● Trump AI Order, Fed Rate Cut, Tesla Unleashed
Trump’s AI Executive Order + a Fed Rate Cut Hit at the Same Time: Why the “Rules That Held Tesla Back” and the “Valuation Framework for Growth Stocks” Are Shifting Together
In today’s post, I’ll summarize in a news format: ① the core of Trump’s AI executive order (not “deregulation,” but “unification of regulation”), ② the structural effect a Fed rate cut has on growth stocks/Tesla, ③ the real impact of a “single nationwide rule” that emerges for robotaxi expansion, ④ why the Samsung–Tesla AI6 chip alliance is more than a simple foundry order, and ⑤ the essence of Rivian’s surge (hope vs. cash runway).
And at the very bottom, I’ll separately extract and organize only the “most important points” that other YouTube channels/news often fail to highlight.
1) Today’s Key Headlines (News Briefing)
1-1. [Macro] A Fed Rate Cut → The “Ceiling” on Growth-Stock Valuations Rises
A Fed rate cut isn’t just “good for stocks” in a general sense; it lowers the discount rate applied to the present value of future cash flows (especially for companies where cash flows 3–7 years out are large).
In other words, companies that “earn big in the future” get more breathing room than companies that make money right now.
Tesla can sometimes look like a cyclical stock if you view it only through EV sales, but what the market truly prices in are long-dated “options” like autonomy (FSD) · robotaxis · robots (Optimus) · AI chips.
Falling rates increase the value of those options, which works in favor of growth stocks like Tesla.
1-2. [Policy] Trump’s AI Executive Order → Closer to “Align 50 States’ Rules into One” Than “Loosen Regulations”
The core of the original text is this.
Right now, the U.S. has different AI-related laws/guidelines by state, so from a company’s perspective, it becomes a regulatory maze: “50 states = 50 versions of regulation.”
Trump’s executive order reads as an attempt to shake up that structure itself.
- Attorney General: State-law response task force
- Department of Commerce: Compile a list of problematic regulations
- Possible limits on federal funding: A pressure card that says, “If a state government directly clashes with the federal direction, the cost goes up.”
Why this matters so much for Tesla is that Tesla’s FSD/robotaxi vision is “general-purpose autonomy that can drive anywhere,” but if rules differ by state, the speed of expansion keeps getting hamstrung.
1-3. [Competition] Rivian Stock Surge: A Premium for “Announcing In-House Autonomy” vs. the Reality of “Cash Runway”
The reason for Rivian’s surge is less a simple technical rebound and more that the market priced a premium into its decision to pursue autonomy on an independent path rather than outsourcing.
These days, autonomy isn’t just a feature; it’s a competition of platforms (data + chips + software), so the very act of declaring in-house development has become rarer.
However, as the original text pointed out, even with cash on hand, if quarterly cash burn (burn rate) is large, it becomes “a game without much time.”
Autonomy R&D is hard to pause once started, so the view that the outcome could be decided within 3–4 years is persuasive.
1-4. [Robotaxi] A “Model S + LiDAR Equipment” Test Spotted in California: A Premium Robotaxi Scenario?
Tesla has mostly used the Model Y for robotaxi testing, so spotting a Model S carries symbolic weight.
There are two main possible interpretations.
- Experimenting with a premium robotaxi lineup: Designing a revenue model that separates “base vs. premium,” like Uber Black
- Short-term testing for sensor/validation data: Data comparison/verification for specific driving environments
The key point is that it can be read as a signal that Tesla is designing robotaxis not as “a service that ends with one car model,” but as a scalable platform.
1-5. [Semiconductors/Supply Chain] Lee Jae-yong–Musk Meet at Texas Foundry + Reports of Requesting a “Musk-Dedicated Space”
The strongest signal in the original text appears in this part.
- Location: Taylor, Texas (Samsung’s new plant) + proximity to Austin (Tesla HQ)
- Scale: AI6 chip deal around $16.5 billion (per the original text’s claim)
- Point: Not just contract manufacturing; Tesla appears to want to directly control manufacturing/processes on site
What this implies is that Tesla sees the bottleneck for FSD/robotaxis/Optimus in “chip supply stability,” and it can be interpreted as a strategy to grip the U.S.-based supply chain more tightly.
