● Warsh Shock Looms, Liquidity Rally vs Volatility Bomb, Six Triggers Ahead
Will the “Warsh Shock” Return? Six Triggers That Simultaneously Increase the Odds of a “Liquidity Rally” and a “Volatility Shock”
This report consolidates three points:
- The core of the debate over whether Kevin Warsh is truly hawkish (and why markets may be misreading the signal).
- Six volatility triggers that can destabilize markets when Warsh emerges (from Senate confirmation to yield-curve dynamics).
- Scenario-based positioning implications for US monetary policy across equities, bonds, the US dollar, and digital assets.
1) Key News Briefing: Why the “Warsh Shock” Emerged
The mechanism was straightforward. Markets had been pricing in a “next Fed Chair = faster rate cuts + liquidity support” narrative. Sentiment reversed when the leading candidate began to be interpreted as the most hawkish option, undermining those expectations.
The immediate outcome was a broad risk-off move, including sharp declines in gold and silver and a correction in equities (risk assets broadly, including the KOSPI). This sequence has been labeled the “Warsh Shock.”
2) Assessing the Claim: “Kevin Warsh Is Not Hawkish”
The hawkish characterization is primarily based on Warsh’s actions and remarks during 2008–2011, when he warned that quantitative easing (QE) could generate inflation.
However, applying that framework directly to the current cycle is not necessarily appropriate.
2-1. The Post-Crisis Response Regime Then vs. Today’s Political, Inflation, and Growth Backdrop
At the time, large-scale easing was unprecedented. Today, policy is still widely viewed as restrictive, with ongoing debate around neutrality and the appropriate level of the neutral rate.
2-2. Recent Assessments: “Historically Viewed as Hawkish, but Now Argues Policy Rates Should Be Lower”
Some institutional commentary emphasizes that while Warsh criticized prolonged QE and was therefore labeled hawkish, more recent statements suggest policy rates should be lower. Markets may be over-weighting the legacy narrative relative to the current stance.
3) Six Primary Volatility Triggers Associated With Warsh (Operational Checklist)
3-1. Trigger #1: Senate Confirmation Risk — Approval vs. Delay as a Volatility Catalyst
The process is: presidential nomination → Senate Banking Committee → Senate floor majority vote. While the party arithmetic may imply approval, conditional stances by key senators and contingent developments (e.g., resolution of sensitive legal or investigatory matters) can alter timing and probability.
Markets tend to react to confirmation signals (e.g., changing positions, compromise messaging, procedural progress) before the final vote. This event risk is more likely to generate positive volatility (risk-on) when probability of approval rises.
3-2. Trigger #2: Powell Remaining on the Board — Potential Continued Influence Over the FOMC
The Chair term and Board Governor term can differ. Even if Powell steps down as Chair, remaining as a Governor would preserve voting influence within the FOMC.
If Powell remains:
- (1) A rapid shift toward rate cuts or broader easing could face internal resistance.
- (2) The timeline for reshaping the Board toward a more dovish composition could extend.
This increases uncertainty around the policy path, raising volatility.
3-3. Trigger #3: AI-Driven Disinflation With Delayed Transmission — Timing Gap Between Narrative and Data
A central argument is: AI adoption → productivity gains → improved supply-side conditions → lower inflation pressure → justification for rate cuts.
The market sensitivity is primarily timing. In the near term, infrastructure buildout and automation-related capex can raise costs before efficiency gains are reflected in CPI/PCE. If disinflation does not become visible in time for key political milestones (e.g., the 2026 midterm cycle), rate-cut expectations can be repriced lower, increasing volatility.
3-4. Trigger #4: Inflation Framing Shift — When “Inflation Is a Choice” Is Credible vs. When It Is Not
Warsh may be interpreted as relatively flexible if markets infer tolerance for inflation modestly above 2% during growth phases.
This stance is conditional:
- If inflation stabilizes in the low-2% range, flexibility can be perceived as policy optionality.
- If inflation re-accelerates toward 3%, the same stance can be interpreted as weakened central-bank independence and implicit tolerance of inflation.
Accordingly, CPI and PCE releases remain the key gating indicators. Re-acceleration would likely undermine rate-cut expectations and pressure risk assets.
