Can a rate cut promise overcome Tech’s wobbles?

Preface: Explaining our market timing models

We maintain several market timing models, each with differing time horizons. The “Ultimate Market Timing Model” is a long-term market timing model based on the research outlined in our post, Building the ultimate market timing model. This model tends to generate only a handful of signals each decade.

 

The Trend Asset Allocation Model is an asset allocation model that applies trend-following principles based on the inputs of global stock and commodity prices. This model has a shorter time horizon and tends to turn over about 4-6 times a year. The performance and full details of a model portfolio based on the out-of-sample signals of the Trend Model can be found here.

 

 

My inner trader uses a trading model, which is a blend of price momentum (is the Trend Model becoming more bullish, or bearish?) and overbought/oversold extremes (don’t buy if the trend is overbought, and vice versa). Subscribers receive real-time alerts of model changes, and a hypothetical trading record of the email alerts is updated weekly here. The hypothetical trading record of the trading model of the real-time alerts that began in March 2016 is shown below.

 

 

The latest signals of each model are as follows:
  • Ultimate market timing model: Buy equities (Last changed from “sell” on 28-Jul-2023)
  • Trend Model signal: Bullish (Last changed from “bearish” on 27-Jun-2025)
  • Trading model: Neutral (Last changed from “bullish” on 31-Jul-2025)

Update schedule: I generally update model readings on my site on weekends. I am also on X/Twitter at @humblestudent and on BlueSky at @humblestudent.bsky.social. Subscribers receive real-time alerts of trading model changes, and a hypothetical trading record of those email alerts is shown here.
 

Subscribers can access the latest signal in real time here.

 

 

Technology Wobbles

Last week I reiterated concerns about the narrowness of technology leadership. During the week, the market wobbled as it underwent a violent rotation when technology leaders fell sharply. The sector violated a rising trend line and it’s now testing a key relative support level. The weakness was only a matter of time, as relative breadth indicators (bottom two panels) had been deteriorating for several months.

 

On the other hand, the stock market adopted a risk-on tone after Fed Chair Powell opened the door to a September rate cut by shifting the focus to the Fed’s employment mandate: “Downside risks to employment are rising. And if those risks materialize, they can do so quickly in the form of sharply higher layoffs and rising unemployment.” Stock, bonds and gold prices soared and the USD fell after his remarks. Was the tech wobble just a market hiccup?

 

 

 

AI Fever Retreats

The warnings were plain to see. The Verge reported that OpenAI CEO Sam Altman said the quiet part out loud: Artificial intelligence could be in a bubble comparable to the dot-com era of the late 1990s. Altman was quoted as saying: “When bubbles happen, smart people get overexcited about a kernel of truth…Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes.”

 

One of the appealing qualities of the technology sector is its capital-light characteristics, unlike the more traditional industrial companies that require a lot of investment in plant and equipment. A common theme that emerged during the dot-com bubble and the AI boom today is their unbelievable capital expenditure levels. The accompanying charts from BCA Research tells the story of the parabolic investment trends, then and now. As the chart of capital spending during the dot-com is shown in dollars, and the one today is shown as a percentage of GDP, my own estimate of the peak capital spending of the dot-com bubble indicates a peak of about 1.1% of GDP, which is slightly less than the levels today (chart annotation is mine).
 

 

The parabolic growth in capital spending is occurring against a backdrop of diminishing returns from large language models (LLMs). If progress starts to stall, it could affect market sentiment.

 

 

As well, AI adoption appears to be hitting some roadblocks. A Census Bureau survey shows that using AI in last two weeks fell to 8.8%, the lowest since May.

 

 

A recently published MIT study, “The GenAI Divide: State of AI in Business 2025”, found that 95% of AI pilot programs are failing. A Fortune article explains the problem as workflow integration:

The core issue? Not the quality of the AI models, but the “learning gap” for both tools and organizations. While executives often blame regulation or model performance, MIT’s research points to flawed enterprise integration. Generic tools like ChatGPT excel for individuals because of their flexibility, but they stall in enterprise use since they don’t learn from or adapt to workflows, Challapally explained.
The data also reveals a misalignment in resource allocation. More than half of generative AI budgets are devoted to sales and marketing tools, yet MIT found the biggest ROI in back-office automation—eliminating business process outsourcing, cutting external agency costs, and streamlining operations.

 

By implication, the much touted mass layoff effect from AI adoption is far in the future.
 

 

Constructive Signs

Here is the good news, even as large-cap technology stocks falter, the rest of the market is holding up well on a relative basis. The equal-weighted S&P 500 broke out on Friday to an all-time high, and the percentage of stocks above their 200 dma rose a new recovery high, indicating strong participation.
 

 

Equally encouraging are the absolute and relative upside breakouts exhibited by the small-cap Russell 2000.
 

 

As well, these before and after Powell speech snapshots of Fed Funds expectations summarizes how the market consensus has shifted. The odds of a September rate cut rose from 71.5% to over 90%. The market still expects two quarter-point rate cuts in 2025, and an accelerated easing schedule in 2026.
 