From Samsung’s perspective, having a “mega reference customer (Tesla)” is a very powerful card for persuading other big-tech customers.
2) Why Trump’s AI Executive Order Is “Truly” Important for Tesla
2-1. Not Deregulation, but “Regulatory Unification” Is the Game Changer
Many interpretations stop at “autonomy regulations will be loosened,” but the more important point is that if rules converge into one, companies can optimize development/validation/expansion around a ‘national standard’.
Even if regulation is strict, if it’s “one,” the industry grows.
Conversely, even if regulation is loose, if it’s “split into 50,” expansion slows down.
2-2. Paradox: A Single Federal Regulation May Not Benefit “Everyone,” but Could Favor Only a Top Few
This is the point the original text called “only half-correct” in common interpretations.
If a single federal regulation emerges, it’s likely to demand more than vague guidance; it may require the following.
- Data structures that can explain liability in the event of an accident
- Log/audit systems that can trace decision processes
- Systems that can be immediately fixed via OTA updates when issues arise
- Standardized processes for data consistency/validation
These requirements disadvantage companies that “stitch together outsourced software from various places.”
By contrast, vertically integrated structures like Tesla—where hardware, software, data, and update responsibility sit within one company—become stronger.
2-3. Musk’s “P&L Calculation” for Supporting Trump May Be About Autonomy Expansion Rights, Not EV Subsidies
On the surface, Trump’s policies can look unfavorable to Tesla due to EV subsidy cuts, etc.
But if you shift the perspective, subsidies are variables that affect short-term quarterly sales, while a single nationwide rule for autonomy regulation is a variable that changes the size of Tesla’s market itself.
If you assume Tesla’s big payoff comes not from being “a company that sells cars,” but from a world where a “robotaxi/autonomy network” opens up, policy priorities look different.
3) Reframing from an Investment/Industry Perspective: The Changes That Happen “Because They Hit Together”
3-1. Rate Cuts (Cost of Capital ↓) + Regulatory Unification (Expansion Cost ↓) = Higher Expected Value for Robotaxi Expansion
The key to this issue is that these two news items are not “separate.”
Rate cuts create a favorable environment for growth stocks, and AI regulatory unification simplifies the path for autonomy expansion.
In other words, when valuation (the price of money) and regulation (the road for the business) move at the same time, the market tends to price the story bigger.
3-2. The “Barrier Holding Tesla Back” Was More About the Regulatory/Validation Framework Than a Sales Slowdown
Tesla’s short-term results can wobble, but what the market is most sensitive to is “whether robotaxis can be designed on a nationwide basis.”
If the state-by-state regulatory maze is resolved, the blueprint for robotaxi scale-up becomes much clearer, and from that moment, it may become harder for competitors to catch up.
3-3. If You Also Connect the Semiconductor Supply Chain (Samsung Foundry), Tesla Gains a Pretext to Increase “Expansion Speed”
Autonomy/robots are ultimately a compute race, and compute is ultimately a fight over chips/process nodes/yield/supply chains.
If policy (regulatory unification) + capital (rates) + supply chain (chips) align in one direction, Tesla gains “justification” to move to the next stage.
4) Only the “Most Important Content” That Other YouTube/News Often Don’t Mention, Organized Separately
- Point 1) Single federal regulation is not “relaxation,” but “standardization.”
The market’s misconception is “regulation easing = freedom,” but in reality it’s likely to move toward “national standards = stronger requirements for audits/liability/logs/OTA systems.”
This may not be a policy that helps small players; it can become a structure that pushes forward a prepared few. - Point 2) State-level regulatory sprawl is, before “safety,” a problem of “expansion cost.”
For robotaxis, operations (insurance/liability/logs/data submission/audits) often become the bottleneck more than the technology itself; if it differs by state, expansion speed slows sharply.
