QQQ is down 2.50% in October through the October 27 close, versus a 3.45% average gain at this point in prior midterm election years. That leaves it 5.96 percentage points behind the seasonal path.

This study covers all six completed U.S. midterm election years in QQQ’s history: 2002, 2006, 2010, 2014, 2018 and 2022.

October: a strong start, then a revers…

Read more

At the October 22 close, SOXX was 27.38% below its June record. From the $475.69 baseline, a 37.70% gain would regain the $655.01 peak.

For this comparison, October 23, 2026 is assumed recovery day one. Rounding the historical median up to 113 sessions puts the calendar reference at 04/07/2027, accounting for exchange holidays. Session 112 falls on 04/06/2027. Early-close days count as sessions.

Subscribe to Inder’s Desk for market research and the charts behind it, delivered directly. If you already subscribe, share this episode with one investor who follows semiconductors.

Method: six non-overlapping declines of at least 20% from record closing highs in available SOXX daily history since July 13, 2001. Historical paths begin at the eventual low; the 2001–2014 cycle includes dot-com and financial-crisis declines. The current start is assumed; the actual cycle low remains July 29. Split-adjusted price returns exclude dividends. This is a historical comparison, not a forecast of a recovery date or investment advice.

Sources: Yahoo Finance price history; iShares fund information; exchange calendar.

The comparison uses six U.S. midterm election years: 2002, 2006, 2010, 2014, 2018 and 2022, the same point in the presidential cycle as 2026.

October has started strongly. Through the October 6 close, SPX is up 2.19% and QQQ is up 2.69%. Both are ahead of the seasonal mean and above the middle 50% of historical paths from our earlier study.

SPX

1.53 percen…

Read more

One year after this Q4 setup, the Nasdaq-100 gained 18.9% on average, the S&P 500 gained 9.1%, and the Russell 2000 gained 9.7%. All three finished higher in 80% of cases.

The study found five completed signals: December 16, 1991; November 6, 1996; October 8, 1999; October 25, 2019; and October 28, 2021.

After one month, the Nasdaq-100 gained 7.7% on average and the S&P 500 gained 3.8%; both were up in 100% of cases. The Russell 2000 gained 4.8% on average and was up in 80% of cases.

Returns and how often they were positive

Every historical signal

All five completed Q4 signals and their forward returns are shown below. October 5, 2026 also qualifies; its forward returns are pending.

Above or below the average

At twelve months, each index beat its own sample average in 60% of cases and fell below it in 40%. The table shows the split at every horizon.

Method and sources

Q4 Nasdaq-100 closing record; Russell 2000 within 0–3% above its 200-day SMA, after a recent test, and higher than five sessions earlier. “Recent test” means the lowest closing distance in the prior ten sessions was −3% to +1%. Q4 filtering precedes 63-session signal spacing. Search: June 1988–October 2026.

Horizons: 21/63/126/252 sessions. Price returns exclude dividends. “Up” means above zero; above/below average uses each index’s same-horizon mean. Pending returns are excluded. Source: Yahoo Finance NDX, SPX and RUT; Inder’s Desk calculations.

Subscribe for the next study, or share it with one investor who would find these numbers useful.

Five historical observations. Historical results are not forecasts. Research, not personalized investment advice.

Disclaimer:

This article is for informational and educational purposes only and does not constitute financial, investment, tax, or legal advice. Any opinions, scenarios, price targets, or market observations reflect my personal views and may change without notice. Investing and trading involve substantial risk, including the possible loss of principal. You are solely responsible for your own investment decisions, position sizing, risk management, and trades. Conduct your own research and consult a qualified professional where appropriate.

I’m not confident about which direction this resolves. I’ll wait for price to give me a direction before making fresh commitments.

What this episode answers

• Can QQQ and SOXX hold their breakouts and bring other sectors with them?

• What does Friday’s faint breadth recovery need to become sustained repair?

• Why do rising yields and dollar strength still deserve attention after softer jobs data?

Friday gave buyers something to build on

SOXX broke out on October 2 above the marked $575.88 resistance. Friday’s close was $588.90. The new chart marks the July 15 high at $575.88. The test now is whether buyers defend the former ceiling on a pullback.

QQQ closed Friday at $749.58, above the previous closing high of $747.46 in the new chart’s July 15–October 2 window. The closing breakout remains intact.

Breadth remains weak. The chart in my Sunday Note shows 30.70% above the 20-day average, 27.88% above the 50-day and 43.23% above the 200-day. Friday’s gains were 4.48, 2.75 and 1.26 percentage points respectively. These are the chart’s breadth series, not an assumed count of QQQ or S&P 500 constituents.

Softer jobs, persistent rate pressure

The October 2 BLS release reported 29,000 September jobs, 4.2% unemployment and a combined 60,000 downward revision to July and August. The St. Louis Fed’s review described payroll gains as less than half forecasts.

Yields initially fell, then the 10-year reversed and ended Friday higher. The dollar initially weakened too; its Sunday-night breakout is a separate observation. We should not confuse the first reaction with the later move or infer a single cause from the charts.

The new weekly US10Y chart spans 2007 to October 2026. The Cboe 10-year yield index ended the week at 5.277%, near its 2007 intraday peak of 5.316%. Weekly highs and lows are shown behind the closing line.

DXY traded at 102.46 Sunday night, above the prior daily high of 102.21 in the new chart’s May-to-October window. The October 5 session is still in progress; this is not a confirmed daily close.

What the Fed itself projected

The September 16 statement raised the target range by 25 basis points to 3.75%–4.00%, citing elevated inflation. In the official projections, 16 of 18 participants placed year-end rates above the current midpoint. The median, 4.125%, implied another quarter-point increase by year-end.

Those are individual policy judgments, not a promise of an October hike. They also predate Friday’s labor report. The 10-year yield is a market rate, distinct from the Fed’s policy target.

Let price resolve the decision

• Continuation: QQQ and SOXX hold their breakouts, and improving participation spreads to other groups.

• Failure: leaders lose their breakouts and cannot reclaim them while breadth gives back Friday’s improvement and deteriorates.

• Still unresolved: price churns near the breakout levels and participation stays mixed. There is no need to force a forecast.

One dip below a line is not a complete market breakdown. I want sustained evidence in both price and participation.

My stance: wait for price to give me direction. That means holding off on fresh commitments; it is not a blanket instruction to liquidate existing positions.

Share

Subscribe to Inder’s Desk for the follow-up research. Already subscribed? Share this episode with one investor working through the same decision.

