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The much-better-than-expected July nonfarm payrolls and Berkshire's Q2 earnings report – could these be two signals that US stocks are stabilizing and rebounding?

BIT
特邀专栏作者
2026-08-10 10:50
This article is about 1614 words, reading the full article takes about 3 minutes
Buffett's choice essentially says: in the second half of the AI trade, certainty is worth more than flexibility.
AI Summary
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  • Core View: Last Friday's US nonfarm payroll data came in significantly below expectations, and the decline in Berkshire's cash reserves together signal that the market is stabilizing and rebounding, and indicate that the AI trade logic is shifting from cyclical memory chips to more certain application-layer giants (such as Google).
  • Key Elements:
    1. The US July nonfarm payrolls decreased by 23,000, far worse than the expected increase of 80,000, strengthening expectations of a Fed rate cut and driving all three major US stock indices to close higher.
    2. Berkshire's Q2 cash reserves fell from a record $397 billion to $365.5 billion, with net spending of $31.5 billion in one quarter, marking a shift in its investment direction from "holding cash and waiting" to "moving to deploy."
    3. Buffett deployed about $20 billion to increase his stake in Google, rather than the memory chip stocks that the market had been hotly discussing, reflecting his preference for the "AI application realization" ecosystem money over the "supply-demand imbalance" cyclical money.
    4. The market cautions that rate cut expectations will fluctuate with subsequent economic data (such as CPI, nonfarm payrolls), and the market path will remain bumpy, so one cannot simply "copy the homework."

Last Friday, two events worth paying close attention to occurred. Together, these two events may have conveyed two signals of stabilization and recovery for the U.S. stock market, which had recently shown some weakness.

One comes from the non-farm payroll macro data, and the other comes from Warren Buffett's Berkshire.

1. Signal One: Non-Farm Payrolls Significantly Exceed Expectations

Let's look at the macro picture first. U.S. non-farm payroll employment decreased by 23,000 in July—not only the first decline since February, but more critically, far exceeding expectations: the market had anticipated an increase of 80,000.

From the expected "+80,000" to the actual "-23,000," this extreme reversal signal triggered excitement rather than panic as the market's first reaction. The logic is straightforward: a clearly weakening job market significantly lowers the threshold for Fed rate cuts, rapidly intensifying market expectations for a cut, and instantly reviving liquidity-easing trades.

In the end, all three major U.S. stock indices closed higher.

2. Signal Two: Berkshire's Cash Pile Decreases by $31.5 Billion

The other signal comes from Berkshire's Q2 earnings report.

In this report, the most critical number isn't profit, but the change in cash reserves. In Q1, Berkshire's cash reserves had reached a record $397 billion—the market was constantly worried at the time: Buffett hoarding so much cash without acting, does that mean he thinks the market is too expensive? Does it mean some black swan event is about to hit? After all, the Oracle of Omaha sitting on the sidelines has never been a good omen for a bull market. Buffett has long proven that no matter the circumstances, he may not win every time, but he absolutely never loses—he always survives in the market.

By Q2, cash reserves had fallen to $365.5 billion. In one quarter, $31.5 billion was deployed.

The significance of this number lies in the fact that Berkshire, this massive ship, has finally begun to change course. When the market's most cautious capital starts shifting from "holding cash" to "taking action," it is itself one of the most powerful endorsements of market valuations.

What's even more intriguing is where the money went—of that $31.5 billion, roughly $20 billion was poured into increasing its stake in U.S.-listed Alphabet (Google).

3. From Memory Chips to Alphabet: Another Approach to the AI Trade

Buffett's choice happens to align perfectly with our previous analysis.

Within the current AI narrative trading context, we've previously analyzed the issue with memory chip stocks: expectations have already peaked ahead of fundamentals, valuations are pricing in peak performance in advance, and rushing in now could mean buying at the mountain top. So, is there a more stable AI beneficiary?

Buffett gave his answer with $20 billion: Google.

Google's logic is completely different from that of memory chip stocks. Memory chip stocks profit from cyclical "supply-demand imbalance," with gross margins already surging to highs around 80%, meaning the upward slope will inevitably flatten. Google, on the other hand, profits from the ecosystem value of "AI application adoption," benefiting across cloud services, search, and large language models—its valuation hasn't over-discounted as much expectation. Buffett's choice essentially says: in the second half of the AI trade, certainty is worth more than upside potential.

4. Final Thoughts

However, one thing to note: neither the rate-cut trade driven by non-farm payrolls nor the sentiment recovery backed by Buffett's endorsement is a straight line.

Rate-cut expectations will keep swinging with every economic data release—weaker data raises expectations and lifts stocks; stronger data cools expectations and drags stocks down. Every upcoming CPI print and non-farm report could trigger significant market volatility. Similarly, "buying Google because Buffett does" isn't blind copycat investing—Berkshire's cost basis, holding period, and scale are on an entirely different level from retail investors.

This kind of market condition—where "direction has clues, but the path is bumpy"—is precisely when tools become valuable.

BIT Exchange's options buying feature is suited for trading this kind of data-driven, high-volatility window: whether betting that the next data release will further push rate-cut expectations, or hedging against pullback risk in existing positions, you can participate with small costs, with maximum loss locked in at the premium at the time of order placement—turning the uncertainty of a data surprise into a calculable cost. The margin trading feature is better suited for after the signal is confirmed: once a rate cut materializes and the trend becomes clear, you're not limited by principal size and can amplify positions to capture the move.

The signals have appeared, but the turbulence won't be scarce. Using the right tools is what gives you a better chance of actually converting signals into returns.

Disclaimer: This article is based solely on public information and market data for analysis and discussion. The views expressed represent the author's personal judgment and do not constitute investment advice, securities recommendations, purchase or sale offers, or return promises for any securities, financial products, or digital assets. The analysis of companies, industries, and market trends mentioned herein does not represent future performance, nor does historical performance guarantee future results. Investors should fully understand the risks, fees, and trading mechanisms of relevant products and make independent judgments and prudent decisions based on their own risk tolerance. Markets are subject to volatility risk, and the use of leveraged instruments such as options and margin trading may amplify gains and losses; investors may lose part or all of their invested capital.

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