It was especially fatal because what Tesla wants is “general-purpose that can drive anywhere.” - Point 3) The benefits of rate cuts come less from “EV sales” and more from the “robotaxi option value.”
If you focus only on short-term sales indicators, interpretation goes off track.
The essence of growth-stock valuation is future cash flows, and Tesla has a high share of that. - Point 4) The Samsung–Tesla alliance is not a simple order, but a battle for “on-site control rights.”
If it’s true that Musk requested a dedicated space inside the factory, it signals not a customer who merely receives deliveries, but an intent to hold the process/validation/mass-production cadence together.
In the autonomy/robot era, this control is speed. - Point 5) Rivian’s in-house autonomy is not a “technology challenge,” but may be a “fundraising card for survival.”
In-house development is cool, but it burns money.
What the market rewarded with a higher stock price may not be confirmed “success,” but the expectation that the door opened for the “next-round investment story.”
5) Keywords That Naturally Connect From Today’s Post (SEO Points)
This issue is a topic that can attract search traffic when viewed alongside macro keywords like U.S. rate cuts, inflation, recession, AI semiconductors, and USD exchange rates.
In particular, “autonomy regulatory unification” is highly likely to keep coming up, so it’s good to steadily accumulate related keywords.
< Summary >
A Fed rate cut increases the long-dated option value of growth stocks (Tesla).
Trump’s AI executive order is less about deregulation and more about “unifying the patchwork of state-level regulations.”
A single federal regulation could instead favor a small number of players that already have data/liability/log/OTA systems in place.
Model S robotaxi testing is a signal of either premium service or validation-data purposes.
The Samsung–Tesla AI6 alliance is not an order; it’s securing a U.S.-based AI chip supply chain/on-site control.
Rivian’s surge is an in-house premium, but depending on cash burn, the outcome could be decided within 3–4 years.
[Related Posts…]
- How Tesla’s Robotaxi Expansion and Autonomy Regulatory Changes Affect the Stock Price
- Why Growth Stocks and AI Semiconductors Strengthen During a Rate-Cut Cycle
*Source: [ 오늘의 테슬라 뉴스 ]
– 트럼프 AI 행정명령 통과 이후, 연준 인하까지 겹치며 테슬라를 막던 규칙과 판이 동시에 흔들리기 시작했다 !?
● US Stocks Flash Red, AI Profit Fear, Yield Spread Shock, Liquidity Crunch, Yen Carry Unwind
U.S. Stocks: Multiple “Bad Signals” Hit All at Once—AI Earnings, Rate Spread, Liquidity, Even the Yen (and the Next Scenarios)
Looking at the U.S. stock market these days, the key point isn’t just “a correction could happen,” but that several correction triggers are overlapping at the same time.
In today’s post, I’ve organized the following points all in one place.
① A pattern where the “second tier” within AI leaders collapses first
② Why a “seizure” in the 10Y–3M rate spread is dangerous (and how it has repeated in the past)
③ What it means that Fed liquidity (reserves) is at the lowest zone
④ How a Japanese rate hike → yen carry unwind risk affects U.S. tech stocks
⑤ Portfolio actions investors can actually take in practice—instead of “sell everything / buy everything”
And at the end, I’ll separately summarize the truly important points that news/YouTube often don’t cover.
1) (News Briefing) AI-Related Stocks Plunge: Not “Panic Selling,” but a “Profitability Doubt” Signal
Key summary
Oracle (-10%+) → Broadcom (-11%+) → even Nvidia (-3%) wobbling,
signals that the market has started to question again whether the AI rally’s core is actually “making money.”
1-1. What fell: The classic pattern where the “AI second tier” cracks first
It’s easier to understand if you roughly divide the AI ecosystem into three layers.
– Layer 1 (strongest cash generation · defensive): Big-tech cores like Microsoft and Alphabet
– Layer 2 (investment stamina can weaken · debt burden can grow): Oracle, Broadcom, Meta (relatively heavier investment)
– Layer 3 (theme/valuation sensitive): high-P/E software and small/mid-cap AI momentum names
This time, it wasn’t fear where “everything drops together,” but a differentiation where Layer 2 breaks first—that’s the point.
