● Cybercab 2026 Shockwave, Robotaxis and Optimus Upend Global Economy and AI
The official launch of Cybertruck in 2026 is imminent: A complete overview of how Robo-taxis and Optimus will change the global economic landscape and AI trends
Key points contained in this article
The commercialization signal of Cybertruck in 2026 is unraveled into a path connected to actual revenue models through numbers and institutional changes.
The introduction of Robo-taxis presents the quantitative framework of the secondary and tertiary ripple effects impacting inflation, interest rates, the labor market, and urban finance.
The roadmap of mass production for Optimus’s third generation in 2026 and 1 million units annually by 2030 is explained regarding how it will transform the industrial robot market structure.
The regulatory issues concerning the Cybertruck in Europe are interpreted in terms of their implications for the approval process of Cybertruck and Robo-taxis.
A Tesla-like digital transformation architecture connecting data centers, energy, and mobility is offered along with an investment and policy checklist.
Q4 2025 → H1 2026: The triggering period for Cybertruck’s commercialization
Franz von Holzhausen indicated on CNBC that the design of Cybertruck is essentially final and hinted at its actual road deployment next year.
Cybertruck adopts a design dedicated to Robo-taxis combined with full self-driving software, optimizing for two passengers.
This strategy targets the demand structure where 98% of ride-hail requests are for 1-2 passengers, aiming to increase cost efficiency and turnover rates.
While extreme cases like indoor and double-layer parking movement are still incomplete, a FSD integrated update is expected to narrow the gaps.
The key point is that this year marks the transition from a “prototype showcase” to a “revenue-generating service platform.”
2026 → 2027: Scaling and unit economics of Robo-taxis
The essence of unit economics is derived not from the vehicle itself but from the combination of utilization rate, maintenance, insurance, and energy costs on an hourly basis.
Using hypothetical examples, if the vehicle CAPEX is $30,000 to $35,000, depreciation over 5 years, operating for 16 hours a day, and energy costs are $0.12-$0.18/kWh, while tire and maintenance costs are $0.05-$0.08/mile, the total cost per mile could converge to a range of $0.35-$0.55.
This suggests a potential 20-40% reduction in pricing compared to the average fares of Uber or Lyft in urban areas, while still allowing for profits.
Insurance rates could further decrease per mile as the incidence rate of FSD accidents declines, and if combined with in-house insurance underwriting, overall costs improvements could accelerate.
Batteries featuring LFP and LMFP chemistries have the advantage of longer life cycles, and at the end of their life, they can transition into energy storage solutions, enhancing total returns.
Regulatory timeline and interpretation of European signals
The German and EU prohibition on the road operation of Cybertruck combines pedestrian protection, vehicle shape, and weight safety device justifications with industrial protection psychology.
This presents two implications for Cybertruck.
First, it must clearly comply with UNECE regulations and pedestrian protection designs, with consensus on details like vehicle exterior, ground pressure, and edge processing being crucial.
Secondly, Robo-taxis must address not only vehicle safety but also remote operation, data processing, and privacy and mapping regulations, making city-level sandbox models the key.
The United States is likely to expedite city pilots leveraging state-level autonomous driving permit structures, while the EU may take a gradual and conditional allowance approach as a reasonable scenario.
Optimus 3rd generation: 2026 mass production and 2030 roadmap for 1 million units
According to a roadmap revealed on Weibo, the 3rd generation is set to be unveiled at the end of 2025, start mass production in 2026, and target the production of 1 million units annually by 2030.
Considering that the global annual shipment of industrial robots is about 600,000 units, the goal of 1 million units for a single company represents a paradigm shift.
Initially deployed in high-frequency, low-risk tasks such as factory logistics, picking, last-mile deliveries, retail replenishment, healthcare assistance, and household repetitive tasks.
Designed with humans and the environment as the focus, the humanoid form dramatically reduces costs associated with adaptation to tools, stairs, doors, and buttons.
Sharing the robot operating system and data network with vehicles enhances learning efficiency and part commonization, sharply declining the cost curve.