3-5. Trigger #5: Constraints on the Speed and Magnitude of Rate Cuts — Expectations vs. Meeting Calendar Reality
Political messaging may favor large and rapid cuts (e.g., targeting rates near the 1% area), while the FOMC is constrained by meeting frequency and the convention of 25 bp increments.
If the number of meetings ahead of key political dates is limited, delivery may fall short of market expectations. Each incremental gap between expectation and realization can amplify repricing episodes.
3-6. Trigger #6: Yield-Curve Steepening — Widening Term Spread as a Core Risk Signal
This is a central risk channel. Short-term yields can decline quickly on rate-cut signals. Long-term yields incorporate inflation risk, Treasury supply, and policy credibility.
If markets perceive political influence over the Fed or higher inflation risk, long-term yields may remain elevated or rise, producing steepening. A pronounced steepening can transmit rate volatility into valuation pressure across risk assets.
Additionally, if Treasury issuance increases while the Fed is unwilling or unable to absorb duration via QE, supply-demand dynamics can limit the decline in long yields. This combination can trigger bond-market stress and broader cross-asset deleveraging.
4) Three US Monetary Policy Scenarios (Market Impact Focus)
4-1. Scenario A: Smooth Confirmation/Policy Transition and Stable Inflation → Stronger “Liquidity Rally”
If easing expectations remain intact and inflation data cooperate, risk assets (led by US equities) may sustain momentum. USD strength could moderate, with greater scope for flows into emerging markets and alternative assets.
4-2. Scenario B: Confirmation Delays + Powell Board Variable + Mixed Data → Alternating Repricing (“Hope vs. Disappointment”)
This represents a plausible baseline. Markets may rally sharply on positive confirmation progress or dovish signaling, then sell off on adverse inflation surprises or long-yield spikes, producing a structurally higher-volatility regime.
4-3. Scenario C: Inflation Re-acceleration + Deepening Steepening → Breakdown of Rate-Cut Expectations
This scenario is adverse. Higher long-term yields compress equity valuations and can shift the “liquidity” narrative into a “credibility” narrative. High-PE growth, leveraged positioning, and strategies predicated on low volatility would be particularly exposed.
5) Positioning Considerations: Why Liquidity Expectations Still Require Cash Buffers
Even if the medium-term direction points toward easier liquidity conditions, intermittent drawdowns are likely as policy events and macro data shocks recur.
For individual investors:
- (1) Maintain a cash buffer to avoid forced selling during volatility spikes.
- (2) Monitor a small set of high-signal indicators weekly: CPI/PCE, the US 10-year yield, and the 2s10s term spread (or comparable curve measures).
- (3) Reduce risk into weeks where confirmation headlines, Powell’s Board decision risk, and Treasury issuance/supply dynamics cluster.
Cross-asset tendencies:
- Stronger liquidity expectations typically support equities and digital assets.
- If steepening intensifies, long-duration bonds may fail to rally meaningfully (or post losses), while growth equity volatility can increase.
6) Key Point Often Underemphasized in Media Coverage
Most commentary focuses on whether Warsh is hawkish or dovish. The more material issue is the market’s confidence in the long end of the curve.
6-1. The Core Variable Is Not Rate Cuts, but Long-Term Yield Credibility
The Fed can influence short rates through guidance and policy decisions. Long-term yields are disciplined by market judgments on inflation, Treasury supply, and institutional independence. Under a Warsh-led regime, the primary risk is not the rate-cut headline, but whether long-end credibility erodes. If credibility weakens, steepening can accelerate and reprice risk-asset valuations broadly.
6-2. AI Disinflation: The Constraint Is Political Timing, Not Directionality
Productivity gains from AI are increasingly accepted. The market focus is when those gains become measurable in CPI/PCE. If the effect is not visible ahead of key political windows, policy justification weakens and volatility risk increases.
6-3. Fed Leadership News Transmits Through Global USD Liquidity and Capital Flows
This is not solely a domestic US issue. Shifts in USD dynamics affect emerging-market assets, Korean equities, the KRW, and major digital assets. The transmission channel intersects with broader growth and recession risks.