1-2. The Oracle issue: “AI investment costs exploding + pulling spending forward with debt”
The most important message in the original was this.
Oracle isn’t generating cash flow at a big-tech level, yet it is aggressively expanding AI investment (data centers/infrastructure),
and that burden is likely to lead to increased debt.
In other words, the market has started focusing less on “AI will grow” and more on “who bears the cost of that growth, and how they can endure it.”
1-3. The impact of Broadcom’s remarks: “AI revenue, margins are lower than expected”
Broadcom’s CEO delivered a message that’s pretty painful from an investor’s perspective.
– Even if AI revenue grows quickly, gross margins are lower than expected
– Deferred the release of a 2026 AI revenue forecast (= delaying conviction)
This isn’t just an earnings comment—it hits the word investors hate: “monetization uncertainty.”
Whether the AI bubble “bursts hard” or “deflates mildly” ultimately comes down to margins and cash flow.
1-4. Why the ones that held up actually held up
It’s paradoxically understandable that Apple held up relatively well.
– Limited intensity of AI investment (= lower CAPEX burden)
– Companies with strong funding capacity/cash flow are more likely to become “safe havens” in a correction
What the market is saying here is simple.
It’s not “not doing AI,” but rather repricing the balance between under-/over-investing in AI.
2) (Macro) Another “Seizure” in the Rate Spread: Not Just a Number, but a “Bond Market Warning Light”
The spread here is typically described as the 10-year Treasury yield minus the 3-month yield,
and the original point is that the issue isn’t the level itself, but the sharp, spiky “seizure” over a short period.
2-1. Why it’s dangerous: Rate cuts but the 10-year jumps = the market fears something else
This is where retail investors often get confused.
If the Fed cuts rates but the 10-year yield rises,
the market is usually suspecting one of the following.
– Inflation re-accelerating (or rising inflation expectations)
– Fiscal/Treasury supply burden (bonds get dumped → yields rise)
– Weakening policy credibility (why people call it a “bond market seizure”)
In other words, it may not be the “easing” that’s good for stocks, but an instability where bonds are getting uneasy.
2-2. Past pattern: “Corrections within 1–2 months after a seizure” repeated many times
The original explains that in the five-year post-COVID period, this kind of seizure signal appeared multiple times,
and correction/crash events often followed within 1–2 months.
This doesn’t mean it’s 100% accurate,
but rather that it should be viewed as a warning light where the “hit rate” rises when leverage/credit/theme exposure is high.
3) (Liquidity) Fed Reserves at a 4-Year Low: “Stocks Struggle to Fight Liquidity”
The most practically useful sentence in the original was this.
“Instead of asking others whether you should buy stocks now or not, you can look at liquidity and enter based on that.”
3-1. What does it mean that reserves are low?
After a large portion of the liquidity unleashed during COVID was absorbed into stocks/real estate/commodities,
the recent four-year context may indicate a period where the ‘extra cash cushion’ inside the financial system has thinned.
In such times, even small shocks (a sudden rate spike, geopolitics, policy variables) can more easily increase volatility.
3-2. Investment takeaway: “If you see a liquidity expansion event, it’s an opportunity; otherwise, defend”
– If there’s a clear event that increases liquidity in 2026 → a correction could become a “buying opportunity”
– If it feels like we’re moving into a phase where liquidity keeps shrinking → defensive allocation adjustments are advantageous
What matters here is not the direction, but the cycle.
4) (Technical + Sentiment) More Important Than a “Double Top” Is “Whether There’s a Next Catalyst”
A double top (or triple top) isn’t automatically the right answer,
but the key point the original made isn’t the technical pattern itself; it’s this.
After a big move, a rebound comes—but to turn that rebound into a “breakout,” you need reinforcements (good news/catalysts)
4-1. Why is prolonged sideways action risky?
A bull market is sustained only when “new money (new buying)” comes in.
But if it goes sideways for months, new participants decline,
and in a sell-buy balance state, even a small negative headline can break the balance downward.