AI technology stack: Convergence of vehicles, robots, and data centers
The end-to-end vision model of FSD v12 may replace rule-based models as large-scale self-vehicle data reduce reliance on maps and heuristics.
Cybertruck combines edge inference with backend monitoring and simulation in a hybrid structure to elevate reliability.
The data center is likely to mix Nvidia-based clusters with proprietary optimization stacks while maximizing energy efficiency with the division of labor between learning and inference.
Tesla’s energy business is centered on optimizing the grid that links data centers, charging infrastructure, and vehicles, lowering energy costs through peak shaving and demand response.
This integrated structure is the core competitive advantage of Tesla-like digital transformation.
Macroeconomic impact: Inflation, interest rates, and global economic outlook
As transportation costs fall with the commercialization of Robo-taxis, the structural disinflationary pressure emerges as the share of transportation in service CPI decreases.
Improvements in productivity and reductions in transportation time can produce real wage effects, positively contributing to the global economic outlook.
Central banks will balance short-term spikes in energy and electricity demand with long-term cost decreases, but if productivity shocks are significant, the interest rate path may lean towards gradual cuts.
Urban finance will experience a simultaneous decline in parking and enforcement revenues, alongside congestion alleviation, necessitating a financial restructuring that includes converting road and parking uses.
The insurance industry may improve loss ratios due to reduced accident rates and price competition, though investments in a new premium system and data-driven underwriting will be essential.
Industry and investment landscape: Winners and risks
Potential winners include battery materials (LFP, LMFP, copper), power infrastructure and distributed energy, data center power and cooling, AI semiconductors, alternative data for maps and HD maps, and software operating platforms.
Challengers and risks include traditional vehicle sales channels, certain taxi and TNC intermediary models, urban parking and land, and downward pressure on used vehicle residual values.
As Robo-taxis operate around the clock, the demand structure for durability and maintenance ecosystems as well as tire and brake needs will be reconfigured.
Second-life batteries and recycling will serve as a backstop against revenue model risks, absorbing fluctuations in raw material prices.
The center of AI trends will shift to “movement data × robot actuation,” making mobility the largest source of real-world data generation.
Tesla internal events and Wall Street signals
On November 6, support for management proposals during the general meeting and approval for investments linked to XAI will directly connect to realizing a long-term AI vision.
Canaccord raised the target stock price to $490, viewing the rollout of affordable models and the combination of energy storage and data center power as key momentum.
This reflects a reevaluation that goes beyond car sales to income diversification into service, energy, and AI platforms.
While there may be short-term valuation pressures, frequent reallocation of multiples occurs in phases where realizable revenue models come into play.
The key lies in the speed at which actual metrics for paid miles, accident rates, utilization rates, and margins are disclosed.
A new standard for city and policy design
Cities can realistically expand limited operation hours, zones, speeds, and remote operation regulations through pilot zones.
Data sovereignty and privacy can strike a balance through anonymization, on-device processing, retention period limits, and audit logs.
For charging and power grids, combining bus depot mega-chargers with battery buffers can reduce peaks, and distributed ESS can lower blackout risks.
Insurance and liability need to define risk-sharing rules among manufacturers, operators, and users under level-4 conditional criteria.
Standardization requires a common format for safety KPIs (disengagements, collision mileage per event, pedestrian proximity events) to be publicly disclosed.
KPIs to check in 2026
Paid driving miles and waiting times per call for each city, as well as trends in average fares and utilization rates.
Quarterly changes in accident rates, pedestrian proximity events, and premium rates.
Vehicle costs, battery cycle life, maintenance intervals, and tire wear rates.
Charging times, energy prices, and peak reduction rates as energy cost indicators.
Optimus’s task success rate, MTBF, and speed of real-time feedback loops in the field.
Key points often overlooked (under-discussed elsewhere)
The impact on city finance.
The growing tax revenue gap from reduced parking, enforcement, fines, and fuel taxes may lead to the reconfiguration of road pricing and intelligent congestion charging.
The change in used vehicle residual value structure.
Due to the utilization rate gap, the downward pressure on personal vehicle residuals will increase, and corporate and fleet residual models will become standardized.
Quality of power.
