Entering August 2026, the US stock market faces a critical earnings season verification period. Over the past two years, the rapid rise of generative AI has reshaped the global tech landscape and driven a valuation re-rating of core US tech giants. However, as the S&P 500 and Nasdaq Composite show signs of heightened volatility at high levels, investor focus is shifting from a pure "computing power arms race" to the actual financial returns of AI commercialization. In this race between capex and profit realization, US asset allocation faces unprecedented complexity and opportunity. Constructing a robust portfolio during tech stocks' high-volatility period is a core proposition all market participants must face.

AI Capex Enters the "Deep Water Zone": A Rigorous Test from Narrative to Performance

Looking back at the US market in 2024-2025, the AI narrative was the undisputed main theme. The "Magnificent Seven" enjoyed massive valuation premiums through huge investments in computing infrastructure and large model R&D. But by mid-2026, market sentiment is shifting subtly. Per research institutions, earnings expectations for tech giants are maxed out this earnings season. Any signal of lower-than-expected capex conversion or slowing cloud growth could trigger a drastic valuation model re-rating.

The logic behind this shift is straightforward. In early AI development, markets paid high premiums for "long-term options" since computing bottlenecks were the core constraint on tech deployment. Now, with chipmakers like Nvidia delivering iterations, the computing supply gap is narrowing. The market asks: what real revenue increments can these multi-billion-dollar GPU orders generate for customers? If killer AI apps fail to achieve mass adoption, tech giants' high depreciation costs will severely drag down future free cash flows.

Therefore, current US asset allocation logic must shift from "beta-driven valuation expansion" to "alpha-driven profit verification." For investors, relying solely on a one-sided tech stock rally for asset growth faces extremely high drawdown risks. Portfolio defensiveness and volatility resistance have been elevated to unprecedented heights.

Barbell Strategy: Finding Balance Between Growth and Defense

Facing tech stock earnings uncertainty, adopting the Barbell Strategy is a highly practical asset allocation approach. Its core involves concentrating funds at both ends: high-risk, high-elasticity growth assets on one side, and low-risk, stable-cash-flow defensive assets on the other, avoiding mediocre middle-ground assets.

In specific US stock holdings, one end can retain positions in core AI computing and infrastructure leaders. Despite short-term capex verification pressures, these firms have deep moats and strong balance sheets, making them the highest-certainty beneficiaries of the AI wave. The other end should increase allocations to defensive sectors with strong free cash flow, low capex, and reasonable valuations, such as utilities, consumer staples, and certain healthcare giants.

This allocation's advantage: when AI earnings beat expectations, the growth end captures upside gains; when AI capex is questioned and sentiment falls, defensive assets provide stable dividends to hedge drawdowns and offer capital gains in rate-cut cycles. Through this asymmetric asset matching, investors can smooth portfolio NAV curves without sacrificing long-term return expectations.

Dynamic Asset Allocation and Stock-Bond Balancing: Weapons Against Macro Uncertainty

Beyond internal equity adjustments, cross-asset dynamic asset allocation is indispensable. In H2 2026, the macro environment remains complex. While the US economy shows resilience, some forward-looking indicators suggest slowing growth; meanwhile, the Fed's monetary policy path remains uncertain amid inflation-employment trade-offs. This "data-dependent" macro environment easily triggers seesaw effects between stocks and bonds.

Against this backdrop, the classic stock-bond balanced allocation regains strategic value. In the past low-rate era, bonds were often ignored due to low yields. But with US Treasury yields stabilizing at high levels, long-duration Treasuries and high-grade credit bonds offer considerable allocation value again. When stocks correct sharply due to AI valuation bubbles popping or macro data missing expectations, bonds provide stable coupon income, and their negative correlation with equities acts as a portfolio "shock absorber."

Investors should set reasonable stock-bond ratios based on risk tolerance and strictly execute portfolio rebalancing strategies. For instance, if tech stocks surge during earnings season, pushing equity ratios above thresholds, take profits decisively and rotate funds to bonds; conversely, if panic triggers a stock market crash, making bond ratios too high, reverse operations by shifting funds from bonds to oversold quality equities. The discipline of such contrarian operations is key to overcoming greed and fear for long-term value investing.

Multi-Asset Allocation: Building an All-Weather Long-Term Value Portfolio

Under a prudent investment philosophy, true wisdom lies not just in capturing single-asset trends, but in building an all-weather portfolio that transcends economic cycles through multi-asset allocation. Beyond stocks and bonds, commodities, gold, and certain alternative assets hold irreplaceable allocation significance currently.

Gold, a traditional inflation hedge and safe-haven asset, offers macro hedging value independent of stocks and bonds amid frequent geopolitical risks and continuous central bank purchases. Adding gold or gold-related assets to a US stock portfolio effectively lowers overall volatility. Additionally, energy sectors tied to AI computing demand—especially power infrastructure and uranium firms—warrant attention. AI data centers' exponential power consumption brings multi-year earnings certainty to firms transitioning traditional to clean energy.

From a long-term value investing perspective, excellent asset allocation isn't about predicting the future, but building a system that survives and profits regardless of scenarios. At this sensitive juncture where the US market verifies AI capex, investors should return to allocation fundamentals:

• Hold Core Assets: Identify platform giants with real pricing power and sustained profitability as portfolio core holdings.
• Add Satellite Assets: Use small positions for high-elasticity AI application or semiconductor equipment leaders to capture excess returns.
• Strengthen Cross-Asset Hedging: Use counter-cyclical properties of bonds and gold to hedge potential equity market systemic risks.
• Execute Disciplined Rebalancing: Abandon emotional trading; dynamically adjust portfolios regularly using clear valuation anchors and position ratios.

Conclusion: Stay Calm Amid Noise, Navigate Uncertainty with Allocation

In August 2026, the US market is in a critical transition from AI narrative to profit realization. Every data point in tech giants' earnings could trigger market ripples. However, for rational investors embracing long-term value investing, short-term earnings volatility shouldn't alter allocation strategies, but serve as a touchstone to test and optimize portfolio resilience.

Facing the valuation-profitability gap, investors needn't guess specific earnings numbers. Instead, build a self-repairing portfolio via barbell strategies, stock-bond balancing, and multi-asset allocation. In volatile markets, allocation wisdom often outweighs stock-picking skills. Only by prioritizing risk control and using scientific holdings to navigate potential scenarios can investors capture the era's dividends from the AI-driven industrial revolution while safely enduring inevitable cyclical pains, ultimately achieving robust, substantial wealth growth.