In the first half of 2026, markets showed an unusual intensity of divergence - high-growth sectors kept setting new records while domestic demand industries faced broad pressure. Entering July, global markets underwent a rapid style shift, sparking increasing discussions about valuation bubbles. What has changed beneath the surface?

At a mid-year exchange in early July, Han Haifeng, Partner and Head of Research at Gaoyi Asset Management, shared his perspectives on these dynamics. The following Q&A excerpts cover his market review and observations on AI, energy, consumption, internet, and other sectors, offering a window into his thinking.

Market Perspectives - What's Behind July's Sharp Decline?

Question: How do you view July's market downturn and what matters most going forward?

Han Haifeng: The July correction appears more like a rebalancing of overcrowded positioning, stretched valuations, and high leverage, rather than a reversal of the AI trend. That said, financing pressures and concentration risk are indeed building. The market's valuation logic for AI has shifted from focusing solely on capital expenditure to measuring monetization efficiency and cash flow resilience. This shift was clearly visible in the pullback - within the tech sector, large software and cloud platforms with stable cash flows and direct computing monetization held up relatively well, while asset-heavy, thin-margin businesses and categories like memory and semiconductor equipment - the biggest gainers and most crowded trades - fell the most.

Meanwhile, the industry itself is evolving: domestic large language models continue rapid iteration, China's AI cost-performance and competitiveness keep rising, and the competitive landscape for foundation models remains highly uncertain. Additionally, the listing of some large technology companies has not only disrupted market liquidity but also carries long-term implications for hardware industry structure. Overall, the industrial trend hasn't reversed yet, but AI application progress, the realization timeline for cloud provider returns, and financing sustainability under tight external liquidity conditions all remain significant uncertainties.

On the macro front, the Federal Reserve held rates steady in July but showed a rare split with three committee members calling for hikes. The resulting steepening of the Treasury yield curve suggests rising expectations of future rate increases, and tight external liquidity persists - constraining long-duration, rate-sensitive AI assets and global risk appetite. For AI specifically, a prolonged high-rate environment means cloud providers will face persistently elevated financing costs. Moreover, the Fed's continued de-emphasis of forward guidance means markets will need to rely more on hard data, and policy uncertainty itself could become a source of volatility. Adding to this, renewed US-Iran tensions, oil price swings, and inflation fluctuations remain key variables influencing the Fed's policy path.

Domestically, Q2 GDP grew 4.3% year-over-year - the lowest since 2023 - with weak investment and consumption. Exports performed well, boosted by AI-related sectors, while the K-shaped divergence remained pronounced. The late-July Politburo meeting adopted a more supportive tone, lifting expectations for policy action, though the magnitude and direction of measures still need further confirmation.

Overall, AI remains a critical market variable. In Q2, domestic active equity funds pushed holdings in sectors like electronics and communications to historic extremes. July's market turbulence reflects both a rebalancing of that crowded positioning and AI's transition from its "capital-driven" first phase to a "commercial validation" second phase.

Question: Given extreme divergence and heightened volatility, what is the value of balanced allocation?

Han Haifeng: From a market perspective, extreme divergence and high concentration inherently carry substantial risk, with the most intuitive being a stampede effect. Thanks to strict regulatory controls on investor leverage in recent years, China's market doesn't face the same fragility seen in South Korea today or the A-share "leverage bull" of 2015. Nevertheless, the risk of extreme divergence is real because high concentration stems from highly aligned expectations - once consensus breaks down, the negative feedback loop can be severe.

In the AI supply chain, overseas hardware leaders still capture the majority of value. Some Chinese companies with strong competitive positions in specific components are participating in profit distribution, but high expectations have been priced into many firms that lack genuine competitiveness. Going forward, differentiation will intensify with a focus on separating winners from noise - companies that can actually secure orders and grow earnings will generate returns, while those relying on narrative with inflated valuations face significant downside.

This is precisely where balanced allocation demonstrates its value. It avoids excessive exposure to any single sector and instead diversifies opportunities across different industries to rebalance risk and reward. The advantage lies in not putting all eggs in one basket: when AI excels, there's participation in those gains, and when AI corrects while other sectors move, diversified positioning captures those opportunities. At its core, this is a trade-off strategy - no asset is perfect, and the goal is finding a fit that's optimal for the current environment and one's objectives.

Industry Insights - Beyond the AI Bubble Debate

Question: With increasing talk of an AI valuation bubble, what's your view?