High-speed charging on a large scale could cause local voltage stability and harmonic issues, necessitating investments in filtering, microgrids, and battery buffers.
Restructuring of the risk-based capital (RBC) system in insurance.
AI safety indicators will be directly reflected in the capital requirements for regulation, with Tesla’s public data disclosure setting an industry benchmark.
Energy arbitrage between data centers and vehicles.
Charging at low-cost power during downtimes could generate additional revenue by operating Robo-taxis during peak hours and via V2G and ESS.
Reader checklist: Prepare for 2026
Check the autonomous driving pilot policies and operation permit roadmap of your resident city.
Analyze the charging infrastructure and electricity pricing system to estimate the potential for reduced mobility costs.
When renewing insurance, compare rates based on driving data and reflect Robo-taxi usage patterns.
In tasks and logistics, reduce lead time through nighttime movement and non-stop operating strategies.
Shift workforce skills towards robot collaboration and data operation capabilities to capture productivity bonuses.
< Summary >
Franz’s statement has increased the likelihood of the Cybertruck being deployed on roads in 2026, and the combination of two-passenger optimization and FSD opens up the unit economics for Robo-taxis.
The third generation of Optimus is set for mass production in 2026, aiming for 1 million units by 2030, expanding humanoid applications across industries and households.
The European regulatory issues for Cybertruck remind us of pedestrian protection and shape regulations, while city sandboxes and data governance are key to commercialization.
Falling transportation costs and increased productivity suggest potential for disinflationary pressures that could positively influence the global economic outlook and support a gradual easing of interest rate paths.
The integration of data centers, energy, and mobility constitutes the core of Tesla-like digital transformation, and in 2026, keep an eye on paid miles, accident rates, utilization rates, energy costs, and Optimus’s task success rates.
SEO keywords have been naturally included in the text: global economic outlook, inflation, interest rates, AI trends, and digital transformation.
[Related articles…]
How the price disruption from Robo-taxis flips urban finance and insurance
*Source: [ 오늘의 테슬라 뉴스 ]
– 2026년 테슬라 공식 출시 확정! 머스크의 사이버캡 드디어 출격, 로보택시 시장 판도 뒤집는다!?
● US Korea FX Pact, No Swap Shock
[Breaking News·Immediate Analysis] Announcement of the Korea-U.S. ‘Exchange Rate Policy Agreement’, the Absence of Currency Swaps as a Message and Real Impact
Key Points of This Article
1) This article summarizes how the hidden clauses on ‘symmetric intervention, government investment institutions, and transparency’ in the agreement will constrain Korea’s foreign exchange policy tools in the future.
2) It presents the essence of the bilateral exchange rate diplomacy ‘Plaza Accord 2.0’ that started without currency swaps, and the path of the dollar weakness strategy.
3) It explains the possible risk mitigation of observation countries in the exchange rate report while simultaneously increasing the KRW liquidity premium.
4) It provides an action plan for exchange rate hedging for corporations and investors, along with a checklist by timeline for 1 week, 1 month, and 1 quarter.
5) From the perspective of AI trends, it suggests a practical monitoring framework that connects public data, high-frequency alternative indicators, and stablecoin liquidity.
1. Timeline and Summary of Key Points of the Agreement
On April 24, 2024, in Washington D.C., the exchange rate issue was officially brought to the table at the ‘2+2 Trade Consultation’ at the request of the United States.
On October 1, 2025, at 09:15 (Korean time), the financial authorities of Korea and the U.S. jointly announced the exchange rate policy agreement.
The core principle reconfirms the existing principle that ‘the value of one’s currency shall not be manipulated.’
Clause ① Macroeconomic soundness and capital movement measures shall not target competitive exchange rates.
Clause ② Overseas investments by government investment institutions (GIV) should be for risk adjustment and diversification purposes and cannot be a tool for exchange rate targeting.
Clause ③ Foreign exchange market intervention shall only be considered in cases of excessive volatility or disorder, implemented symmetrically regardless of direction.
With a strengthened transparency framework, Korea will privately share monthly details of market stabilizing measures that are currently disclosed quarterly with the U.S. Treasury.
