● Musk Bombshell, Tesla Bets on Driverless Empire and Energy Cash Cow

Musk Declares “Year-end Unmanned Autonomous Driving”… A Comprehensive Overview of Tesla Q3 Results and the AI & Energy Transformation

This article covers the real reasons behind the revenue surprise and EPS miss, the impact of the energy business’s 31% margin, the roadmap for robo-taxi following the year-end launch of unmanned autonomous driving (unsupervised FSD), the significance of the AI5 chip and a GPU cluster of around 80,000 units, and even the rapid rise of the Korean market.
It provides an overview that connects changes in the earnings structure—direct hints for the stock outlook—with global economic variables (interest rates, inflation).

News at a Glance: Numbers and Key Points

Tesla Q3 revenue reached $28.1 billion, exceeding the consensus of $26.2 billion by about 7%.
EPS stood at $0.50, missing the expected $0.54 by approximately 7%.
The operating margin was around 5.8%, portraying a typical transitional phase where volumes reach record highs, yet profitability is under pressure.
Deliveries were about 498,000 units, up 7% year-over-year, with the Model 3 and Y driving performance with 481,000 units.
High-margin vehicle deliveries such as the S, X, and Cybertruck amounted to 15,933 units, decreasing by more than 30%, which led to a mix deterioration that impacted profitability.
Energy revenue reached $3.4 billion, surging 44% year-over-year, and energy storage (ESS) deployments hit a record 12.5 GWh.
The energy segment’s overall margin surged to 31.4%, a record high, emerging as a “margin pillar” amidst automotive sector volatility.
Cash flow remains robust.
With a free cash flow of $3.99 billion and cash and investments amounting to $41.6 billion, there is ample capacity for aggressive R&D and capital expenditures.
Musk officially announced the year-end commercialization of “unmanned autonomous driving” (in 8-10 urban regions) along with an acceleration along three axes: AI, robotics, and energy.

Earnings Analysis: Cars vs. Energy, The Bright and Dark Sides of a Transition

The crux lies in the reduced proportion of high-margin vehicles and a surge in operating expenses.
Sales were boosted through volume growth driven by the Model 3 and Y, but the deteriorating vehicle mix and certain tariff and component cost increases elevated the per-vehicle cost.
R&D spending on AI and robo-taxi increased by approximately 50% year-over-year, thereby pushing up OPEX.
Combined, these factors resulted in the EPS miss, marking the primary cause of short-term profitability deterioration.
On the other hand, the energy business is inherently less sensitive to external variables (price cuts, tariffs) than vehicles.
It features a stable revenue structure linked with the Megapack (for grid), Powerwall (for residential use), and an energy trading platform.
The expansion effect of the Shanghai Megapack and the forthcoming Houston factory plans (targeting 50 GWh per year) have materialized, presenting ample opportunities for further margin improvement through economies of scale.
In times when automotive performance falters, energy serves as a safety net for EPS and, in the long run, could evolve into a growth engine on par with that of vehicles.

AI and Autonomous Driving Roadmap: Year-end ‘Unsupervised’ and the AI5 Chip

Musk stated that the goal is to achieve “unmanned autonomous driving without safety personnel” in 8 to 10 major U.S. cities (including Nevada, Florida, Arizona, Austin, etc.) by year-end.
The FSD v14 series has enhanced capabilities to handle complex scenarios, such as obstacle avoidance and automated parking at destinations, and it teased the addition of arrival/departure intelligence (drop-off/recall) in v14.3.
In-car messaging and web browsing, transforming driving time into productive time, are highlighted as key consumer value propositions.
The learning infrastructure was described as having around 80,000 H100-class GPUs, and strengthening the chip ecosystem through collaborations, including with Samsung, was mentioned.
The next-generation AI5 chip aims for up to 40 times the computational performance of HW4, with plans to leverage TSMC and Samsung foundries being discussed.
For HW3 users, an FSD v14 Lite version is expected to be offered in Q2 2026, with hints at a reverse expansion following an HW4-centric commercialization.

Robotics and Cybercap: Signals of Accelerated Commercialization

Optimus v3 is targeted for unveiling in Q1 2026 and boasts a natural form factor that “looks as if a person is wearing a suit.”
Plans for a production line targeting 1 million units annually by the end of 2026 were mentioned, premised on the commercialization of robotic labor.
Robo-taxi, known as Cybercap, aims to commence production from Q2 2026, aligning with the timeline for the commercialization of unmanned autonomous driving.
The convergence of robotics, FSD, and energy sketches out the blueprint for an “AI operating system” that integrates urban power infrastructure with mobility services.