5) (Global Variable) Possible Japanese Rate Hike → Yen Carry Trade Unwind Risk
In the original, the variable mentioned for next week was the Japanese rate hike issue.
What does this have to do with U.S. stocks?
It’s because the capital flow of borrowing cheaply in yen (low rates) and investing in dollar assets (U.S. stocks, etc.) could be shaken.
5-1. The point is not the “absolute rate,” but the “rate of change”
Even if Japan’s rate rises only from 0.5 to 0.75,
the market feels it not as “0.25%p,” but more like a 1.5x increase.
From that moment, some capital can shift to “Should we start considering unwinding the carry?”
and it becomes even more sensitive when liquidity isn’t ample.
6) (Practical Investing) What’s Needed Now Isn’t Prophecy, but “Position Sizing” and “Insurance”
The direction the original points to is exactly this.
“This isn’t a signal telling long-term high-quality stock investors to sell everything, but risky investors should be careful.”
6-1. Realistic actions under a correction scenario
– Reduce leverage/margin exposure (it gets liquidated first in seizure phases)
– Trim theme/speculative positions and re-align the portfolio toward cash, bonds, and high-quality stocks
– After declines progress sufficiently and “new catalysts (reinforcements)” appear, then increase equity exposure
6-2. Why you also need to watch the U.S. dollar/exchange rate
The original also mentioned the move where the exchange rate spikes (KRW/USD rising).
When FX becomes unstable, for overseas stock investors,
– FX loss/FX gain volatility expands
– Dollar strength can attach itself as a risk-off signal in some cases
so don’t look only at stocks—watch the “dollar” too.
7) The “Most Important Points” That Other News/YouTube Often Don’t Cover (My View Summary)
Point A. The essence of this decline is not “AI growth,” but a repricing of “AI profitability (margins/cash flow)”
Most people say “AI has rolled over,” but more accurately,
the market is shifting toward “the cost structure of AI investment is heavier than expected.”
In a growth-stock regime, the scariest thing isn’t slowing revenue—it’s margin disappointment.
Point B. It’s not “big tech is safe,” it’s that the “capital funding structure” is safe
It’s not “they’ll hold up no matter what because they’re big tech,” but rather,
– Can they fund CAPEX with internal cash?
– Are they not in a structure of pulling spending forward with debt?
This difference creates a stamina gap during corrections.
Point C. A rate-spread seizure signals a “volatility regime shift” before stock direction
This signal isn’t “guaranteed crash,” but more accurately used as a warning that we’ve shifted into a
volatility phase unfavorable to leverage and high-valuation sectors.
Point D. Yen carry risk isn’t a “Japan” issue; it’s a “dollar liquidity” issue
Rather than the Japanese rate hike itself,
if in an already tight liquidity phase a “reason” emerges for funds to pull back,
high-valuation assets like U.S. tech stocks can wobble first.
8) Core SEO Keywords Naturally Checked in This Post (Top Economic Keywords)
U.S. stock market
Nasdaq
Fed interest rates
Treasury yields
Exchange rate
< Summary >
The AI leader sell-off began not from simple fear, but from doubts about “profitability/margins.”
Oracle revealed a structure where stamina relative to investment (debt) is weak, and Broadcom directly mentioned AI revenue margin concerns.
A seizure in the 10Y–3M rate spread is a warning of a volatility regime shift, especially unfavorable to leverage and high valuation.
With Fed reserves at a 4-year low, the liquidity cushion is thin, and the possibility of a Japanese rate hike increases yen carry unwind risk.
Right now, rather than “sell everything/buy everything,” practical answers are portfolio position sizing and insurance (risk management).
[Related posts…]
- Nasdaq volatility expansion phase: a summary of the key indicators to check
- Overseas investment strategy during a rising exchange-rate period (strong dollar): risk management points
*Source: [ Jun’s economy lab ]
– 미국 주식에 등장한 몇가지 안 좋은 신호들
● UGG Booms, Deckers Stock Slumps, Tariffs, Rates, Demand Crash Fears, AI Forecast Lifeline
Why are the “national winter shoes,” UGGs, selling well—yet the stock price has cooled? (Tariffs · Interest rates · Consumer sentiment · AI demand forecasting, all in one)
Today’s article includes these key points.