Additionally, it will publicly disclose monthly foreign exchange reserves and futures positions based on IMF templates, along with the annual currency composition of foreign exchange reserves.
In conclusion, the agreement on the surface institutionalizes the existing principles and strengthens the framework for continuous communication and monitoring.
2. The ‘Real Changes’ That Others Might Miss
Firstly, the principle of symmetric intervention structurally limits unilateral KRW defense.
In times of rapid KRW depreciation, the policy of unilaterally selling large amounts of dollars to defend the currency will face an increased burden of explanation regarding ‘symmetry’ retrospectively.
This may reduce the frequency of the ‘last resort’ for exchange rate volatility shocks and weaken market defense expectations.
Secondly, the GIV clause narrows opportunities for ‘indirect exchange rate stabilization’ through government investment institutions like the Korea Investment Corporation (KIC).
Even if not openly targeted, the transparency and firewall of operations will be strengthened to avoid considering foreign investment and rebalancing processes as instruments for exchange rate targeting.
Thirdly, the transparency clause signifies the end of ‘strategic ambiguity.’
The sharing of monthly intervention details privately and the disclosure of currency composition may provoke anticipatory interpretations in the market, increasing front-running risks.
Fourthly, the limitation of the objectives of macroeconomic soundness and capital movement measures increases the burden of justification for future changes in entry and exit taxation or futures position regulations.
This results in reduced policy flexibility, but simultaneously increases the predictability of the system.
3. Why Now and Why is There No ‘Swap’?
The picture of liquidity backstop (swaps) being postponed due to concerns about moral hazard while alleviating issues in the U.S. Treasury’s exchange rate report is evident.
The U.S. Federal Reserve has limited standing swaps to a few key reserve institutions, establishing temporary lines only in emergencies (2008·2020).
Currently, it appears that there is an evaluation that global system stress is not in an emergency phase.
In summary, the agreement provides ‘rules, oversight, and transparency,’ and without a swap, a ‘liquidity lifeline’ is absent, resulting in the KRW risk premium persisting.
4. Is It ‘Plaza Accord 2.0’?: A Mechanistic Perspective
In 1985, a multilateral cooperation was used to induce dollar weakness, whereas in the 2020s, there is a tendency to produce results cumulatively through bilateral agreements.
This agreement does not directly mention exchange rate targets, but through the constraints of intervention symmetry, transparency, and GIV, it reduces the ‘means of resistance.’
The United States has the incentive to pursue both manufacturing reshoring and export competitiveness (preferencing dollar weakness) by combining tariffs, industrial policies, and exchange rate diplomacy.
If this trend accumulates, the direction of the dollar may gradually weaken, while currencies that were previously ‘resistant’ will be forced to gradually strengthen.
Nonetheless, if the won-dollar exchange rate remains high, it signals that Korean-specific factors like the external balance (energy, transportation, tourism) and portfolio outflows are significant.
5. Connection with the Exchange Rate Report (Observation Country)
The U.S. designates observation countries based on three factors: trade surplus with the U.S., current account surplus, and foreign exchange intervention.
Korea has continuously met two-thirds of the criteria due to structural surplus factors, and label risk exists regardless of ‘manipulation.’
This agreement holds the potential to alleviate the tone of the report through the commitment to intervention symmetry and transparency improvement.
However, there is no guarantee of removal from the observation list, and there is a high possibility of practical benefits in the future regarding the wording of the report and preventing escalation.
6. Market Impact Timeline
Short-term (1 week): The absence of swaps may limit the rally, while volatility could initially dampen before potentially increasing again.
1 month: Confirmation of the tone of the exchange rate report is the first event, with adjustments in the KRW premium linked to oil prices and U.S. real interest rates being crucial.
1 quarter: As the monthly intervention details accumulate, the speed of market learning regarding policy response functions will accelerate, refining tactics for both short and long positions.
7. Action Plan for Corporations and Investors
For exporting and importing companies: Categorize the exchange rate hedging target ratios by grade and diversify costs using phased (ladder) NDF and options (call spread, seagull) combinations.
Incorporate ‘exchange rate adjustment clauses’ into pricing policies and stagger shipment and payment timings to reduce dollar cash flow volatility.