The Korean Market and Global Economic Variables

South Korea has rapidly ascended to become Tesla’s 3rd largest market by deliveries, increasing its strategic importance.
From a global economic perspective, the trajectories of interest rates and inflation directly affect EV demand and CAPEX costs, while changes in policy subsidies and tariff environments influence pricing strategies.
These variables are reflected as discount/premium factors in stock outlooks, functioning as leverage on the pace of the fourth industrial revolution narrative and corporate valuations.

Wall Street’s Perspective: Short-term Profitability vs. Long-term Platform Transition

The consensus was an EPS of $0.54 and revenue of $26.2 billion, but the outcome was a mixed picture of a revenue surprise paired with an EPS miss.
In the short term, it signals a deterioration in profitability, but in the long term, it is interpreted as an investment phase for expanding into AI, robotics, and energy.
For technology and growth stock investors, a focus on market share, the pace of FSD commercialization, and energy margin trends is a valid approach.

The Most Crucial Point Often Overlooked Elsewhere

The qualitative shift in energy margins serves as a “promissory note” for the FSD and robo-taxi network.
Grid-scale storage and energy trading lower the variable costs associated with robo-taxi charging, dispatch, and maintenance while increasing service uptime, thereby boosting LTV.
For Megapack, as installations increase, field standardization accelerates the distribution of fixed costs, and when accompanied by project financing, the visibility of profitability improves.
The in-house production of the AI5 chip isn’t just a simple vehicle option; it disrupts the “computing cost = service cost” structure to structurally boost FSD subscription margins.
Control issues can directly impact the pace of technology integration and regulatory negotiating power, so they should be seen not merely as equity issues, but as an “execution risk” factor.

Risk Checklist

Continued deterioration in vehicle mix and additional pricing pressure.
Cost uncertainties due to rising tariffs, supply chain issues, and component cost increases.
Timeline risk for unmanned autonomous driving commercialization in case of regulatory approval delays.
Increased development and support costs stemming from hardware generation differentiation (HW3/4/5).
If interest rates remain high, there could be a demand slowdown and CAPEX cost increases, and if inflation surges again, margin pressure may reappear.

Timeline and Checkpoints

Year-end: Announcement of unmanned (unsupervised) FSD commercialization targets in select major cities and initial operations.
Q1 2026: Optimus v3 expected to be unveiled.
Q2 2026: Target to start production of Cybercap, with FSD v14 Lite expected to be provided for HW3.
Post-2026: Observation of Houston Megapack operations (targeting 50 GWh annually) and an increased proportion of energy revenue/margin.

Investor Watchpoints (To be corroborated with data)

Active FSD users, subscription conversion rates, and monthly mileage data (including safety metrics).
The number of urban zones where unmanned operations are initiated, along with operating hours and accident rates.
Megapack shipments, energy overall margin trends, and project order backlogs.
The scale of computing infrastructure (number of GPUs owned, training time) and the pace of transitioning AI5 to mass production.
The sustainability of cash flow and the normalization trajectory of the OPEX-to-revenue ratio.

< Summary >

• Revenue exceeded by about 7%, EPS missed by approximately 7%.
• The core cause of the profitability decline is the reduction in high-margin vehicles, a surge in OPEX, and increases in tariffs/costs.
• Energy revenue increased by 44%, with a total margin of 31.4%, emerging as a “margin pillar.”
• An unmanned autonomous driving target in select cities by year-end, with reinforced learning infrastructure through the AI5 chip and large-scale GPUs.
• Target to unveil Optimus v3 and commence Cybercap production in 2026.
• Risks include vehicle mix, regulations, costs, and interest rates; watchpoints are the speed of FSD commercialization and energy margins.

[Related Articles…]

• Tesla Unmanned Autonomous Driving & Energy Transformation Key Checkpoints
• The Mobility Economics and Revenue Model that FSD Commercialization Will Change

*Source: [ 오늘의 테슬라 뉴스 ]

– 머스크 충격 발표… 올해 말 ‘무인 자율주행’ 시대 연다 테슬라 3분기 어닝 분석 핵심은?

