higher. Fiscal dominance now dictates bond behavior. The classic negative correlation between stocks and bonds that powered 60/40 success for decades has broken down.

Oppenheimer reaches the diagnosis from the equity vantage. “More government debt, increased issuance, and persistent inflation have all contributed to a higher cost of capital, leaving earnings as the key driver of returns,” he wrote. “We think this trend will continue.” The 10-year rolling earnings growth rate in technology has accelerated past the 2000 peaks, his data indicates. Forward-implied growth has climbed since 2020. Earnings, in other words, must keep delivering. Valuation discipline offers little cover if growth falters.

Outside the big-bank consensus, voices had sounded alarms months earlier. Acadian Asset Management’s Owen Lamont flagged that expected long-term S&P 500 earnings growth reached 20.2%, topping the 18.6% high seen in 2000. “Today’s optimism… yet another way in which 2026 is looking like 1999,” he said in June, per Fortune. JPMorgan CEO Jamie Dimon captured the mood at a Bernstein conference. “It’s gung-ho, folks… There’s a lot of exuberance out there.” He traced $10 trillion to $12 trillion in deficit spending that had artificially lifted corporate profits. A sugar high mistaken for structural strength.

Ray Dalio went further still. His bubble gauges showed equity markets climbing close to levels last seen in 2000 and 1929. Economist Steve Hanke distinguished the problem. Valuation metrics might not scream danger. The deeper mispricing sits inside the earnings themselves. BCA Research’s Peter Berezin joined the chorus, calling the AI surge “primarily an earnings bubble rather than a valuation bubble.”

July’s earnings season brought the tension into sharp relief. IBM’s 25% single-day collapse erased $40 billion after a modest revenue miss. Microsoft, by contrast, surged 17% in one session, adding nearly $500 billion in market value. Its largest daily move since 2008. Such volatility underscores the narrow base on which recent gains have rested. The Magnificent Seven, once unified in momentum, now show dispersion. Apple’s year-to-date gain leads the group at 25%, outpacing the S&P 500, while others lag, a Reuters analysis from late July noted.

Capex plans continue to climb. The five major hyperscalers lifted 2026 capital expenditure guidance by $130 billion after recent results. Wall Street now models more than $650 billion in combined spending through the end of 2026, largely aimed at cloud AI capacity. Oracle reported a $30 billion jump in its order book. GPU rental rates have risen 40% since October. Yet investors remain skeptical. Semiconductor stocks trade at price-to-earnings multiples that imply the data-center investment cycle may have already crested, according to the JPMorgan mid-year outlook. Private markets still bid aggressively for stakes in AI leaders. Public markets punish the builders.

This divergence creates opportunity and hazard. A continuing AI cycle could drive productivity higher, expand margins, and support valuations. S&P 500 margins, which hit 13.3% in late 2025, could climb toward 15.5% by 2027 if adoption accelerates. Productivity growth already runs near 3% year-over-year, above the five-year average. Historical precedent from the 1990s shows forecasts often undershoot the eventual gains. Higher productivity might ease inflation, permit lower rates, and stabilize debt-to-GDP ratios over time.

But the JPMorgan report also flags risks. Volatile inflation could pressure both stocks and bonds in a 60/40 mix. Correlations between the asset classes appear structurally higher in the post-pandemic era. Rolling economic shocks may define the decade. Cash holdings erode purchasing power. Traditional portfolios require stress-testing against scenarios once considered remote.

Portfolio construction must therefore evolve. Some allocators eye core-satellite structures that incorporate alternatives as anchors. Others tilt toward sectors benefiting from data-center expansion, energy infrastructure, or private-market exposure in robotics and physical AI. Hyperscalers themselves trade at discounts in certain metrics. Enterprise value to EBITDA for names like Microsoft has fallen to levels not seen since 2018 even as earnings power has multiplied.

The equal-weighted outperformance hints at rotation. Broader market participation, pickup in mergers, and a less concentrated leadership group could sustain gains even if mega-cap growth moderates. Yet the structural forces Slok identifies will not vanish quickly. Fiscal trajectories point higher. AI investment intensity shows little sign of immediate retreat. Earnings quality questions linger when free-cash-flow generation decouples from reported profits.

Investors who clung to the 60/40 through the inflation surge of 2022 have already endured one painful lesson. The strategy’s worst year on record came in 2022 when both stocks and bonds declined sharply. Recovery followed as rates peaked and growth proved resilient. This time the challenge runs deeper. The regime itself has changed. Business-cycle dynamics no longer steer the primary assets in the classic mix. Concentration risk in equities meets fiscal dominance in fixed income.

Slok’s conclusion leaves little room for nostalgia. The real danger materializes when either the AI narrative cracks or deficit fears intensify. Simultaneous pressure on both legs of the stool would expose portfolios built on outdated assumptions. Adaptation demands more than incremental tweaks. It requires fresh thinking about what constitutes balance when old relationships no longer hold.

Recent market action reinforces the point. Dispersion within technology has widened. Rotation toward smaller names and other sectors has gathered momentum. Whether this broadening proves sustainable or simply a pause before renewed concentration remains the central debate. Goldman’s data suggests the former. History and the scale of fiscal and technological forces suggest caution.

Portfolio managers face hard choices. Maintain the traditional split and accept higher volatility without the former diversification cushion. Or reconstruct allocations with an eye toward inflation resilience, alternative return streams, and selective exposure to AI beneficiaries trading at reasonable multiples. The earnings bubble, if it exists, need not burst dramatically. It can deflate gradually as growth normalizes and capital costs stay elevated. That slow grind may prove more corrosive to conventional strategies than any single crash.

One thing seems clear. The era when 60% stocks and 40% bonds delivered reliable risk-adjusted returns with minimal thought has ended. Wall Street’s bulls have said so out loud. The rest of the investment community must now decide how quickly to adjust.