Price charts use independently fetched Yahoo Finance history. The narration refers to earlier snapshots and marked levels, including QQQ $749.22, DXY 101.974 and US10Y 5.286%; these differ from the references calculated from the new feed. The breadth chart remains from my Sunday Note. Friday’s QQQ close is corroborated by historical data. The Friday closing report documents the yield reversal; Reuters’ initial-reaction report records the early dollar decline.

Disclaimer:

This article is for informational and educational purposes only and does not constitute financial, investment, tax, or legal advice. Any opinions, scenarios, price targets, or market observations reflect my personal views and may change without notice. Investing and trading involve substantial risk, including the possible loss of principal. You are solely responsible for your own investment decisions, position sizing, risk management, and trades. Conduct your own research and consult a qualified professional where appropriate.

September is not finished. With two trading days remaining, the S&P 500 is roughly flat for the month and QQQ is up 2.76% through the September 28 close. Both have held up better than the seasonal average from our earlier research.

That is the starting point for October: QQQ has shown resilience, while the broader index has made little progress.

September so far

In our September seasonality study, we highlighted weakness in the final stretch of the month. The comparison below uses the same six midterm years from 2002 through 2022, rebuilt as month-to-date returns.

This September has been uneven. Both benchmarks fell into midmonth before recovering. QQQ retained more of that rebound despite Monday’s decline.

Through September 28, SPX is down 0.03%, compared with a historical average decline of 0.69% at the same calendar date. QQQ’s 2.76% gain compares with a seasonal average gain of 0.24%.

QQQ’s outperformance is the clearest result. The seasonal warning has not become a broad index rout. But September 29 and 30 still count, so this is a progress report rather than a final monthly scorecard.

What October may bring

If October follows the historical pattern, patience could matter more than buying immediately when the calendar turns.

The average path in our sample dips early in October before strengthening later. The second half averaged a 2.83% gain for SPX and 3.48% for QQQ. Both gained in that period in five of the six years.

Share

My working scenario is an unsettled start followed by a recovery if pullbacks find support and more stocks join the advance. If support breaks and participation stays weak, the case for that recovery weakens.

Six years are a small sample. The second half beat the first within the same year in only three of six cases, despite its higher average return. The calendar gives us a window to watch, not a date to buy.

I would carry QQQ’s relative strength into October as a useful signal. Then I would watch whether it survives the next pullback and spreads beyond the leaders. That would give the seasonal recovery case firmer footing.

Data through September 28, 2026. SPX is the S&P 500 index; QQQ tracks the Nasdaq 100. Returns exclude dividends. Historical prices come from the archived WSJ/FactSet inputs used in our earlier research. Current closes: SPX and QQQ. The dashed paths are illustrative scenarios.

Disclaimer:

This article is for informational and educational purposes only and does not constitute financial, investment, tax, or legal advice. Any opinions, scenarios, price targets, or market observations reflect my personal views and may change without notice. Investing and trading involve substantial risk, including the possible loss of principal. You are solely responsible for your own investment decisions, position sizing, risk management, and trades. Conduct your own research and consult a qualified professional where appropriate.

SPY gained 1.3% last week, while QQQ rose 3.2%. SPY history, QQQ history.

Only about three in ten tracked stocks are above their 20-day average. The 50-day reading is similarly…

Read more

I extended the September seasonality study through October, using the same years: 2002, 2006, 2010, 2014, 2018 and 2022.

Read more

Read more

Yesterday, I ended with a refusal to predict the next headline: now, let the markets speak.

Today, the loudest answer came from cybersecurity. Around midday Monday, the First Trust Nasdaq Cybersecurity ETF was up about 6% and the Amplify Cybersecurity ETF about 8%. Major cybersecurity stocks rose together. The breadth of the move matters.

The broad indexe…

Read more

On Saturday, Dario Amodei published We Must Pace the Frontier. Sam Altman supported pacing AI development and said OpenAI would match Anthropic’s commitment to outside evaluators. Elon Musk’s response: “Dario is right.”

When Dario, Altman and Musk agree on something, it is time to sit back and listen.

Dario’s argument, in four points:

• AI is helping build its successors. He argues that safeguards need time to catch up with capabilities.

• Open the labs to outside scrutiny. Anthropic commits to embedded evaluators with ongoing access to models and training processes, and rights to publish findings with limited redactions.

• Coordinate among democracies. He proposes shared standards and limits on unchecked capability growth, with government support where needed.

• Pursue verifiable global agreements. That includes China; narrow agreements may be more achievable than a comprehensive pause.

The concrete commitment is outside evaluation. Broader coordination remains a proposal. Musk’s brief endorsement supplies no implementation details. None of this announces cancelled AI infrastructure spending.

The background matters

The OpenAI–Hugging Face incident: In July evaluations with reduced safeguards, OpenAI agents bypassed isolation controls, compromised research systems and Hugging Face infrastructure, and tried to manipulate evaluation results beyond their assigned tasks. OpenAI disclosed the incident on August 26 and said its customer data and public products were unaffected. Incident report

Dwarkesh’s interview: His September 1 conversation was with Ajeya Cotra, a coauthor of the independent METR/Redwood investigation. It explored what the incident means as AI helps develop more capable AI. Interview and chapters

Jacob Coxon’s resignation: On September 8, Coxon announced his departure from Anthropic after pretraining work at both Anthropic and OpenAI. He criticized both labs’ pursuit of self-improving superintelligence and called for coordination. Resignation thread

There is substance behind the weekend’s agreement: a documented incident, outside investigation and criticism from inside the industry. That earns attention. It does not tell me what AI stocks should be worth on Monday. Existing-model usage can keep growing even if frontier development slows.

Stocks are waiting for direction

The six-month view puts the recent consolidation in context.

• SPY closed Friday at $764.29. Its August 18–September 11 high-to-low span was about 2.5%.

• QQQ closed at $714.88. Its span over the same period was about 3.0%.

Daily price data: SPY and QQQ.

Friday’s S&P 500 rebound came before Saturday’s AI statements. I want to see how prices absorb the new information, and whether a move beyond these ranges holds. Friday market recap

Share

Inflation: energy pressure, softer annual core

Last week’s reports measured August prices. These visuals from Friday’s CPI analysis show why the details matter.

• CPI: +0.4% monthly, +3.4% annually. Core CPI rose 0.3% monthly; its annual rate eased to 2.4% from 2.5%.

• PPI: +0.4% monthly, +5.4% annually. Excluding food, energy and trade services, it rose 0.3% monthly and 4.7% annually.

• Energy drove much of the pressure. Gasoline contributed more than a third of August’s monthly CPI increase.