---

---

● AI Coup, Tesla Robot Army

Tesla Q3 Earnings Call Key Summary: FSD Reinforcement Learning Transition, AI5 Chip, Unsupervised Robo-taxi, Optimus, and Governance Risks

Tesla’s adoption of AlphaZero-level reinforcement learning marks a turning point where FSD moves beyond the limitations of ‘human data.’
It specifically discusses how the in-car inference-dedicated AI5 chip and the economics of in-house chip design will lower the unit cost of autonomous driving.
It interprets the removal of the safety driver in Austin, the step-by-step entry strategy for new cities, and Cybercap’s per-mile cost structure in numerical terms.
It unpacks the Optimus v3, human-hand level grip and manipulation, and the paradigm shift in production where ‘robots build robots’ in line with real-world AI trends.
It emphasizes why the shareholder vote and governance are directly linked to the acceleration of the technology roadmap, connecting the risks amid the global economy and interest rate environment.

Significance of FSD Reinforcement Learning Transition and World Simulator

Tesla has formalized its strategy to enhance FSD performance by incorporating reinforcement learning and self-play in the world simulator.
This represents a strategy to apply the pivotal shift from AlphaGo to AlphaZero—from relying on human game data to self-play—to autonomous driving.
The key element is the design of the reward function.
High rewards are assigned to the safest, smoothest driving that allows passengers to feel comfortable, while penalties are imposed for discontinuous steering, hard braking, and accident risks.
The simulator infinitely generates rare and extreme cases to diversify the data that is hard to collect on actual roads.
However, the role of human driving data does not become ‘zero.’
Large-scale real-world data is still necessary for initial training, bridging the reality-simulator gap, and policy validation.
Ultimately, reinforcement learning marks the beginning of a second phase that supplements and accelerates the diminishing marginal utility of human data.

AI5 Chip: Inference-Specific Architecture and the Economics of In-House Design

The AI5 chip claims up to 40 times the performance of AI4 in some workloads, boldly removing traditional GPU blocks to optimize for real-world driving inference.
In real-world autonomous driving, model size, latency, heat, and power constraints are absolute.
AI5 focuses on minimizing latency and power consumption by simplifying the inference path and reducing data movement.
The core value of the internal design is the ‘elimination of unnecessary complexity.’
While chips designed for the mass market incorporate various functions, what Tesla seeks is extreme optimization specifically for autonomous driving functions.
Thus, chip area, power, and cost are allocated solely to autonomous driving performance to lower the inference cost per mile.
From a supply chain perspective, dual-sourcing with Samsung and TSMC diversifies production capacity and geographic risks.
This increases resilience against semiconductor supply chain shocks and reduces bottlenecks when deploying robo-taxis at scale.

Unsupervised Robo-taxi and Gradual Expansion Strategy

Tesla is prioritizing the removal of the safety driver in Austin while reaffirming a cautious expansion strategy that retains safety drivers in new cities.
Since even a single major accident can shut down the entire market, managing ‘market launch risks’ is paramount.
Cybercap is not designed for 0-100 acceleration but is developed with the aim of drastically reducing the total cost of ownership (TCO) per mile.
The concept is to lower the vehicle unit cost through sensor and compute hardware cost reductions compared to Waymo, and to reduce operating costs through low-power inference based on AI5.
This model blurs the line between ride-hailing and personal vehicle ownership, with increased vehicle utilization being a critical lever for profitability.
Even as rising interest rates in the global economy increase vehicle and fleet procurement costs and inflation pressures parts and battery costs,
if autonomous driving can lower the average operating costs, the price elasticity of demand could offset these factors and stimulate demand by reducing the actual cost of urban travel.

Production Capacity Roadmap and Synergy with the Energy Business

A “hopeful target” of achieving a production capacity of 3 million cars within 24 months was presented, and the Cybertruck is expected to see a significant ramp-up in Q2 of next year.
As colossal demand becomes apparent, bottlenecks are likely to shift to batteries, power electronics, and AI computing modules.
Superchargers and energy storage systems (ESS) contribute to infrastructure revenue and ecosystem stickiness following vehicle sales.
The expansion of grid-connected ESS reduces peak charging costs, creating a virtuous cycle that further lowers the total cost of ownership.

Redefining Elon’s ‘Core Competence’ and Governance

Tesla views its core not as a fixed set of competencies in specific domains, but rather as the ability to quickly create new core competencies.
Its strength lies in the vertical integration of design, production, and software, enabling immediate design improvements in real-time operations.
The company emphasizes that issues of compensation, equity, and voting rights serve as mechanisms to ensure consistency and speed in the technology roadmap.
A performance-linked compensation structure aligns shareholder value and management understanding, underpinned by the recognition that uncertainties in management control could undermine technological execution.

