Far exceeding expectations at 165,000, does the nonfarm payrolls report rekindle the "soft landing" narrative for the U.S. economy? Mechanical selling pressure cannot stop the AI and tech recovery momentum after the sharp sell-off.

Title context: Far exceeding expectations at 165,000, does the nonfarm payrolls report rekindle the "soft landing" narrative for the U.S. economy? Mechanical selling pressure cannot stop the AI and tech recovery momentum after the sharp sell-off. Text: The U.S. labor market data report for October just released by the U.S. government shows that the U.S. nonfarm labor market added 165,000 jobs on a large scale in October, far exceeding the market median expectation of 65,000, with the unemployment rate falling to 4.1%, and the employment data for the previous two months revised upward by a combined 84,000. This provided risk asset sectors such as the U.S. stock market, which on Thursday and Friday experienced brutal sharp sell-offs in AI computing power and semiconductors and even broader technology stock themes, as well as global stock markets, with increasingly strong economic resilience support under the "soft landing" narrative for the U.S. economy. At the same time, another piece of information crucial to financial markets shown by the nonfarm payrolls report is that nonfarm employment growth covered multiple industries, while year-over-year wage growth remained at a low level in recent years. To a large extent, this means that strong nonfarm payrolls can both improve corporate earnings expectations and give the Federal Reserve more confidence to continue addressing inflation; a tech stock rebound, rising U.S. Treasury yields, and pressure on gold can occur simultaneously, and the market is digesting both the growth-oriented positive from the expansion of AI investment in the United States and the pressure from rising interest rate expectations. U.S. nonfarm payrolls added 165,000 jobs in October, far exceeding the consensus expectation of 65,000 among economists, and combined with the upward revision of 84,000 for the previous two months, it reinforced the judgment that household income, consumer demand, and corporate earnings can maintain resilience. The nonfarm report showed year-over-year wage growth of 3.1%, which, although higher than forecast, remained at a low level in recent years, preserving room for the soft landing narrative; at the same time, strong employment also gave the Federal Reserve more confidence to focus on inflation. After the data was released, the market's bet on a December rate hike rose from about 70% to 78%, and U.S. Treasury yields and the dollar rose accordingly. This repricing did not immediately interrupt the premarket rebound that technology stocks had previously started: Nasdaq futures were still up about 1.4%, indicating that post-selloff buying support is contending with higher funding costs. Against the backdrop of Barclays' estimate that volatility-target strategies could release about $135 billion in deleveraging pressure over the next 24 to 48 hours, whether the rebound can continue depends on whether active buying and possible short covering can absorb delayed selling pressure. What the market is trading is whether the strong resilience outlook for the U.S. economy, dominated by the multi-year AI super bull market as well as trillion-dollar-level AI investment and expectations of AI-driven productivity transformation, can provide earnings support for technology stocks that have experienced valuation compression, while the rally itself may also gradually improve trend and volatility conditions and create room for subsequent repair. Employment beats expectations, wages remain moderate: soft landing gains support, and the Fed also has more confidence for further rate hikes Before the October nonfarm payrolls release, the median forecasts in Reuters and Bloomberg surveys both pointed to 65,000 new jobs and an unemployment rate maintained at 4.2%. Among major institutions, Goldman Sachs, Bank of America, and JPMorgan all forecast an increase of 75,000, Morgan Stanley forecast 60,000, Deutsche Bank forecast 55,000, and Barclays forecast 50,000. Therefore, the actual result of 165,000 not only exceeded the consensus by 100,000, but also clearly surpassed the relatively optimistic judgments of several large banks. The market had originally expected a modest recovery from the September low, but what it actually received was a report showing a marked strengthening in hiring. Even more significant is that the employment improvement was continuous and broad-based across industries: August new jobs were revised up from 133,000 to 186,000, and September from 29,000 to 60,000, with the revised average for the past three months at about 137,000. In October, professional and business services added 70,000, health care added 42,000, transportation and warehousing added 25,000, and manufacturing also added 19,000. The series of newly released data above weakened the judgment that "a sharp drop in hiring signals an imminent economic stall" and provided a more solid foundation for household income, consumer demand, and corporate revenue growth. Especially for technology companies closely linked to the surge in AI computing power and AI agents, support for corporate client budgets and end demand helps ease market concerns that AI capital expenditure risks will be further extrapolated into a full-scale