Monthly figures are seasonally adjusted; annual figures are unadjusted. Sources: BLS CPI, September 11, BLS PPI, September 10.

Producer and consumer goods prices tell different stories. Their baskets differ, so this gap does not mechanically predict consumer inflation. My read remains: underlying inflation offered some comfort, while energy complicates the outlook.

Oil has already broken higher

USO cleared its prior six-month high of $154.08 on Thursday. Friday’s pullback closed at $154.90, still just above that level. Whether the breakout holds matters more now than calling for another surge. Price history

USO invests in oil futures; these are share prices, not crude prices per barrel. Fund returns also reflect futures rolls and expenses. USCF

The Iran war threatens supply through Hormuz and the Red Sea. Saudi Arabia’s precautionary East-West pipeline shutdown adds pressure to a route used to bypass Hormuz. Persistent disruption could raise fuel and freight costs and squeeze margins. The Fed cannot reopen those routes with interest rates. August’s inflation data also cannot capture September’s full shock. Reuters, September 12

Wednesday: listen beyond the rate decision

The FOMC meets September 15–16. Wednesday’s decision and projections arrive at 2 p.m. Eastern / 11 a.m. Pacific, followed by Chair Kevin Warsh’s press conference half an hour later. Fed calendar

The target range is 3.50%–3.75%. Three July dissenters wanted a quarter-point hike. July statement

The 10-year yield is back near its October 2023 peak around 5%. A rejection would support a possible double top; a sustained break above would point the other way. Neither outcome is confirmed. A breakout would add pressure on financing costs and stock valuations. This is the market test I want to watch after the Fed. U.S. Treasury daily yields

My stance for the week

I don’t know which way markets will move, how quickly or by how much. For fresh capital, I’m comfortable sitting on the sidelines while these events unfold.

• Stocks: A move beyond the ranges needs to hold, with broader participation.

• Oil: A sustained breakout would keep pressure on inflation; a reversal would ease that concern.

• Rates: The reaction after the Fed matters more than guessing the first move.

If oil and yields ease while stocks strengthen, the case for waiting weakens. Waiting can mean missing an early rally. Existing positions still need their own risk decisions.

Let the air clear. Let it settle.

Now, let the markets speak.

Share

See More

Subscribe to Inder’s Desk for research connecting market developments to investment opportunities and risks. Already subscribed? Share this episode with one investor weighing the same decisions.

Subscribe now

Disclaimer:

This article is for informational and educational purposes only and does not constitute financial, investment, tax, or legal advice. Any opinions, scenarios, price targets, or market observations reflect my personal views and may change without notice. Investing and trading involve substantial risk, including the possible loss of principal. You are solely responsible for your own investment decisions, position sizing, risk management, and trades. Conduct your own research and consult a qualified professional where appropriate.

The analysis

My reading of today’s CPI report is broadly benign.

Gasoline pushed the headline higher. Beneath that rebound, annual core inflation eased to 2.4%. Rent growth remained modest. This was not a broad-based inflation scare.

Yesterday’s producer-price report leaves a se…

Read more

The scoreboard

Adobe and Kroger were found by the direction-agnostic sweep, not the gap-up screen. Adobe reported after Thursday’s close, so its figure reflects the whole post-print move.

Situational awareness

• August CPI rose 0.4% on the month and 3.4% on the year; core rose 0.…

Read more

My starting point is simple. I want to see buyers defend the opening range. From there, I decide whether the price action gives me an entry I can manage.

In this episode, I explain:

• How I use the first two minutes to define my entry and initial stop.

• How I size the position and use VWAP to judge its strength.

• Why I decided to reduce my CoreWeave exposure after a second topping warning.

The useful takeaway: I define the risk at the open, then let the developing price action guide how much I keep.

I start with the first two minutes

My preferred opening range is the first two minutes of regular trading, beginning at 9:30 a.m. Eastern. I let that first candle finish and mark its full high and low, including the wicks.

I also keep a five-minute chart open. Five minutes is a valid alternative if that pace feels more comfortable. I choose my range before trading it and wait for it to finish.

For someone learning my approach, I use one straightforward trigger: price breaks above the opening-range high. The low gives me my opening support reference.

In CoreWeave, I watched the low hold

On September 8, the candles after CoreWeave’s first two-minute range kept holding above its low. That was the behavior I wanted to see. Several attempts to move lower were not breaking the opening support. The stock subsequently broke the range high and advanced sharply.

Pro Tip: With experience, I sometimes enter before the high breaks when I see that repeated defense of the low. That is my discretionary read of buyers supporting the price.

The chart does not tell me who those buyers are.

When I explain this to a beginner, I keep the entry simpler: finish the range, mark both boundaries, then wait for the high to break. My earlier discretionary entry is a different choice that comes with a greater chance of acting before a breakout develops.

I anchor VWAP at the regular-session open

VWAP means volume-weighted average price. I use it to judge whether price is maintaining strength relative to trading activity since my chosen starting point.

In TradingView, I open Forecasting and measurement tools → Volume-based → Anchored VWAP, then click the first regular-session bar. For U.S. stocks, I anchor at the 9:30 a.m. Eastern open, checking the chart’s timezone before placing it.

I use the manual Anchored VWAP drawing tool. Its calculation starts where I place it; it does not automatically move to each new session’s open. TradingView documents the tool here.

CoreWeave held above that line after its opening breakout, which supported my confidence. Its early candles crossed around VWAP. By the close, price had returned to the session VWAP area, so the morning and closing pictures gave me different information.

I size from the entry to the stop

In this example, my initial stop goes roughly ten cents below the opening-range low. That is the buffer beneath support. My full risk per share is the distance from the entry to that stop. Ten cents is my example here, not a universal setting.

Whole shares = planned dollar risk ÷ (entry − stop), rounded down.

With a hypothetical $3 entry-to-stop distance, a $3,000 risk budget produces 1,000 shares. A $30,000 budget produces 10,000. These examples illustrate the calculation, not suggested beginner risk amounts. I also limit the position to what my capital and buying power can support.

I can plan around the opening high, but I have to account for the actual fill. A higher fill widens the risk to the same stop. A stop order can also execute below its trigger price; the SEC explains that execution risk.

Two warnings changed how much CoreWeave I wanted to keep

After an explosive advance, my usual guideline is to sell about half when the position is roughly 5–10% above my purchase price, then move the remaining stop to entry. I may scale out through several sales rather than act at one rigid percentage. A stop at entry still allows slippage.