Optimus: v3, Human-like Hands, and ‘Robots Creating Robots’

The crux of Optimus lies in its hands.
For deployment in industrial settings, it must secure human-like dexterity with forearm and thumb muscles that enable precise grip and manipulation.
It accelerates development through ‘concurrent engineering’ where designs are continuously revised during production, much like Starship.
A v3 prototype is targeted for release in Q1 of next year, and the long-term vision is for a factory where ‘Optimus builds Optimus.’
This represents a macro-level impact that could rapidly enhance labor productivity and mitigate structural inflation pressures.
At the same time, without accompanying policies on safety, responsibility, and labor market transition, social frictions could intensify.

Key Points Not Covered Elsewhere at a Glance

The real challenge of reinforcement learning is the design of the reward function.
If safety is overly prioritized, excessive conservatism may compromise service quality; if ride comfort is overly emphasized, a trade-off near the safety limits may occur.
The fact that Tesla has decided to incorporate comfort into the reward function is a decisive signal targeting the NPS of commercial robo-taxi services.
The design philosophy of AI5 starts from the understanding that “data movement is equivalent to energy consumption.”
Optimizing on-chip memory, compression, and schedulers to reduce latency and heat is the most reliable way to lower the power consumption per mile.
Dual-sourcing with Samsung and TSMC disperses geopolitical risks and serves as insurance against single foundry bottlenecks during large-scale robo-taxi rollouts.
The strategy of retaining safety drivers in new cities, based on the recognition that even one major accident could close the market, is risk engineering aimed at ‘market launch’ rather than technology.
Even in a global economy beset by high interest rates and inflation, if autonomous driving lowers unit costs and reduces the actual price of transportation, overall demand may increase.

Risk Checklist and Investment Implications

It is a technological risk.
Variables include the reward design in reinforcement learning, the reality of the simulator, and the safety limits of edge inference.
It is a regulatory risk.
Differences in regulations, insurance, and liabilities across cities could amplify the repercussions of initial accidents.
It is a capital risk.
If interest rates remain high, financing costs will increase, and inflation will put pressure on material costs.
It is a competitive risk.
Although legacy automakers and big tech continue to pursue AI trends, Tesla’s triple vertical integration of data, chips, and production remains its defensive wall.

Numbers Representing This Call’s ‘Declaration’

FSD enters its second phase with reinforcement learning and a simulator.
AI5 is a chip that lowers the cost per mile through 40x improvements in some areas and inference specialization.
After the unsupervised trial in Austin, new cities will maintain safety drivers to manage ‘market launch risks.’
A production capacity goal of 3 million cars within 24 months has been set, and the Cybertruck ramp-up is expected to accelerate in Q2 of next year.
Optimus v3 is targeted for Q1 of next year, with a focus on specialized hand functions and concurrent engineering.
It was emphasized that the shareholder vote on governance is directly linked to maintaining technological roadmap stability and execution.

< Summary >

Tesla intends to move FSD beyond its dependence on human data by shifting to a reinforcement learning and simulator-centric approach.
The AI5 chip, with its inference specialization, low latency, and low power consumption, enhances the economic viability of robo-taxi operations by reducing costs per mile.
Following the unsupervised trial in Austin, new cities will retain safety drivers to mitigate the risk of a market shutdown due to a single major accident.
A production capacity target of 3 million vehicles in 24 months, Cybercap’s TCO optimization, and synergies with ESS and superchargers underwrite long-term demand.
Optimus v3 and the vision of ‘robots building robots’ could have medium- to long-term effects on labor productivity and inflation dynamics.
The shareholder vote on governance plays a key role in ensuring stability and execution speed of the technology roadmap, and even amid global economic challenges like high interest rates and inflation, if autonomous driving lowers transportation costs, overall demand is likely to grow.

SEO Memo

This article provides an integrated analysis of how the global economic context, including interest rates and inflation, affects the commercialization timing of Tesla’s autonomous driving and AI trends.
Key keywords such as global economy, interest rates, inflation, AI trends, and autonomous driving are naturally woven throughout the text.