For treasury teams: Weekly checks on cross-currency basis and foreign currency LCR are necessary, along with calendar management to avoid concentration of rollover maturities.
For investors: Prepare for a gradual dollar weakness scenario based on global economic outlook, while pricing separately for Korea-specific external balance risks.
For bonds and interest rates: The pass-through of exchange rate instability to inflation (import prices) may slow the pace of interest rate cuts, so split approaches to duration positions are advantageous.
8. Upgrade Monitoring with AI Trends and Data Strategies
With increased data availability from the agreement, build an AI-based real-time ‘exchange rate risk dashboard.’
Core indicators: Summarize and conduct sentiment analysis of IMF templates (foreign exchange reserves, futures positions), Bank of Korea announcements, and U.S. Treasury report texts using LLM.
Alternative indicators: Combine NDF-spot basis, cross-currency basis, CDS, oil prices, refining margins, shipping rates, and semiconductor business cycle leading indicators.
Crypto/stablecoin: Use fluctuations in the market capitalizations of USDT and USDC, on-chain dollar demand, and the ‘Kimchi premium’ as high-frequency signals for offshore dollar liquidity.
Model: Estimate potential intervention periods using volatility regime switches (HMM) and set up automated hedging based on event-triggered mechanisms.
9. Scenario-Based Exchange Rate, Interest Rate, Inflation Pathways
Baseline scenario: A gradual dollar weakness takes place while Korea’s improvement in external balance is slow, leading to the possibility that the won-dollar exchange rate stabilizes after fluctuating around a high point.
Strong KRW scenario: Acceleration occurs under the combination of declining oil prices, robust semiconductor exports, improved report tone, and temporary liquidity backstop news.
Weak KRW scenario: In cases of energy shocks, geopolitical risks, and intensified portfolio outflows, the defense may decrease, stimulating inflation through rising import prices, which could delay interest rate cuts.
10. Checkpoints
1) Changes in the wording of the exchange rate report and observation country status.
2) Market interpretations and dollar composition signals following the first public disclosure of currency composition in foreign exchange reserves.
3) Simultaneous movements of risk proxies, such as oil prices, U.S. real interest rates, basis, and CDS.
4) The rebalancing calendar of government investment institutions and the consistency of policy communication.
5) Whether discussions about temporary swaps are reignited.
< Summary >
The Korea-U.S. agreement has solidified the rules of foreign exchange policies through ‘symmetric intervention, GIV constraints, and enhanced transparency,’ while the absence of swaps leaves a KRW liquidity premium remaining.
While it is a superficial reconfirmation, in reality, it reduces the degree of intervention freedom and decreases strategic ambiguity, accelerating the market’s learning of policy responses.
This aligns with the tendency of ‘Plaza 2.0’ track, cumulatively encouraging a gradual dollar weakness.
While there are expectations for a tone reduction regarding the exchange rate report risk, a guarantee of removal is not assured, and factors such as oil prices, external balances, and portfolio flows will influence the KRW pathway.
Corporations and investors should preemptively respond to volatility regime changes by integrating hedging categorization, alternative indicator monitoring, and AI-based alert systems.
[Related Articles…]
Immediate Explanation of the Exchange Rate Agreement: What the Transparency Obligations Mean
Plaza Accord 2.0? At the Crossroads of Korean Exports and Interest Rates
*Source: [ 경제 읽어주는 남자(김광석TV) ]
– [속보] 한미 재무당국간 환율정책 합의 발표, 통화스와프는 없는 환율합의. 한국판 플라자합의 시작인가? [즉시분석]
● Liquidity Shock Ignites Gold and Stocks, AI Act Two Powers Up
Conditions for the rally of volatility, liquidity, gold, and stocks at the same time in October, and the roadmap for the second act of AI.
This article contains three main points.
First, the true nature of the ‘acceleration of liquidity’ that most people overlook, what the regional engines are, and how it spreads to the gold and stock markets with a three-month lag.
Second, how the central bank’s rebalancing is changing between the dollar and gold, and the hidden indicators that provide hints for investment timing.