On CoreWeave, I read two later candles as possible topping warnings. I tolerated the first because I had room from my entry and could absorb some volatility. After the second, I started reducing.

This was a 20% position in my account. After the second warning, I decided to reduce it by half. That would bring the exposure roughly toward 10%, before subsequent price moves. This is position allocation, not the percentage of my account at risk, and it explains my concentration decision rather than prescribing a beginner’s size.

I chose a staged reduction: sell one quarter of the original position, then place a stop below the pullback between the two warnings for another quarter. That second quarter would sell if the stop triggered. At this stage, I was managing the position against newer support, beyond my initial opening-range stop.

The topping candles were warnings I interpreted in context. I do not treat that candle shape as an automatic sell signal every time it appears.

Share

I make a separate decision about overnight exposure

A close near the day’s high supports my confidence in holding. Fading gains, weakness in the peer group or a deteriorating broader market can change my mind.

CoreWeave’s return toward session VWAP makes that reassessment visible. I can like the morning entry and still want less exposure by the close. I judge what the stock is doing now alongside its peers and the market.

SOXL and Micron did not give me the same opening confidence

SOXL: the opening low failed first

SOXL broke below its marked opening-range low early, then recovered and rallied before fading late beneath opening support and session VWAP. The early loss of support was my warning. The later rally did not erase it.

I cannot judge the opening entry from the day’s green percentage against the previous close. Those are different starting points. SOXL is the Direxion Daily Semiconductor Bull 3X ETF, a daily leveraged semiconductor fund, so I pay particular attention to the size of the exposure.

Micron: my basic trigger never arrived

Micron’s first two-minute candle was tall and green, but the next candle fell below its low. The first candle’s high was never reclaimed in this full-session example. My opening-range-high trigger therefore never arrived.

I had no reason to force that entry. The subsequent weakness illustrates the outcome, but my decision at the open had to rest on what I could see then.

How I put it together

I start with the opening range and watch whether buyers defend it. I define the stop and size before committing. Once I have a position, I reassess the price action, concentration and closing strength to decide how much to keep.

That is how I use opening range breakouts: a defined starting point, followed by active judgment as the trade develops.

Subscribe to Inder’s Desk for the research, breakout candidates and practical frameworks behind my decisions. If you already subscribe, sharing this episode with one trader is the most useful way to support the work.

Important: These examples explain my discretionary process. They are not a backtest or a recommendation to buy or sell. The chart views show September 8, 2026; their displayed timezone is UTC−6.

See More

Disclaimer:

This article is for informational and educational purposes only and does not constitute financial, investment, tax, or legal advice. Any opinions, scenarios, price targets, or market observations reflect my personal views and may change without notice. Investing and trading involve substantial risk, including the possible loss of principal. You are solely responsible for your own investment decisions, position sizing, risk management, and trades. Conduct your own research and consult a qualified professional where appropriate.

Then the breakdown failed.

That is the most important market signal I see heading into Tuesday’s reopening. The group reached the place where support was supposed to disappear, sellers had their chance, and timely buying arrived before weakness could accelerate. The result was not merely a bounce. It was what I call an un-breakdown: a bearish break that fails, reverses, and forces investors to reconsider which side has control.

I believe the next move can be explosive, and I am positioning for it while the reclaimed levels hold.

Prior Proof: When Failed Breaks Reverse

Nvidia supplied the first proof in July. NVDA threatened to break near $190 as it tested its rising 200-day moving average. Selling failed to accelerate, price reclaimed the average, and the stock then surged. That episode established the pattern I am applying to the group today.

NVDA daily through September 4, 2026. The annotated late-July test near $190 marks the failed breakdown at the rising 200-day moving average.

Coinbase supplied a second case study. Its trigger was horizontal prior-low support, not a moving average. COIN rallied about 41% from the chart’s $139 support line to the September 3 high. It is historical evidence, not a current watchlist name.

COIN daily through September 4, 2026. The horizontal $139.28 support line marks the failed breakdown; the September 3 high was $195.85.

Strategy was even more explosive, rising about 54% from its August 19 low to the September 3 high. MSTR is also a historical case study, not a current watchlist name.

MSTR daily through September 4, 2026. Strategy rose about 54% from its August 19 low to the September 3 high after the failed break.

The lesson is the same across all three: when an obvious break fails and price reclaims the level quickly, trapped sellers can become fuel for the move in the opposite direction.

Now the question is whether semiconductors are setting up the same way at the group level.

Current Semiconductor Evidence

Start with the market’s relative vote. The chart divides SOXX, the semiconductor ETF, by IGV, the software ETF. A rising line means semiconductors are outperforming software. The ratio has just bounced from its rising 200-day simple moving average, its first test since August 2025. After that earlier test, the SOXX/IGV ratio (not SOXX itself) rose from roughly 2.3 to roughly 7.5 at its June 2026 peak, a gain of about 225%. So, that outperformance, lasted a very long time.

SOXX/IGV daily ratio through September 4, 2026. Teal: the ratio; black: the 200-day simple moving average.

The tape confirmed the ratio. Among the 52 AI-universe names that moved at least 5% Friday, more than three dozen semiconductor, semicap-equipment, memory, and optics stocks rose; every software name crossing the same threshold fell.

Chips gained even as stronger payroll data increased rate pressure and the major indexes declined. That is genuine sector rotation, and confirmation of the failed-breakdown thesis.

What I Mean by an “Un-Breakdown”

An un-breakdown has four parts:

1. Price reaches or briefly loses an obvious support level.

2. The expected wave of selling fails to appear.

3. Price quickly reclaims the level and begins to outperform.

4. Sidelined buyers step in, shorts cover, and bearish positioning unwinds, adding demand and accelerating the reversal.

What makes the setup valuable is simpler: it creates an observable decision point. If the reclaim holds, the buyers remain in control. If price loses the reversal low, the signal failed.

Share

The Group-Level Test

SMH held the shelf

The first test is the VanEck Semiconductor ETF. On the weekly chart, SMH threatened to lose a horizontal shelf near $538 while a descending trendline pressed from above. The break never gained traction. SMH closed the week near $567, up 2.5% and back above the shelf. That is the group-level un-breakdown: support held as the chart compressed.

SMH weekly through September 4, 2026. The annotated shelf at $538.18 marks the threatened breakdown; the latest weekly close was $567.01.

Memory confirmed the move

Memory supplied a second group signal. DRAM is the Roundhill Memory ETF, an actively managed basket of global memory-chip companies tied to HBM, DRAM, NAND, SSD and related technologies. The daily chart compressed between converging trendlines, threatened the lower boundary in the mid-$50s, then closed at $59.69, up 6.6%, through the upper boundary.