1) From an investor’s perspective, I’ll break down the classic forward-looking structure of “solid revenue but a falling stock price.”
2) I’ll organize how ‘tariffs’ can go beyond a simple cost increase to undermine pricing power and the inventory cycle.
3) A point that doesn’t get much coverage in the news: UGG’s real competitor isn’t “other boots,” but the consumer’s winter budget (economy · interest rates · inflation) itself.
4) Finally, I’ll connect why the AI trends (demand forecasting · price optimization · inventory optimization) that fashion/retail use the most these days have become so important for brands like Deckers.
1) Today’s news briefing: “UGGs are selling well, but why is Deckers’ stock wavering?”
If I summarize it in one core sentence, it’s this.
“The market is pricing in not today’s results, but next year’s margins and demand slowdown in advance.”
Organizing the facts in a news style based on the original content:
[What’s happening]
On the streets of New York, UGGs are still going strong, and brand popularity remains high.
For Deckers, UGG accounts for a large share of sales, and the running brand ‘HOKA’ is also serving as a growth engine.
[Why the stock still drops]
① As U.S. trade policy changes, the likelihood of a heavier import footwear tariff burden has increased.
② The market is already reflecting a “margin pressure scenario” that could run: tariffs → higher costs → price hikes → weaker demand.
③ With interest rates high and, after inflation, consumption reshuffling toward “essentials first,” there’s also concern that fashion-oriented spending (boots/slippers) could be the first to wobble.
[Where Wall Street is split]
Opinions diverge between “Brand power makes this pullback a buying opportunity” vs. “Tariffs/consumer slowdown haven’t fully hit earnings yet, so it could fall further.”
2) Understanding it structurally: The 3-step logic behind “good results but a falling stock price”
1) The stock market looks more at ‘next quarter to next year’ than the ‘present.’
The fact that UGGs are selling well this winter is close to a “confirmed number.”
What moves the stock price is: “Can they keep selling just as well next year while maintaining profit margins?”
2) Tariffs don’t stop at being a cost issue; they become a test of pricing power.
If tariffs raise costs, there are three choices.
① The company absorbs it by cutting margins → profitability declines
② Raise consumer prices → risk of slowing sales volume
③ Change the cost structure (production/logistics/sourcing) → time and expense required
In other words, tariffs grow from “this quarter’s cost” into a much bigger issue: proving “how expensively the brand can sell.”
3) Fashion footwear is the “first spending to cut” when the economy slows.
This is the real point.
UGG’s competitor isn’t “another boot brand,” but the consumer’s “leftover wallet” this winter.
In a high-rate environment, when installment/card interest burdens rise, a $190 pair of boots feels even more expensive.
3) Checkpoints that matter more than the numbers: Why UGG’s ‘seasonality’ looks like risk again
The fate of a seasonal brand is “inventory.”
Once winter ends, the window of time in which you can sell is limited.
If demand forecasting misses, inventory piles up, discounts (promotions) increase, and that immediately erodes margins.
The “four-season expansion (slippers/loafers/sneakers)” mentioned in the original piece is directionally right, but the market is more ruthless.
An expansion strategy can raise valuation if it succeeds, but
the moment success becomes ambiguous, it can be interpreted as “brand identity dilution + increased inventory complexity.”
4) Why the other engine, ‘HOKA,’ is a stock-sensitive point
From an investor’s standpoint, Deckers essentially looks like a two-track story: “UGG (winter lifestyle) + HOKA (running/performance).”
What matters here is that the market has already priced a good portion of HOKA’s high growth into the stock.
So the moment HOKA’s growth rate slows
it can be read as “UGG faces tariff/consumer slowdown worries, and HOKA is also slowing,” compressing the multiple (valuation).