earnings recession. Wage data need to be viewed in terms of both the surprise versus expectations and its historical position. Average hourly earnings rose 0.4% month over month and 3.1% year over year, above the prior expectations of 0.3% and 2.9%; however, according to Bloomberg's comparison, 3.1% was still equal to the lowest year-over-year growth rate since 2021. Therefore, this newly released overall nonfarm payrolls report cannot be directly described as wage inflation spiraling out of control again, nor can its stronger-than-expected aspect be ignored. What it reinforces is the judgment that "the economy can withstand further tightening," rather than proving that the Federal Reserve must carry out consecutive large rate hikes. Employment resilience gives policymakers more room to focus on inflation, while whether the soft landing can ultimately be delivered still depends on the subsequent combination of wages, productivity, energy prices, and overall prices. Tech rebound and bond decline in parallel: the market reweighs earnings support and funding costs This report landed at a time when positioning was highly fragile. After Democrats won control of both chambers of Congress, market concerns intensified over data center approvals, construction pace, and investment returns. On Thursday, the Nasdaq 100 fell 6.36%, the largest single-day drop since March 2020; the S&P 500 fell 4.36%, the Philadelphia Semiconductor Index fell 12.25%, and the VIX surged about 70% to around 28. Asian trading on Friday extended the overnight shock: South Korea's KOSPI closed down 6.02%, falling below 5,000 points during the session and triggering a circuit breaker, before closing back at 5,059.69; the Nikkei 225 fell 5.96%, and Taiwan's weighted index fell 4.51%. It should be noted that these Asian closes occurred before the nonfarm payrolls release and reflected de-risking in the AI trade rather than a reaction to strong employment data. After such a sharp decline, chip stocks had already seen support in premarket trading. Jefferies equity strategist Jane Gibbons attributed Thursday's sell-off to a concentrated collision of AI spending, policy, and inflation concerns, and believed the market reaction did not yet mean corporate fundamentals had been fully reset. At 8:31 U.S. Eastern Time after the nonfarm release, or 21:31 Beijing time, Nasdaq 100 futures were still up 1.37%, S&P 500 futures were up 0.11%, and Dow futures were down 0.96%; Reuters explicitly pointed out that S&P futures narrowed their gains after the data release. The trading clue that can be derived from this is that the trading state at the time was technology stocks continuing their post-selloff repair while being constrained by rate-hike repricing, and it could not yet be summarized as strong nonfarm payrolls driving a broad U.S. stock rally. The underlying logic is that stocks reflect future earnings, discount rates, and risk premiums at the same time. Strong employment can reduce recession concerns and increase the credibility of earnings delivery; even if Treasury yields rise, stocks may still rise as long as these supports are enough to offset valuation pressure. In other words, technology stocks can continue to rebound while U.S. Treasury yields rise because stock prices are affected simultaneously by earnings expectations, the risk-free rate, and the equity risk premium. Strong employment eases recession concerns and strengthens corporate earnings expectations; as long as the positive from earnings support and a decline in the risk premium is enough to offset the valuation pressure from higher rates, stock prices may still rise. Bonds, meanwhile, more directly bear the impact of higher expected policy rates: in the initial period after the data release, the 10-year U.S. Treasury yield rose to about 4.898%, up more than 6 basis points, while spot gold was at about $4,041.89 per ounce, down more than 1%. Rate hike expectations support the dollar's interest rate differential advantage and raise the opportunity cost of holding non-yielding gold. However, the October employment data reflect the economic conditions before the election and cannot automatically eliminate future approval and financing pressures for data center projects; for highly leveraged computing power developers, financing costs remain another independent constraint. This bond pullback is also testing the true stance of previous Treasury bulls. Before the nonfarm release, some options trades bet that the 10-year yield would fall further to 4.7% or even 4.35%, but the logic for buying bonds was not entirely based on weak employment. Jamie Patton, co-head of global rates at TCW, previously said that even with strong data, she would prefer to add to bonds on declines; in a BMO survey, 48% of investors were prepared to buy into a nonfarm-induced bond pullback, above the six-month average of 43%. These top institutional investors are also watching falling oil prices, declining inflation expectations, and safe-haven demand. Therefore, a short-term rebound in yields does not mean Treasury bulls have fully capitulated, and whether sustained support emerges later will directly affect the discount-rate pressure facing technology stocks. "Predicting your prediction" continues the game: the rebound does not need to wait for all the mechanical selling from "fast money"-dominated institutional forces to exit The reason Thursday's decline was so severe