[Related]
- https://NextGenInsight.net?s=interest%20rates Comprehensive review: how rate-cut cycles affect asset markets
- https://NextGenInsight.net?s=inflation Checklist: signals of inflation re-acceleration and positioning considerations
*Source: [ 경제 읽어주는 남자(김광석TV) ]
– “캐빈워시는 매파가 아닙니다”. ‘유동성과 변동성을 동시에 불러올 것’ [경읽남 231화]
● Season 2 Greenlight, Copyright Smokescreen, Unfair Competition Showdown, Platform Takedown Chaos, IP Shockwave
Signals Indicate Season 2 of “Fireworks Baseball” Is Feasible; the Core Dispute Is Not Copyright but a Fight Over the “Unfair Competition” Framework
This note covers the following:
1) Why Season 2 is considered “feasible” (the actual focal points of the preliminary injunction decision)
2) Why YouTube videos continue to be taken down (how platforms act before a court reaches a final copyright determination)
3) The limitations of “format copyright” under Supreme Court precedent (common misconceptions)
4) The decisive battleground in this dispute: how to avoid and redesign around “exploitation of another party’s achievements” (production strategy)
5) Spillover effects for the content industry, platforms, and investors (market volatility and key risk-management considerations)
1) News Briefing: What Has Happened
Producer Siwon Jang independently developed a new program titled “Fireworks Baseball,” separated from the production trajectory of JTBC’s “Strongest Baseball.”
JTBC initiated legal action on the basis that the new program’s narrative is connected to “Strongest Baseball,” and an interview references a preliminary injunction decision issued last year.
Attorney Jeongcheol Kim (counsel for “Fireworks Baseball”) stated that multiple legal issues remain in active dispute, while also presenting a practical interpretation that “Season 2 is feasible.”
2) Three Legal Issue Clusters: Contract, Copyright, and Unfair Competition (the Third Is Pivotal)
2-1. Contract Breach
At the preliminary injunction stage, contract breach was not necessarily the sole or dominant basis; it was one element within a broader framework.
In practice, outcomes often hinge on how far the agreement restricts rights and uses (e.g., production rights, derivative works, reuse of cast and staff, similarity of titles). The interview did not disclose specific contractual language.
2-2. Copyright Infringement
A frequent misconception is addressed here.
Under the thrust of Supreme Court precedent, a “format itself” is generally not protected by copyright in a straightforward manner.
Accordingly, it is difficult to establish copyright solely on the basis of an “baseball variety-show format” or elements such as match operations and mission structures, which are closer to ideas or methods than protectable expression.
The interview similarly states that copyright recognition based solely on format is rare globally.
2-3. Unfair Competition Prevention Act (Exploitation of Another Party’s Achievements)
This was cited as the decisive basis for granting the preliminary injunction in this matter.
Unlike copyright, which focuses on copying of protected expression, this framework examines whether one party unfairly leveraged the other party’s market-established achievements (brand, narrative continuity, distinctiveness, and audience-drawing power).
In summary, while the dispute may appear to be a “copyright fight,” the practical outcome is more likely to turn on “unfair competition (free-riding on achievements).”
3) Why Season 2 Is Feasible: Narrative Discontinuity Design Can Reduce Risk
Counsel’s argument is positioned as operationally pragmatic.
If the injunction decision focused on factors such as narrative continuity with “Strongest Baseball” and partial cast overlap, then Season 2 can potentially mitigate “exploitation of achievements” claims by severing the narrative (universe, team composition, storyline, and premise) and fully repositioning the program.
An analogy is offered: the same cast appearing across different shows does not, by itself, establish narrative continuity.
Therefore, identical cast alone does not automatically imply illegality; the critical issue is whether the audience is led to perceive the new content as a continuation of the prior work through specific continuity devices.
4) Why YouTube Videos Are Removed: Platform Processes Move Ahead of Judicial Findings
This is the most immediate pain point for audiences.
When JTBC submits takedown notices to YouTube, YouTube does not adjudicate the merits of infringement in real time.
Until a dispute is finally resolved in court, platforms often apply interim restrictions (suspension or removal) once a notice reaches a certain threshold of facial plausibility.
As a result, content may be posted for a short period and then removed repeatedly.
This mechanism is increasingly material across the broader content industry.