 

 

No Major Top in Sight

From a big picture perspective, I see few signs of a major market top despite the tech wobble. In a surprising turn of events, well-known value investor Howard Marks appeared on Bloomberg TV and acknowledged that U.S. stocks are in the “early days of a bubble”, but he is not “ringing the alarm bells” of a “serious market correction”. He compared current conditions to 1997 when Greenspan warned about irrational exuberance, but stock prices continued to rise for several years.

 

Jim Paulsen studied the variance from the long-term of different investment styles. While large-cap growth is highly extended, he found that the rest of the market is not, which is constructive for long-term equity returns.
 

 

In addition, consumer confidence is low by historical standards, which tends to be bullish for equity returns.
 

 

 

Short-Term Warnings

Nevertheless, I am tactically cautious on stock prices. Most of the improvement in breadth indicators can be attributed to the single-day reaction to Powell’s speech, and I would prefer to see bullish confirmation before becoming overly bullish. As a reminder, the market had been hesitant until the Powell speech as the S&P 500 declined for five straight days. Even as the S&P 500 tests overhead resistance, it’s exhibiting negative RSI divergences. And even though the VIX Index fell to test its lows, the VVIX, which is the volatility of the VIX, exhibited a divergence by staying at elevated levels.

 

 

As well, the July FOMC minutes showed that, were it not for the extreme weakness in the Payroll Report, most of the Committee believed that a September rate cut would be highly doubtful. In his Jackson Hole speech, Powell adopted the Waller view that tariff-induced inflation is probably a one-time shock and labour market weakness can’t be ignored.

 

Bloomberg’s NLP Fedspeak Index, which is derived from a chatbot, interpreted recent Fed speeches as having hawkish tones. While the opinion of the Fed Chair undoubtedly carries a lot of weight, this is a sign that the FOMC is divided. The market consensus is highly fragile, and even slight shifts in the data, such as a hot PCE print or strong NFP report, could quickly shift expectations in the opposite direction.
 

 

Based on the recent record of weakness of initial jobless claims (red lines, inverted scale), the odds of a positive July nonfarm payroll surprise are elevated, which would completely flip the narrative and market expectations.
 

 

From a trader’s perspective, banking system liquidity is weak, which creates a headwind for stock prices. Recent Treasury’s debt sales were supported by a decline in ON RRP, which is now almost empty. Further debt issuance will drain market liquidity.
 

 

Investors should be on guard for heightened levels of volatility. Nautilus Research pointed out that we are entering a period of positive seasonality for the VIX. As the S&P 500 tends to be inversely correlated with the VIX, investors should pay special attention to developments in volatility during this seasonally important period.
 

 

In conclusion, recent stock market leadership had become overly concentrated in large-cap technology stocks, which wobbled last week. The good news is market breadth is broadening out, which sets the tone for further price advances. However, weakening liquidity and negative seasonality pose short-term risks to the current uptrend.

 

2 thoughts on “Can a rate cut promise overcome Tech’s wobbles?

  1. Hereis a small summary:

    1. Fri price action is a combo of hedging unwind and short covering. IWM had a very deep speculator short and high commercial long postiiotns before Fri. A lot of correlation trades are hinged on rate cuts by Fed. Along the way we need to observe how market front-run the rate cut expectation to determine which area money will be flowing to. We already saw first signs: home buliding, small caps, financials, retail and discretionary. Of course cryptos and precious metals and ARK funds.

    2. AI model development has shifted direction. Large general foundational models have reached near plateau. It is now prone to hallucination as edge cases occurred more often and convergence is precarious. This now requires more manual intervention. Since 80% of AI work is data labeling the emphas is now shfted to data handling before training.

    3. The AI eco stack is formed. A few will do large foundational models and and the rest will be in anywhere of the stack from this ground level up. Which implies that the next steps will be custom models leveraged on the foundational models. This is where majority of companies will be focused on. Custom models integrated into current workflow by trial and error. Most of of AI compnaies will be profiting from helping corportaions adapt and do regular maintenance/upgrade as new data arrive. And a lot of them will die, like in dot com era.

    4. As a result the current IT landscape will shift a little. A lot of companies will reacquire edge computing resources and hosted by widespread local micro datacenters, together with sourcing from existing large hyperscalers to form a new hdrid cloud structure.

    5. The industry transformation takes some time but the payoff will be enormous, especially for companies in various tech fields.

  2. They say that interest rates precede the Fed. A monthly chart of the UST2y shows this nicely. The 12 month SMA has been going down for a year. It started rising in 2021, well before Powell started to raise rates. This doesn’t mean rates can’t go higher, but most of the time the 12 month SMA trend lasts several years.
    If we get an inflation shock, it could go up, but aging boomers is deflationary.
    Of course if things crash rates fall into a hole.
    But really, if rates drop .25 % in September , will we all be chaffing at the bit to go to Europe, or on boat tours or buy things because that car loan went from not really affordable to maybe a little less not really affordable.
    It’s all noise.

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