5) (A key point that other news/YouTube rarely covers) The real essence of tariff fear is not ‘price increases’ but a ‘kink in the demand curve’
Most people only talk up to “tariffs raise costs.”
What the market (the stock price) fears more is this.
“Is UGG a brand that consumers will ‘just accept’ after a price increase?”
UGG clearly has brand power, and in winter there’s an area where substitutes are ambiguous.
But after inflation, consumers move much faster toward “the cheaper option if it looks similar.”
In other words, a 10–15% price hike could become an inflection point where it’s not “revenue holds,” but “unit volume drops sharply”—and that’s the core risk.
6) From a global economic outlook: If you view the UGG issue through macroeconomics, it looks like this
① Post-inflation shifts in consumption patterns
Once prices rise, consumption becomes “rationalized,” and impulse buying decreases.
② The felt economy at peak-rate levels
Even if nominal income rises, if interest costs rise, consumers’ spending capacity shrinks.
③ The re-emergence of tariffs/supply-chain issues
Supply-chain risk often “suddenly” returns as the market’s main theme.
Especially for industries like footwear/apparel with high overseas production exposure, the impact hits immediately.
The five economic keywords you should naturally watch alongside this article are exactly these.
Interest rates / inflation / recession / tariffs / U.S. consumer
7) From an AI Trend perspective: How ‘AI’ defends stock prices in fashion retail
Now this is the practically important part.
In a tariffs/economic slowdown phase, the performance of fashion companies is determined not only by “brand,” but ultimately by operations.
1) AI demand forecasting ( Demand Forecasting )
The key is to tie together weather (cold snaps/temperature), regional sell-through speed, SNS trends, and search volume to match demand more granularly by SKU (product unit).
Winter items, in particular, turn forecasting misses directly into inventory losses.
2) AI price optimization ( Dynamic Pricing )
“When to discount” isn’t just marketing; it’s margin defense.
Discount too early and you damage the brand; discount too late and inventory turns into a swamp.
3) AI inventory optimization ( Inventory Optimization )
The key is reallocating store/online inventory to match regional demand.
These days, “logistics costs” are also a cost item, so inventory movement itself is a target for optimization.
4) Generative-AI-based product planning/merchandising
Companies that can quickly catch trend signals (color/silhouette/materials) and produce capsule lines or collaborations faster have an advantage.
In summary
In an environment where tariffs raise costs, the battleground is “how much more expensively you can sell” + “how little inventory you leave behind,” and
AI is the tool that boosts execution on both.
8) Investor checklist: From next quarter to next year, what will determine “buying the bottom vs. further downside”?
1) The intensity of price increases (or promotions)
You need to see whether sales volume holds after price increases, or whether the company defends with discounts.
2) Changes in gross margin guidance
Margins are where tariffs/logistics costs/discounting show up all at once.
3) Inventory growth rate
If inventory grows faster than sales, the probability of discount pressure next season increases.
4) HOKA growth rate trends
Because HOKA’s share in Deckers’ growth story is large, market sensitivity is high.
5) The direction of U.S. consumer indicators
In particular, you should watch whether discretionary spending is recovering (apparel/footwear/home goods) alongside the broader flow.
< Summary >
UGGs are still selling well, but the stock is pricing in “next year’s margin pressure from tariffs + a consumption slowdown in a high-rate environment.”
The essence of the tariff issue is not cost inflation, but a test of “pricing power—does demand hold even after raising prices?”
For winter seasonal products, if demand forecasting misses, inventory/discounting immediately damages profit margins.
If signals of HOKA growth slowing appear, stock pressure could intensify.
Going forward, AI capabilities in demand forecasting, price optimization, and inventory optimization will become core to margin defense for fashion/retail companies.
[Related posts…]
- How tariff risk affects U.S. consumer goods companies’ earnings
- Investment strategies for consumer stocks and retail in a peak-rate environment
*Source: [ Maeil Business Newspaper ]
– [어바웃 뉴욕] “전세계 다 신는데” 겨울철 국민 신발 ‘어그’의 식어가는 주가 | 길금희 특파원