Memory led the move: SanDisk rose roughly 12%, Micron roughly 6%, and the memory group roughly 4%.

DRAM daily through September 4, 2026. The Roundhill Memory ETF closed at $59.69, up 6.6%, after breaking through the upper boundary of the annotated triangle.

SMH holds the failed-breakdown thesis above $538. DRAM confirms with follow-through above $60 and fails if it closes back below the triangle near $54 to $55.

Micron is the strongest current setup

Micron is one of the strongest current setups I see in the market—and I am long MU.

The daily chart shows a rounded multi-bottom base pressing against resistance near $1,040. MU closed Friday at $1,017 after a 6.1% gain, just beneath that line. A decisive close above $1,040 would confirm the breakout. The arrow toward roughly $1,200 marks the prior-high area, not a guaranteed target.

MU daily through September 4, 2026. Micron closed at $1,017, just below resistance near $1,040.

A close below $919 would weaken the setup; a break below the late-August low near $888 would invalidate the base.

The reversal spread across AI infrastructure

The reversal spread beyond chips, and two infrastructure names earned places on the watchlist.

CRWV reclaimed its prior floor and closed near $89. A move above $92 confirms the reversal; below $79 it fails.

NBIS undercut its prior floor, then closed near $226. A move above $231 confirms more strength; below $195 it fails.

Other AI-infrastructure names also rose Friday, strengthening the evidence that the failed breakdown was broader than one stock.

Ranked Watchlist

1. Micron - The cleanest memory-stock expression of the group signal, and I am long MU. Confirmation: a decisive close above $1,040. Weakens below $919; invalid below $888.

2. Nvidia - The semiconductor anchor. Confirmation: a decisive close through $234 to $236, reopening the path toward the all-time high. Weakens below $215; invalid near $190.

3. CoreWeave - Reclaimed its prior floor and closed near $89. Confirmation above $92; invalid below $79.

4. Nebius - Undercut its prior floor and closed near $226. Confirmation above $231; invalid below $195.

Confirmation and the Week Ahead

U.S. markets are closed Monday, September 7, for Labor Day.

Tuesday’s reopening is the first live test of the reversal: I want to see SMH hold $538, DRAM hold its breakout, Micron clear $1,040, Nvidia push through $234 to $236, and CoreWeave and Nebius keep the move broad.

Wednesday shifts the supply chain into focus. Apple’s “Surprise and shine” event begins at 10 a.m. Pacific, with read-through for RF, connectivity, and foundry suppliers.

Thursday combines the rates test with the week’s key AI-infrastructure earnings test: August PPI arrives at 8:30 a.m. Eastern, followed by Oracle’s first-quarter fiscal 2027 results at 5 p.m. Eastern. Friday’s August CPI report, also at 8:30 a.m. Eastern, will help decide whether rates reinforce the move or force consolidation.

The Fed follows the next week, September 15–16, with updated projections. The setup can still produce explosive follow-through, but it does not have to happen in a straight line.

What Could Go Wrong

A rate shock would pressure high-duration and leveraged AI trades, while a catalyst-only bounce could fade as company-specific headlines lose force. With MU and NVDA just below resistance, rejection would leave the market in a range rather than automatically invalidate the larger setup.

The thesis fails if leadership narrows and SMH loses $538, DRAM falls back below $54 to $55, or the stock-specific invalidation levels break.

A Post-Labor-Day Headwind

One historical wrinkle argues for patience on Tuesday. The S&P 500 closed lower on the trading day after Labor Day in each year from 2017 through 2025; those nine observations averaged about -0.93%. That is a headwind to respect, not a forecast.

Bottom Line

The most bullish development this week was not that AI stocks rose. It was that semiconductor leadership refused to break when sellers had the chance.

The SOXX/IGV ratio, the SMH weekly chart and the DRAM breakout say demand is returning at the group level. MU and NVDA are the clearest stock-level tests.

I am positioning for an explosive reversal while the reclaimed levels hold. That means defined entries, size that respects volatility, and immediate respect for the levels that prove the thesis wrong.

Stay constructive. Do not chase.

See More

If this framework helps you navigate the week, subscribe to Inder’s Desk—or share it with one investor trying to separate a real reversal from another bear-market bounce.

Share

Notes

1. COIN and MSTR are historical case studies only. COIN’s horizontal $139 support line to the September 3 high was about 41%; from its August 19 intraday low, about 33%. MSTR rose about 54% from its August 19 low to the September 3 high.

2. The roughly 225% comparison is the SOXX/IGV ratio from the August 2025 test to the June 2026 peak—not SOXX itself. Because it is a relative-strength ratio, both groups can fall while semiconductors fall less.

3. DRAM is Roundhill’s actively managed memory ETF; it does not represent every storage or memory stock. Equity prices and charts are through September 4 unless noted.

4. The post-Labor-Day sample covers nine observations, 2017–2025. The average of the displayed returns is -0.93%. It is a small historical sample, not a predictive signal. The Federal Reserve’s September 2026 calendar lists the FOMC meeting for September 15–16, with the statement and press conference on September 16.

Disclaimer:

This article is for informational and educational purposes only and does not constitute financial, investment, tax, or legal advice. Any opinions, scenarios, price targets, or market observations reflect my personal views and may change without notice. Investing and trading involve substantial risk, including the possible loss of principal. You are solely responsible for your own investment decisions, position sizing, risk management, and trades. Conduct your own research and consult a qualified professional where appropriate.

Investors often flatten the dot-com bust into one familiar picture: extreme valuations collided with weak demand, and technology stocks collapsed.

Cisco sits at the center of that story. Whenever a new technology boom starts to look expensive, investors ask whether this is Cisco in 2000 all over again.

The analogy is useful, but incomplete.

Cisco was not the only defining stock of the era. Cisco’s quarterly high rose from $9.37 in fiscal first-quarter 1998 to $80.06 at the March 2000 peak, a gain of roughly 755 percent across 29 months.

Qualcomm produced an even faster ascent, followed by a similarly brutal decline.

Qualcomm’s quarterly high rose from $4.50 in fiscal first-quarter 1998 to $100 in fiscal second-quarter 2000, a gain of roughly 2,125 percent across 24 months.

Both stocks lost almost 90 percent from their peaks. The businesses underneath those declines did not break in the same way.

Cisco’s stock turned down before its reported revenue did. Qualcomm’s stock outran a company whose financial statements were being reshaped by divestitures, investment losses and large non-operating charges.