When platforms control distribution faster than courts can reach final judgments, producers and investors face heightened market volatility as revenue, advertising, and subscription metrics can be disrupted.
5) What “Similar Cases Are Common” Really Means: “Format Disputes” Are Ultimately Boundary-Design Disputes
Examples include lawsuits over similarity between programs, disputes arising during the production of film sequels, and brand or franchise conflicts.
A recurring feature is that disputes typically arise not from exact duplication, but from a gray area: where inspiration ends and free-riding begins.
Accordingly, production teams increasingly operationalize differentiation early, including:
– Separation of distinctiveness in title, logo, and key visuals
– Narrative-discontinuity mechanisms: premise, team names, objectives, and rule-explanation methods
– Separation of signature elements such as editing tone, narration, music, and subtitle design
– Communication guidelines to avoid describing overlapping cast participation as a continuation of the prior work
6) Macro and Industry Implications: Key Takeaways for the Content Investment Market
Treating this solely as entertainment news risks missing the core implications.
As production budgets and IP values increase, and as distribution platforms (YouTube, OTT services, broadcasters) gain greater control, legal risk increasingly converts directly into cash-flow risk.
6-1. IP Stability Is Becoming as Material as “Rates”
For financing and valuation, IP stability is a central variable.
In particular, global supply agreements and sponsorships are highly sensitive to the risk of mid-stream distribution interruptions.
6-2. Platform Risk Can Drive Reported Performance
A single YouTube notice can disrupt distribution, affecting revenue recognition, ad execution, and brand safety.
Such event-driven risk can create valuation premiums or discounts and can influence investor sentiment comparably to major macro variables.
6-3. Production Strategy Can Become More Precise Through AI
Practical applications include:
– Similarity screening: model-based comparison of editing style, subtitles, and structural elements to identify high-risk segments in advance
– Narrative design: simulation of alternative storylines that avoid keywords likely to evoke the prior work
– Automated rights management: clip-level rights metadata management to improve response speed in platform disputes
The market is shifting from “quality alone” to “quality plus defensible, interruption-resistant distribution.”
7) Key Point Often Underemphasized in Other Coverage: The Material Issue Is the Strengthening Unfair-Competition Frame
The core is not a dispute over “who is the original,” but an indicator that the unfair-competition framework is gaining force in content markets.
Where format-based copyright claims are weak, courts may increasingly rely on “free-riding on achievements” to enforce market order, while platforms may restrict distribution before legal determinations are finalized.
The implications are practical:
Producers may need to embed legally defensible differentiation at the planning-document stage, and investors are likely to price preliminary-injunction and platform-blocking risks more explicitly rather than focusing only on short-term buzz.
< Summary >
The dispute centers more on unfair competition (exploitation of another party’s achievements) than on copyright, and this appears to have been a primary driver of the preliminary injunction.
Season 2 may remain viable if narrative continuity with “Strongest Baseball” is severed and the program’s identity is redesigned to reduce free-riding risk.
YouTube removals are largely driven by platform enforcement mechanisms that can restrict distribution based on notices before final court rulings, directly translating into revenue and investment risk.
Going forward, IP value may be increasingly determined by anti-free-riding design and platform distribution risk management rather than by format copyright claims.
[Related Articles…]
- How copyright disputes translate into investment risk
- Unfair Competition Prevention Act: key criteria for “exploitation of achievements”
*Source: [ Jun’s economy lab ]
– 불꽃야구 시즌2 할 겁니다(ft. 김정철 변호사 1부)
● SaaS Meltdown, SAP Value Wipeout, Subscription Exodus, Build With AI, Seat Pricing Collapse
Why the “End of SaaS” Is Not Just a Catchphrase: From SAP’s KRW 187 Trillion Market Cap Loss to Subscription Cancellations and the Shift Toward Building In-House with AI
This report covers the following core points:
First, a structural explanation for why top-tier software companies such as SAP, Salesforce, and Adobe weakened simultaneously.
Second, the investment-relevant signal behind Klarna’s “removal of 1,000 SaaS subscriptions.”
Third, how AI agents can undermine software pricing units and force a shift in monetization models.
Fourth, a buyer-centric classification of higher-risk vs relatively resilient software categories.