Han Haifeng: Every so-called bubble doesn't emerge from thin air - it's backed by real fundamentals, just excessively amplified by markets. This AI cycle differs fundamentally from previous bubbles, particularly the internet era of 2000, in two key respects. First, on fundamentals: before the 2000 dot-com bust, severe overinvestment had occurred. When the US relaxed telecom regulations, a flood of companies entered and laid fiber optic cables nationwide, all betting on the coming "information century." Yet over 85% of that fiber became "dark fiber" - never transferring a single byte of data. In contrast, today's AI capital expenditure in China faces a genuine compute shortage constraining development and adoption, and overseas capacity largely matches real demand without widespread idle assets. So there's no evidence yet of overinvestment in AI.

Second, on valuation versus earnings: past bubbles burst with valuations compressing from elevated levels, but this rally has been driven primarily by earnings growth rather than multiple expansion. Take the memory sector - which saw significant price increases this year - if we apply the market's expected next-year EPS, several top Korean memory companies trade at only 3-4 times earnings. The debate there centers on earnings sustainability, given the industry's history of periodic losses. With current margins at 50-70%, the question is whether profitability will see a major pullback.

Rather than fixating on bubble talk, we're focused on sustainability across four dimensions. First, whether cloud providers' capital expenditure is sustainable - the key signal is whether future guidance gets raised or cut. At current investment intensity, cloud free cash flow is exhausted; further increases would require debt financing. Second, whether cloud providers' financial structures are fragile - whether rate or policy shifts could break their funding chains. Historically, many bubbles burst not from deteriorating earnings but from sharply rising rates that snap the weakest financial links - this is why we're closely monitoring Fed hike expectations. South Korea's recent market correction, driven largely by excessive financial leverage, is a case study in how deleveraging triggers sharp volatility. Third, whether AI model capabilities continue improving with sufficient revenue potential to justify trillions in investment and generate reasonable returns. If ARR growth at giants like Anthropic and OpenAI slows or stagnates, the market will question AI's addressable market, reshaping the entire narrative. Fourth, structural risks in profit distribution. Currently, profits concentrate upstream, where companies enjoy record-high margins. But manufacturing follows supply-demand dynamics - even with strong demand, if supply grows faster, profits won't stick. The key is watching for supply-demand shifts; if demand slows or supply surges, upstream margins could compress and profits redistribute across the value chain.

Beyond AI: Energy, Consumption, Internet, and Others

Question: What other sectors are you monitoring?

Han Haifeng: Our research team maintains deep coverage across all industries. Beyond AI, we're continuously tracking energy, consumption, internet, and other sectors that the market may currently be overlooking.

Energy: US-Iran tensions have heightened global energy concerns, while AI data center buildout is driving surging electricity demand - power shortages are emerging across parts of the US, creating tightness in power equipment. We're tracking global energy solutions, whether through renewables like wind and solar, nuclear restart, or off-grid models pairing solar panels with battery storage for areas lacking grid infrastructure. China's energy storage products are selling globally precisely because many countries lack the capacity for large-scale grid construction. Energy solutions represent a major future direction.

Consumption: Active fund allocations to consumer sectors in Q2 fell to their lowest since 2013, marking it as a consensus-unloved asset class. But with China's economy at the bottom of its cycle and showing signs of recovery, we're actively evaluating opportunities here. Consumer valuations sit at just over 10 times earnings with dividend yields of 3-5% - even without growth, that stable income stream beats bank deposits. Should economic recovery boost household confidence, lift income expectations, and spur spending, the sector's narrative could reverse sharply.

Internet: Leading internet companies have seen forward P/E ratios compress from the 20-30 times of five years ago to around 10 times today. The market is pricing them as value stocks rather than growth companies, yet their scale economics and competitive advantages persist. Meanwhile, some firms may open new growth paths by embracing AI, potentially expanding their addressable markets - that's worth watching.

Manufacturing and Commodities: The strong dollar has pressured global commodity prices this year, but supply-side expansion remains slow. Chinese companies dominate much of the new capital expenditure in mining globally, while overseas counterparts stay cautious. Looking 3-5 years out, some commodity companies trade at just 5-6 times earnings, presenting attractive opportunities. In chemicals, unlike textiles where entry only requires spinning machines, high technical and capital barriers prevail. Overcapacity from prior domestic expansion may recede as China's dual-carbon policy restricts supply, and a significant supply-demand improvement could reward patient investors.

Financials: Banks and insurers currently offer highly attractive valuations. The industry typically generates ROE above 10% yet trades at only 0.6-0.7 times book value. While falling rates pressure earnings performance, a Chinese economic recovery and a turn in domestic rates would flip this dynamic into an upside catalyst.

Disclaimer: This content reflects the interviewee's analysis, speculation, and judgment at the time of the interview. Information is derived from public sources and its accuracy, completeness, or sufficiency is not guaranteed. This material is for reference only and does not constitute advertising, a sales offer, or advice to trade any security, fund, or investment product. Any entities, brands, or products referenced are solely for research analysis and do not represent investment examples by the interviewee or their organization. Market risk exists; investment requires caution.