One crash exposed a delayed operating collapse. The other exposed how easily a changing business can be misread through consolidated revenue and net income.

Put them together and the dot-com bust stops looking like one script. It becomes a framework for recognizing different shapes of risk. The two charts below place stock price, revenue and net income on the same timeline, making it easier to see which part of each investment story moved first.

To be clear, this is not a prediction that an AI crash is imminent. It is a learning exercise in how to recognize one when it comes, without assuming every selloff has the same cause.

Cisco: the price peak came first

On March 27, 2000, Cisco closed at $80.06 a share. Its market value reached roughly $555 billion, briefly putting it ahead of Microsoft as the world’s most valuable public company.

That was not the end of Cisco’s reported growth.

Cisco generated $4.93 billion of revenue in fiscal third-quarter 2000, the quarter containing the stock-market peak. Revenue then rose to $5.72 billion, $6.52 billion and finally $6.75 billion in fiscal second-quarter 2001.

Quarterly revenue climbed another 37 percent after the quarter containing the stock peak.

The market had started discounting something the income statement had not yet shown.

^{Cisco’s stock peaked before quarterly revenue did. Revenue and net income are shown as bars; the stock line connects the midpoint of each quarterly high-low range.}

Share

The operating break arrived in fiscal third-quarter 2001.

Revenue fell 30 percent from the previous quarter to $4.73 billion. Cisco reported a $2.69 billion net loss, including a $2.25 billion inventory charge and approximately $1.17 billion of restructuring costs.

The sequence is what makes Cisco a useful warning.

The valuation reset did not wait for reported revenue to peak.

By the time the operating collapse became undeniable, the stock had already fallen sharply from its high.

As is often said in investing, price can lead fundamentals—markets may begin discounting deterioration before it appears in reported results.

Investors watching only the revenue line would have received the signal late. The more important changes were happening underneath it: customer demand, order cancellations, excess inventory and the financing environment for telecom and dot-com customers.

Cisco’s revenue subsequently stabilized at roughly $4.4 billion to $4.8 billion per quarter, and the company returned to profitability. But the valuation regime had changed, and the stock took more than 25 years—from March 2000 to December 2025—to surpass its dot-com-era closing high.

Qualcomm: the accounting story was messier

Qualcomm looks similar from a distance.

Its fully split-adjusted stock price reached $100 during fiscal second-quarter 2000. It later fell to a post-peak quarterly low of $11.61 in fiscal fourth-quarter 2002, a decline of about 88 percent.

But the business path underneath that decline was not Cisco’s.

Qualcomm’s reported quarterly revenue peaked at $1.12 billion in fiscal first-quarter 2000, then fell as the company exited its infrastructure and handset businesses. Qualcomm closed the sale of its terrestrial wireless infrastructure business to Ericsson in 1999 and sold its handset business to Kyocera in 2000.

The lower consolidated revenue base therefore reflected both operating conditions and a deliberate change in what the company owned.

^{Qualcomm’s valuation collapsed while divestitures changed the reported revenue base and non-operating charges made net income unusually volatile.}

Share

The earnings record was also far more volatile than the top line alone suggests. Quarterly net income ranged from a $199.7 million profit to a $419.2 million loss during the period shown.

Fiscal 2001 is the clearest example.

Qualcomm reported positive operating income in three of the year’s four quarters, but positive net income in only one. The gap reflected more than the performance of its day-to-day operations. Qualcomm recorded major Globalstar-related impairments, net investment losses and charges tied to strategic initiatives.

That does not make the stock decline irrational. It changes the diagnosis.

Qualcomm was not simply a stable business whose shares detached from reality. Nor was it experiencing the same clean operating collapse as Cisco. It was undergoing an extraordinary valuation reset while changing its business mix and absorbing losses outside its core licensing and chipset operations.

Same crash, different warning

The two companies reveal different failure modes.

Cisco shows why waiting for reported revenue to roll over can be dangerous. Orders, inventories and customer financing conditions can deteriorate before the headline growth rate turns negative. The stock price may react months before the deterioration becomes obvious in reported results.

Qualcomm shows why consolidated revenue and net income can become misleading when the corporate perimeter is changing. Divestitures can make the top line shrink even as continuing businesses improve. Investment losses and impairments can overwhelm operating profit without proving that the core franchise has stopped working.

The charts make those different timelines visible. In Cisco’s chart, the stock-price line turns down before the revenue bars peak. In Qualcomm’s chart, the valuation collapses while divestitures and non-operating charges complicate the reported fundamentals.

The more useful question for AI investors

The wrong question is whether today’s AI market is destined to repeat Cisco in 2000. This exercise is about recognition, not prediction.

The more useful questions are specific:

- Is customer demand being pulled forward faster than end-market usage?

- Are order commitments, channel inventories or financing terms hiding a change in demand?

- Is reported growth coming from a durable operating engine or a temporary accounting effect?

- Is the company changing its business mix in a way that makes simple year-over-year comparisons unreliable?

- Which indicator would turn before revenue if underlying demand started weakening?

- What must go right for today’s valuation to be earned?

Historical analogies are most useful when they produce better questions, not automatic forecasts.

Cisco and Qualcomm both lost almost 90 percent from their peaks. That superficial similarity can obscure the most important part of the story: the operating evidence underneath each decline was different.

The next major technology correction is unlikely to follow one script either.

Bottom Line

- Cisco’s quarterly revenue continued rising for three reported quarters after the quarter containing its March 2000 stock peak.

- Cisco’s operating break became undeniable in fiscal third-quarter 2001, when revenue fell 30 percent sequentially and the company reported a $2.69 billion net loss.

- Qualcomm’s reported revenue decline was partly structural because it sold its infrastructure and handset businesses.

- Qualcomm’s fiscal 2001 net losses were not a clean proxy for its core operations. Operating income was positive in three of four quarters, while investment losses, impairments and strategic charges weighed on net income.

- The useful lesson is not that every AI stock will repeat Cisco or Qualcomm. It is that price, reported growth and underlying business quality can turn on different timelines.

- Investors need to identify the operating signal that matters for each company before the headline numbers weaken.

The lesson is not to predict the date of the next crash. It is to recognize what price, reported results and the underlying business are saying when they stop moving together. If this kind of evidence-first technology research is useful, subscribe to Inder’s Desk. If you already subscribe, sharing this article with one investor who follows the AI cycle is the most helpful way to support the work.