Fifth, the central risk to SaaS: not competition, but the collapse of the pricing unit.
1) Today’s Issue, Summarized as News
① The significance of SAP’s “KRW 187 trillion market cap loss”
SAP is a leading European enterprise software company (top-tier ERP) and historically controlled a core layer of enterprise operations.
A large market-cap drawdown from the peak suggests not only weaker fundamentals but a potential shift in valuation frameworks.
Markets are increasingly reluctant to price SAP and large-cap software as “perpetual-growth subscription assets.”
② U.S. SaaS bellwethers also declined: Salesforce, Adobe, ServiceNow
A 30–40% pullback from peak levels is closer to a sector-wide derating than a company-specific issue.
Beyond the standard impact of higher discount rates in a changing rate regime, AI has added concern that products themselves may become substitutable.
The market’s key question is shifting from near-term revenue growth to whether customers will have a sustained rationale to subscribe over the next several years.
③ Industry framing: “SaaS + Apocalypse”
While the term is hyperbolic, it reflects a real concern: AI is weakening the historical moat that “buying a subscription is cheaper and faster than building.”
2) Why the SaaS Model Was Strong (Legacy Framework)
① SaaS as a Netflix-style recurring subscription model
Before: license purchase → on-prem installation → separate upgrades/maintenance.
Now: cloud access → monthly/annual subscription → continuous updates.
② Enterprise operations standardized into “subscription bundles”
CRM: Salesforce.
HR: Workday.
Design/content: Adobe.
Accounting/logistics/ERP: SAP.
Department-level subscriptions scaled primarily through per-seat pricing.
③ Why SaaS equities historically commanded premiums
High recurring revenue, low churn, and expansion via upsell/cross-sell supported premium valuations.
SaaS was priced as both stable cash flow and growth.
Rates influenced multiples, but the business model itself was generally not questioned; that assumption is now under pressure.
3) Catalyst: The True Message Behind Klarna’s “Cut 1,000 SaaS Subscriptions”
① What Klarna did
Large-scale SaaS cancellations.
High-profile exits including Salesforce and Workday.
Shift toward AI-enabled internal systems (insourcing).
② Debate: “IPO-era margin optics?”
Short-term cost control may have been a factor.
Market reaction was driven by broader implications.
③ Core implication: AI lowers the barrier to insourcing
Historically, replacing SaaS with internal software required large enterprise-scale IT budgets and headcount.
AI coding tools and AI agents increase productivity, enabling smaller teams to build viable internal tools.
This dynamic can extend beyond outliers to mid-sized enterprises.
4) Oracle Vendor Lock-In Is Also Eroding: Why the Kakao Case Matters
① Why Oracle was strong: vendor lock-in
Databases are foundational; switching costs are high due to data schemas, queries, integrations, and operational know-how.
Migration carries outage and data-loss risk.
② Kakao’s long-running “Gliese project” as a symbol of Oracle exit
Since 2019, Kakao reduced Oracle dependency and removed it across multiple affiliate systems.
Historically feasible but expensive and time-consuming.
③ Key change: AI reduces migration and conversion costs
AI tools can lower time and cost via automated data transfer, automated testing, and migration risk detection.
The historical constraint—“too costly to switch”—weakens over time.
5) Structural Shift Driven by AI Agents: Not Feature Competition, but a New Consumption Model
① What an AI agent is
An AI system that plans tasks, executes via tools, validates results, and iterates—beyond a simple chatbot.
② Where moats weaken
SaaS value proposition: “building is hard and slow; subscribing is cheaper and faster.”
As development productivity rises, enterprises may perceive subscription fees as less defensible.
③ The meaning of “vibe coding” adoption
Non-specialists can increasingly specify workflows and UI in natural language to produce internal tools.
As customization becomes cheaper, standardized feature bundles become less compelling.
6) AI-Native Startup Pressure: Consolidation That Reduces the Need for Multiple SaaS Products
① AI-native characteristics
Designed around AI from inception, consolidating functions previously spread across multiple SaaS products.
② Example: integrated platforms that challenge CRM stacks
Legacy: separate subscriptions for CRM, marketing, analytics, automation.
Emerging: AI-managed end-to-end sales processes within a single platform.