is that after Democrats controlled the majority of seats in both the House and Senate, market concerns over strict Democratic policies related to AI data center construction triggered a fundamental repricing, while trend breaks, volatility spikes, and leverage adjustments further amplified selling pressure. JPMorgan estimated that leveraged ETFs cut more than $60 billion in equity exposure late that day, about 90% concentrated in technology-related products; for subsequent volatility-target strategy deleveraging, JPMorgan estimated about $50 billion over the coming days, while Barclays estimated it could reach $135 billion over the next 24 to 48 hours. This global tech stock rout seems to present an increasingly clear reflexive chain: investors, worried that accelerating energy inflation will feed through and that AI computing infrastructure expansion will be hindered after Democrats control both chambers of Congress, sell semiconductor and broadly global technology-themed stocks; price breaks trigger large-scale deleveraging by "fast money"-type quantitative strategy institutional funds such as CTAs and volatility strategies; and active funds then trade these predictable sells in advance, further depressing technology-related trading prices in global stock markets. Volatility-target strategies and trend-following CTAs reducing positions after prices fall below signal thresholds are mechanical selling within fast money; active traders selling early and betting on buying back later at lower prices are "front-running" the mechanical selling. The key to the "predicting your prediction" logic behind the recent sharp sell-off is that active traders will trade these estimable rebalancing needs in advance: first selling or establishing shorts, then waiting to buy back after mechanical selling. When buying support is slow to appear, front-running behavior further pushes prices down and triggers more trend signals and risk-control deleveraging; but if prices stabilize, previously established shorts may also enhance the rebound through covering. Strong nonfarm payrolls can provide active buyers with a basis in economic resilience, but will not immediately change the instructions of all systematic strategies: trend-following CTAs focus on price trends, volatility-control funds focus on realized volatility, and leveraged ETFs reset exposure based on the day's moves. Therefore, even if the index rises and the VIX falls, some volatility-control funds may continue to reduce positions; at the same time, same-day rebalancing by leveraged ETFs may also turn into buying. At present, the forecast view more consistent with market price action and with where global institutional investors are actually putting real money is this: "economic resilience supports tech repair, rate-hike repricing limits rebound space, and active buying and delayed mechanical selling are clashing at the same time." In other words, the market does not need to wait for all mechanical selling to be exhausted before rebounding; rising prices themselves may also gradually ease some deleveraging pressure. If dip-buying in bonds limits the rise in yields, corporate earnings expectations remain stable, and equity stabilization gradually lowers realized volatility, strong employment is more likely to a basis for sustained repair; if rate expectations move further upward while AI orders and project returns are cut, earnings support may not be enough to cover valuation contraction. What truly determines the next stage of the market is whether incremental earnings support can offset higher funding costs, and whether market absorption capacity can digest the deleveraging demand still being executed. Although the Nasdaq 100 index posted its worst decline since March 2020 on Thursday, Wall Street's overall stance has not changed and remains biased toward long-term bullishness. Deutsche Bank has turned bullish again on U.S. technology stocks, believing the recent adjustment has been excessive, valuations and positioning have cooled, and earnings growth remains resilient; Morgan Stanley chief U.S. equity strategist Mike Wilson believes this round of adjustment is nearing its end and is focusing on high-quality companies whose valuations have already fallen and whose earnings durability is strong. The opportunity both point to is a re-matching of adjusted prices with the quality of long-term operating growth, rather than a synchronized rebound in all AI assets. Pershing Square, led by Ackerman, further pointed out in its latest shareholder letter that the market may be treating massive AI capital expenditure as long term but has not fully priced in the subsequent revenue acceleration these investments will bring; large technology companies' customer relationships, data, distribution channels, and commercialization capabilities make it easier for added computing power to be converted into chargeable services. Ackerman's latest judgment is already supported by strong growth in AI-related cloud businesses: Amazon's AWS revenue grew 39.3% in the third quarter, and Alphabet's Google Cloud revenue grew 103%, the latter including an important contribution from TPU system sales. Meta's hot bond sale added the financing link to this bullish logic: when revenue growth, financing availability, and investment returns gradually connect, high-quality platforms have the foundation to move from valuation compression to value re-rating.