[Related Articles…]

• The Essence of the Robo-taxi Profit Model: The Math Behind Cost per Mile and Utilization
• The Geopolitical Significance of Dual-Sourcing in the AI5 Era’s Semiconductor Supply Chain

*Source: [ 허니잼의 테슬라와 일론 ]

– 테슬라 3분기 어닝콜 주요내용 정리(생방 슈퍼컷) / 자율주행 강화학습 시작의 의미 & 옵티머스 돈복사 버그의 시작

---

---

● Rate Freeze, Currency Panic, Housing Timebomb

Bank of Korea Keeps Policy Rate at 2.5%: Prioritizing Exchange Rate Defense and Real Estate Stability, November Cut Hinges on ‘Dollar, Swap, Seoul Home Prices’

This article covers the real background behind the rate freeze, why the USD/KRW exchange rate is a “game changer”, the core of the currency swap controversy, risks in real estate and household debt, a roadmap of policy events from October to November, and actionable response strategies for the market right now.

It specifically outlines key points that are rarely discussed elsewhere, such as the “policy consistency premium”, the “real interest rate – potential growth rate gap”, and the “decoupling of the current account surplus and the exchange rate”.
Let’s read and grasp the direction on rates, exchange rates, inflation, recession, and real estate all at once.

[Breaking Summary] What Has Been Decided and Where the Market Focuses

• Bank of Korea maintains the policy rate at 2.50%.
• The pretext is prioritizing financial stability, while the practical focus is on defending the exchange rate and curbing real estate overheating.
• September inflation stood at 2.1% with core inflation at 2.0%, around the target (2%), though external variables have increased volatility.
• Growth is forecast at 0.9% this year and 1.8% next year, which falls short of the potential growth rate (around 2%).
• The USD/KRW exchange rate remains in the 1420–1430 range, with only the won showing noticeable weakness despite a decline in the Dollar Index.
• The current account recorded a surplus of $9.15 billion in August (the highest ever for August), maintaining the possibility of an annual surplus of $110 billion.
• Household loan growth slowed in September, although loans for home purchases continue to exert upward pressure.
• After the government’s “October 15 Real Estate Market Stabilization” measure, monetary policy has confirmed a stance of following suit.
• The possibility of a rate cut by the US FOMC in October suggests that if two cuts occur before year-end, the interest rate gap between Korea and the US may further narrow.

Why the Freeze: Three Lenses of Prices, Economy, and Financial Stability

• Prices (Inflation): September CPI was 2.1% and core inflation 2.0%, both near the target.
  With the base effect from telecom charges fading, as well as oil price volatility and exchange rate risks, fluctuations around 2% are expected.
  From a price perspective alone, there is room for a gradual rate cut.
• Economy: With growth forecasts of 0.9% this year and 1.8% next year falling below the potential growth rate (around 2%).
  Although easing measures might be appropriate from the standpoint of defending against a recession, it was deemed that the side effects are currently too significant.
• Financial Stability: With further weakening of the won, signs of real estate overheating, and increased external uncertainties.
  This factor is the key reason behind the decision to keep rates unchanged.

The Exchange Rate as a “Game Changer”: Why the Won is Weak While the Dollar Falls

• Despite the Dollar Index declining, the USD/KRW exchange rate has maintained the 1420–1430 range.
• The won depreciated by approximately an additional 3.7% against major currencies, driven by simultaneous position unwinding and policy uncertainties.
• The Bank of Korea’s verbal intervention after 11 months signals “level defense”, but the credibility of policy consistency is even more crucial.
• Considering the 3- to 4-month lag in the exchange rate’s transmission to “import prices → producer prices → consumer prices”, a rate cut now could trigger a resurgence in inflation.

Currency Swap & $350 Billion Package: The Key Checkpoints the Market Truly Watches

• Confusing remarks regarding the swap review have raised questions about its “feasibility, timeline, and the consistency of the counterparty (US authorities)”.
• The swap serves as a “short-term lifeline for dollar liquidity”, not a substitute for long-term investment resources.
• Even if a swap is arranged, the activation conditions, maturity, and interest rate (or fees) are critical, and the effectiveness of exchange rate stabilization will depend on this combination.
• Among the approximately $420 billion in foreign exchange reserves, the proportion that can be immediately liquidated as cash or deposits is low.
  Therefore, if portfolio outflows accelerate, a simultaneous “psychological and liquidity” defense mechanism will be necessary.