Result: lower costs and reduced data fragmentation.
7) The Core Risk: Per-Seat Pricing Weakens as AI Reduces Human Work
① SaaS revenue engine: per-seat pricing
Headcount growth historically drove automatic account and revenue expansion.
② If AI agents replace human tasks
Enterprises reduce headcount, slow hiring, or shift to automation and outsourcing.
Seat counts decline, compressing the revenue base.
③ This is driven by customer organizational change, not competitors
The risk is structural: customers may stop operating in a human-seat-centric model.
8) Incumbent Responses and Constraints: Innovator’s Dilemma
① Incumbents are launching AI agents
Salesforce, ServiceNow, Snowflake, and others are defending with AI features and agents.
② Why market reception remains cautious (3 factors)
First, limited differentiation.
Second, slower-than-expected adoption due to security, governance, and accountability concerns.
Third, dependence on external LLM providers can pressure margins.
③ Central contradiction: successful automation can cannibalize per-seat revenue
More automation can reduce the number of paid seats.
Transitioning aggressively risks existing revenue; delaying risks relevance.
9) Higher-Risk vs Relatively Resilient Software (Investor/Industry Classification)
① Areas likely to be disrupted earlier by AI
Workflow tools.
General-purpose, department-level tools with substitutable features.
Analytics/reporting tools (LLMs can replace parts via natural language).
Products with broad feature sets but low utilization are likely cost-cut targets.
② Areas with relatively stronger defensibility
Core ERP and operational systems (high replacement risk).
Mission-critical databases and infrastructure (outage costs dominate).
Vertical software (hospital EMR, airline operations, manufacturing MES).
AI is more likely to be embedded as augmentation rather than wholesale replacement.
10) The Most Material Point Often Underemphasized
1) The core SaaS risk is not competition; it is the collapse of the pricing unit
The legacy unit is “people/seats.”
AI-era monetization may shift toward “work volume,” “tasks,” “outcomes,” or “agent executions.”
This forces a redesign of pricing architecture.
2) New KPIs used by CIO/CFO buyers
Before: renewal rates, number of departments adopting.
Now: labor-cost reduction attributable to the subscription, and total cost of ownership versus in-house AI-enabled builds.
Budgets may shift from subscriptions to insourcing plus AI operations.
3) Likely long-term winners: firms with enterprise AI operating capability, not just AI features
Adding a model layer is increasingly commoditized.
Differentiation shifts to governance, security, audit logs, access control, and accountability frameworks.
4) Potential acceleration of M&A and bundling
Survival may require broader capability (acquisitions) and/or pricing redesign (bundles).
Platform consolidation could intensify; regulatory scrutiny may rise.
11) Investment and Macro Implications (Key Items to Monitor Through 2026)
① Rates and AI jointly drive valuation reset
Rate cuts can support growth multiples, but if AI reduces the need for subscriptions, prior peak revenue multiples may not fully reassert.
This is more consistent with structural change than a pure cycle.
② Enterprise IT spend: from “subscription optimization” to “AI-centric re-architecture”
The focus may shift from adding more SaaS products to redesigning workflows around AI agents.
③ Public-market checklist
Signs of Net Revenue Retention (NRR) deterioration.
Evidence of pricing shifts from per-seat to per-output/per-task.
Whether AI features create incremental revenue or cannibalize existing revenue.
Impact of external LLM costs on gross margin.
Quantitative signals of vendor consolidation and “SaaS rationalization” among customers.
< Summary >
The drawdowns in large-cap SaaS, including SAP, reflect more than a typical correction; AI is challenging both moats and valuation logic across software.
Klarna’s large-scale SaaS cancellations strengthened the signal that enterprises can reduce subscriptions by building internally with AI, while AI-assisted migration also weakens vendor lock-in dynamics.
The dominant risk is the erosion of per-seat pricing; software monetization may shift toward output, tasks, and agent executions.
[Related Articles…]
SAP risk and European tech valuation reassessment points
https://NextGenInsight.net?s=SAP
How AI agent adoption reshapes enterprise IT budget allocation
https://NextGenInsight.net?s=AI
*Source: [ 달란트투자 ]
– “순식간에 시총 187조 증발” 유럽 1위 기업의 몰락