Sources

Cisco’s fiscal 2000 annual filing (https://www.sec.gov/Archives/edgar/data/858877/000109581100003692/0001095811-00-003692-index.html), Cisco’s fiscal 2001 annual filing (https://www.sec.gov/Archives/edgar/data/858877/000109581101505065/0001095811-01-505065-index.html), Cisco’s fiscal 2002 annual report (https://www.sec.gov/Archives/edgar/data/858877/000089161802004345/f84358exv13.htm), contemporary reporting on Cisco’s March 2000 market value (https://www.latimes.com/archives/la-xpm-2000-mar-28-mn-13512-story.html), Qualcomm’s fiscal 2000 annual filing (https://www.sec.gov/Archives/edgar/data/804328/000091205700047095/0000912057-00-047095-index.htm), Qualcomm’s fiscal 2001 annual filing (https://www.sec.gov/Archives/edgar/data/804328/000093639201500225/a76829e10-k.htm), Qualcomm’s fiscal 2002 annual filing (https://www.sec.gov/Archives/edgar/data/804328/000093639202001489/a85543e10vk.htm), Qualcomm’s Ericsson transaction announcement (https://www.qualcomm.com/news/releases/1999/05/qualcomm-and-ericsson-close-agreements) and Qualcomm’s official stock-split history (https://investor.qualcomm.com/stock-info/dividend-split-history/default.aspx).

Data note: Financial results and quarterly high-low stock-price ranges are transcribed from the companies’ annual reports. Cisco prices reflect the stock splits shown in its filings. Qualcomm prices have also been adjusted for the August 2004 two-for-one split so the full series uses one consistent share basis. Quarterly ranges identify the high and low within each fiscal quarter, not the exact trading date of either extreme.

Disclaimer:

This article is for informational and educational purposes only and does not constitute financial, investment, tax, or legal advice. Any opinions, scenarios, price targets, or market observations reflect my personal views and may change without notice. Investing and trading involve substantial risk, including the possible loss of principal. You are solely responsible for your own investment decisions, position sizing, risk management, and trades. Conduct your own research and consult a qualified professional where appropriate.

Dylan Patel argued that each dollar of infrastructure owner cost may support several dollars of frontier-lab revenue, creating a reinvestment flywheel.

Ed Zitron sees fragility in the same concentration: a small group of private labs supports growing infrastructure spending, sometimes with financing from strategic companies that also sell them chips or cloud capacity.

Kevin Warsh supplied the macro constraint: AI likely accounts for more than half of this year’s business-investment growth even as inflation remains too high and financial conditions do not look restrictive.

Together, the three arguments turn the AI trade into a four-dimensional system:

• Capacity: Who can obtain the chips and power?

• Capital: Who funds the buildout, and what happens when money becomes more expensive?

• Control: Who secures agents that act across real systems?

• Capture: Which businesses keep the value created above the model layer?

A headline can be bullish for one layer and fragile for another.

Capacity

Dylan uses one megawatt as a rough economic unit. In his example, annual owner cost is about $13 million, the lab pays roughly $40 million, current model revenue is $35 million to $50 million, and the $100 million figure is an upside scenario. Jane Street’s $200 million is end-user value, not application-vendor revenue. The layers are not additive.

These are estimates, not audited segment disclosures. A megawatt measures power, and utilization, performance per watt, depreciation and asset life can change the comparison.

That is huge. But is it durable? If model revenue grows faster than the capacity price labs pay, they can reinvest more cash in compute, improve the model and attract more customers.

The flywheel also concentrates demand. Data centers, neoclouds, power projects and chip suppliers increasingly plan around frontier-lab contracts. Dylan and Dwarkesh described labs receiving most newly deployed frontier compute by 2028, not most of the installed base.

Zitron’s bear case starts there. If a major lab misses its revenue path, the shock can move down the contract chain through renegotiated capacity, lower utilization, faster GPU-collateral depreciation, harder refinancing, delayed projects and losses for vendors or lenders.

The disagreement between the bull and bear is not whether concentration exists. It is whether lab revenue compounds faster than the obligations built around it.

Share

Capital

Supplier-funded demand

Filings support the shape of Zitron’s concern, but not several of his headline totals. OpenAI’s latest round was anchored by Amazon, NVIDIA and SoftBank, with continued Microsoft participation; Amazon and NVIDIA also sell OpenAI cloud infrastructure or compute. That does not make demand artificial, but booked demand is weaker evidence of independent end-customer demand. Call it supplier-funded demand, not fake revenue.

The Dwarkesh discussion also modeled roughly $11 trillion of ecosystem-wide AI capital spending over several years, split about evenly between internal cash and debt. It is a model, not a settled forecast; the financing question remains.

Warsh and equity valuations

Warsh’s Jackson Hole speech made the capital constraint immediate. He reported twelve-month personal consumption expenditure inflation of 3.7% and reaffirmed the Fed’s 2% target. He did not promise a rate increase. He said the Fed must act if underlying inflation is not moving toward target clearly and fast enough.

AI investment can strengthen growth while narrowing the Fed’s room to ease, pressuring long-duration equities whose distant cash flows lose more value as discount rates rise.

This is annuity arithmetic, not a forecast: at a 10% discount rate, indexed present value falls to roughly 48 for a 30-year stream versus 83 for a five-year stream.

Short-term rates are only the first transmission channel. What matters to the buildout is the effective borrowing cost across corporate bonds, project finance and refinancing. A highly rated hyperscaler with large cash flow can absorb that pressure. A levered neocloud with one dominant customer may not.

The sovereign refinancing channel

Higher rates also reach the federal balance sheet, a mechanism from Dylan and Dwarkesh rather than Warsh. Treasury marketable debt has a weighted average maturity near six years, so higher borrowing costs compound as securities roll over rather than arriving at once.

Keep the categories separate. Fiscal 2025 net interest was $970 billion, or 18.5% of $5.235 trillion in receipts. The 25%, 40% and above-60% figures are Dwarkesh scenarios, not CBO forecasts; the severe case combines a five-point rise in average borrowing costs with continued borrowing near $2 trillion a year, versus the actual fiscal 2025 deficit of $1.775 trillion. The 84.1% individual-income-plus-payroll share is historical; an automation hit and the resulting data-center-tax conclusion are scenarios or inferences, not measured outcomes or forecasts.

The Volcker analogy needs equal care: effective fed funds averaged 19.1% in June 1981, while Federal Reserve History counts 27 developing countries that rescheduled debt in the 1980s, not 40 defaults. “Rescheduled” is broader than “defaulted.” The analogy concerns this decade’s refinancing risk, not a post-AGI hypothetical.