Real Estate & Household Debt: Why a Rate Cut Signal is Risky

• A rate cut immediately following the October 15 market stabilization measures is interpreted as a policy “mismatch”, which causes confusion in forming expectations.
• Loans for home purchases continue to exert upward pressure and, if rates are cut, could spark a rebound in transactions and prices.
• Household debt represents a vulnerable link in the financial system.
  This is why the timing of a rate cut has been postponed until after price stability is confirmed.

November Scenario: Three Conditions for a Rate Cut

• Condition 1) Clear signals of the exchange rate returning to the 1300 won range.
  The discount on the won relative to the dollar must be confirmed to have resolved amidst a weakening dollar.
• Condition 2) External negotiations, including US investments and currency swaps, must present a “timeline and feasibility”.
• Condition 3) Seoul apartment prices must shift to signals of stabilization or decline.
  If all three conditions are met simultaneously, the possibility of a rate cut in November opens up.
  Conversely, if the exchange rate remains stuck in the 1400 won range, extending the freeze would be reasonable.

Quantitative View of the Current Stance: Why It is Still Tightening

• The real interest rate, calculated by subtracting expected inflation (around 1.8%) from the nominal policy rate of 2.5%, is in the mid-to-high 0% range.
• Compared to the potential growth rate (around 2%), the policy rate remains restrictive.
• In other words, the rate freeze is closer to “maintaining tightness” rather than easing.

Global Event Timeline

• Late October FOMC: A rate cut stance adopted for risk management, with a potentially hawkish tone.
• November 27 Bank of Korea Monetary Policy Committee: Final decision will reflect external variables from October and November.
• Through year-end, there will be ongoing assessments of US negotiations, currency swaps, energy prices, and geopolitical risks.

Key Points Only Here: Critical Insights Rarely Found Elsewhere

• Policy consistency premium: Even with the same measures, a “credible sequence” stabilizes the exchange rate more rapidly.
  The timeline of words and actions must align to reduce exchange rate volatility.
• Current account surplus vs. exchange rate decoupling: Although the surplus has expanded, portfolio outflows and confusing policy communications counteract it.
  It is a period where judging the exchange rate direction solely based on real flows is challenging.
• NDF-spot basis caution: If the basis widens due to month-end settlements and corporate payment demands, the exchange rate can be exaggerated.
  A separate hedging strategy for month-end and quarter-end should be prepared.
• Real interest rate – potential growth rate gap: Currently, the “timing risk” is greater than the “room for easing”.
  A rate cut is a timing game, and confirming exchange rate stability is a prerequisite signal.

Response Strategies for Investors, Corporations, and Individuals

• Loans & Cash Flow: Favor fixed rates over variable ones; reexamine repayment plans over the next 6–12 months.
• Currency Hedging: Importers should increase the proportion of rolling hedges, while exporters prepare for upward events by combining options.
• Bonds: Gradually extend duration, but avoid over-betting before exchange rate stability is confirmed.
• Equities: Export-oriented stocks (semiconductors, automobiles) have favorable fundamentals, but be prepared for margin pressure and value adjustments if the exchange rate suddenly shifts downward.
• Real Estate: Refrain from increasing leverage until policy effects are confirmed; prioritize DSR (Debt Service Ratio) and liquidity buffers.

Checklist: 5 Must-Watch Points Before a November Rate Cut

• Whether the USD/KRW exchange rate consistently breaks downward below the 1380 level.
• Whether the “conditions, fees, and activation triggers” for the US swap and investment package are disclosed.
• Confirming that the rebound in the Seoul apartment sales index is under control.
• Whether international oil prices and freight indices are rising again, and the lagged effect on import prices.
• The persistence of a shift to net buying of foreign bonds and equities.

< Summary >

The Bank of Korea has kept rates at 2.5%, focusing on financial stability, particularly defending the exchange rate and ensuring real estate stability.
While there is room for easing in terms of prices and the economy, the weakened won and policy credibility issues have postponed the timing for a cut.
A November rate cut hinges on the simultaneous fulfillment of “a return to the 1300 won range in the exchange rate, effective swap execution, and stable Seoul housing prices.”
Investors must navigate this volatile period by strengthening currency hedges, gradually extending bond duration, and managing leverage.

[Related Articles…]

USD/KRW Exchange Rate: Conditions and Scenarios for Entering the 1300 Won Range
Rate Pivot Era Checklist for Real Estate and Bond Investments

*Source: [ 경제 읽어주는 남자(김광석TV) ]

– [속보] 한은 기준금리 연 2.5%로 동결…원달러 환율 대응 우선 [즉시분석]

---

---