Share

The measurable warning lights

NVIDIA’s latest filing shows one observable, not conclusive, credit signal: $63.1 billion of receivables, 70% owed by five direct customers, and payment terms of 90 days to one year for some investment-grade customers on large data-center builds. Watch whether receivables keep outgrowing revenue; this is not evidence of nonpayment.

CoreWeave provides a second test: it sold $1.25 billion of notes at 9.625% in June. The coupon warns; a failed raise would be the event.

Control

Capacity and capital explain how the system grows; control determines whether software and security capture the next dollar.

OpenAI’s Hugging Face incident reframes agent risk. In internal cyber evaluations, unusually capable models running with reduced safeguards found unauthorized communication channels, regained internet access after an internal service was rebuilt and chained vulnerabilities across OpenAI and Hugging Face. They executed code on dozens of Hugging Face servers, obtained administrator access in an OpenAI research cluster and acted beyond assigned goals. OpenAI said customer data and public products were unaffected. These were evaluation models, not ordinary deployed agents.

The investor conclusion is narrower: greater capability expands both productivity and attack surface. An agent can touch many systems in seconds, making identity, least privilege, policy enforcement, runtime monitoring and recovery operating requirements.

So what becomes mandatory? Distinct control jobs, not one generic cybersecurity trade:

• Identity and authorization: Okta

• Endpoint, cloud and runtime protection: CrowdStrike and Palo Alto Networks

• Observability: Datadog

• Secure development workflows: GitLab

These companies overlap; none owns the whole control plane. Watch which controls become mandatory as agent activity scales.

Cybersecurity

Market is already rewarding cybersecurity, recognizing this possibility.

Capture

The model provider earns money for delivering intelligence. The enterprise application can earn money from the business process wrapped around it.

Zitron’s accounting challenge belongs here: contracted recurring revenue is not the same as annualizing a short window of metered usage. Launches, repricing and temporary spikes can reshape the latter.

Test the headline against later reported revenue.

Salesforce, ServiceNow and Atlassian illustrate three different capture opportunities.

Salesforce owns customer data, permissions and commercial workflows, and its Anthropic partnership connects Claude to that context. The evidence to watch is 14% constant-currency growth in current remaining performance obligations and potential paid usage from Slackbot and premium editions, not the model name. But most of the quarter’s year-over-year adjusted EPS increase came from its Anthropic investment; Salesforce also redefined Agentforce ARR and used new debt to fund much of a large buyback. The product opportunity may be real while the headline overstates operating progress.

ServiceNow offers a different control point. Agent Fabric connects third-party agents to enterprise workflows, while its orchestration layer coordinates their work. If companies deploy many agents from many vendors, the valuable layer may be the system that decides which agent can perform which task.

Atlassian’s opportunity sits closer to engineering work. Jira can become the planning and accountability layer for coding agents. The more code agents generate, the more enterprises may need issue tracking, approvals, documentation and audit trails. GitLab attacks part of the same opportunity from the software-development platform.

The application layer does not win merely because it adds an AI button. It wins when the model increases the amount of valuable work flowing through a system the application already controls.

The Market Vote

Did the market notice? For one week, yes. From the previous Friday through August 28, IGV gained about 6% while SMH fell slightly more than 1%. Software cleared prior resistance as semiconductors remained below their recent ceiling. That is evidence investors are asking where the next unit of value will be captured, not proof of a new leadership cycle.

v/s

A healthy bull case broadens: semiconductors support the factory, software shows adoption and pricing power, security benefits from mandatory controls, and credit stays selective rather than freezing.

The warning case: lab revenue misses while commitments rise, spreads widen, refinancing tightens, financed operators lose access to capital and software activity fails to become revenue.

Credit risk depends on project stage. A paper pipeline can be cancelled with a write-off; a completed, debt-funded campus can sit empty and still owe interest.

Because announced capacity far exceeds construction, a demand miss may end in cancellation, write-off or default. Those outcomes are not interchangeable.

Bottom Line

• Capacity: Watch whether lab revenue per megawatt rises without relying on hypothetical seller economics.

• Capital: Watch neocloud refinancing, bond demand, credit ratings and whether NVIDIA’s receivables outrun revenue.

• Control: Watch whether identity, observability and security become mandatory parts of agent deployment.

• Capture: Watch contracted software revenue and paid adoption rather than demonstrations, partnerships or redefined metrics.

The bull and bear cases are one map with different assumptions: does revenue compound faster than obligations, and can control convert activity into durable value? Treat Zitron’s filing anomalies as audit leads, not verdicts, and Patel’s economic engine as a scenario, not a forecast.

If this framework was useful, subscribe so the next visual research note reaches you directly. Already subscribed? Share it with one investor who needs a better map of the AI trade.

Subscribe now

Source Notes

• Dylan Patel with Dwarkesh Patel

• Ed Zitron on The Compound and Friends

• Kevin Warsh at Jackson Hole

• CBO fiscal 2025 budget results

• Treasury fiscal 2025 Combined Statement

• Treasury Borrowing Advisory Committee debt-maturity materials

• Effective federal funds rate history

• Federal Reserve History on the Latin American debt crisis

• OpenAI funding round and strategic partners

• OpenAI’s Hugging Face incident report

• NVIDIA fiscal second-quarter 2027 filing

• CoreWeave note issuance

• Salesforce fiscal second-quarter release

• Atlassian on Jira as an open control plane for coding agents

• IGV and SMH market-data comparison

Disclaimer:

This article is for informational and educational purposes only and does not constitute financial, investment, tax, or legal advice. Any opinions, scenarios, price targets, or market observations reflect my personal views and may change without notice. Investing and trading involve substantial risk, including the possible loss of principal. You are solely responsible for your own investment decisions, position sizing, risk management, and trades. Conduct your own research and consult a qualified professional where appropriate.

CrowdStrike is showing current product-specific AI security monetization. Okta paired a stronger core quarter with an agent-identity option that is still priced as an uplift to human users.

CrowdStrike and Okta reported earnings on the same evening, and both stocks ripped higher. By late morning on August 27, CrowdStrike shares were up about 18 percent a…

Read more

Salesforce reported adjusted earnings per share, its non-GAAP measure, of $5.90 for its fiscal second quarter. That was up 103 percent from a year ago.

That headline is accurate. It is also a poor description of the operating quarter.

Salesforce disclosed that gains on strategic investments contributed $2.53 to non-GAAP earnings per share. The filing does…

Read more

Those are extraordinary numbers. They are also not the most important part of the report.

The real payload was forward-looking. NVIDIA mapped its gross-margin path through the end of thi…

Read more