Third, a checklist for practically executing “buy the dip” during the volatile period in October, and an investment map where the focus shifts to power, memory, cooling, and networks in the second act of the AI trend.
1) What money is currently being released: The transition of global liquidity engines.
Liquidity is more directly linked to the ‘rate of increase’ rather than the simple total.
When looking at indicators like M2 as a Z-score, one can see not just levels but also acceleration, or the slope.
In the U.S., while M2 is increasing, the acceleration has been in a recurring phase of deceleration.
Conversely, the Eurozone, China, and Japan often experience phases of increasing acceleration due to policy and credit cycles.
This asymmetry is key to the global economic outlook, as funds tend to boost risk asset premiums in areas with relatively higher acceleration.
Historically, global M2 acceleration often reflects in gold and the S&P 500 with a 1 to 3-month lag.
In conclusion, when the acceleration of liquidity rises, gold and stocks tend to rally simultaneously, diminishing the real value of cash.
Thus, the perspective of viewing gold as a ‘shadow of liquidity’ rather than merely a ‘safe haven’ is gaining traction these days.
2) The subtle tug-of-war between gold and the dollar: The silent rebalancing of central banks.
Various international statistics have shown that central banks are gradually reducing their holdings of U.S. Treasuries within foreign exchange reserves while slowly increasing their gold allocations.
This trend can be interpreted not as an issue of specific countries, but as a general movement within the institutional framework towards a ‘quasi-insurance’ nature.
While this change does not immediately break the structural trend of dollar strength, it tends to increase gold’s beta during liquidity expansion periods.
In other words, even if interest rates and the dollar are strong in the short term, gold can rally counterintuitively in phases of rising liquidity acceleration.
There are two practical investment points.
- Gold channel: Do not only focus on physical gold and ETFs; also consider how refining, transportation, and storage costs impact spreads (premiums).
- Dollar channel: In addition to monitoring the DXY, also track changes in net issuance of U.S. Treasuries, TGA, and reverse repo (RRP) balances to check for net increases in system liquidity.
3) October seasonality: Short-term correction scenarios amid a bullish trend and conditions for ‘buying the dip.’
October is statistically a month with high volatility, making it a good time for adjusting valuations based on quarterly earnings and guidance.
Individuals tend to net buy, while institutions increase hedges and cautiously maintain long exposure, creating a pattern of ‘retail offense and institutional defense.’
In this context, the important aspect is not directional optimism but tactics.
Buying the dip should not be done at any time, but only when at least three of the following conditions are met:
- Improvement in market breadth indicators (increased number of rising stocks, transition to relative strength of the Equal-Weight index).
- A sharp rise in the volatility index (VIX) followed by stable volume within 2 to 3 trading days.
- Normalization of the skew in the options market, alleviating short-term demand excess in puts.
- Appearance of reversal candles in major indices near the 50-day or 100-day moving averages.
- Absence of major earnings or guidance shocks from megacaps, or price reactions that are ‘less vulnerable to bad news.’
4) Portfolio play diagram: When, what, and how.
Weeks 1-3 of October: Volatility defense.
- Reduce high beta and overheated stocks to a delta-neutral position and hedge a portion with protective puts or call spreads.
- Maintain a cash position of 15-25% for flexible responses.
- Conduct rotation tests into energy, value stocks, and dividend-paying stocks with solid cash flow.
Weeks 4 of October – Weeks 2 of November: Candidate period for buying the dip execution. - Confirm improvement in breadth, and begin phased entry into quality growth stocks and the ‘second link’ of the AI value chain (power, HBM, cooling, networks).
- In passive strategies, focus on Equal-Weight, and in active strategies, concentrate on stocks with earnings surprises and raised guidance.
Late November – year-end: Momentum management. - When entering the Santa rally, begin taking profits from tier 2 stocks at signs of overheating.
- Raise the trailing stop to the profit zone to secure risk-reward ratios.
First half of 2025: Rebalancing. - Prepare for risks of inflation reignition and interest rate rises by diversifying duration and adjusting the extent of dollar hedges.
5) AI trend second act: From semiconductors to ‘power, memory, cooling, and networks.’
The first act involved GPU shortages and a boom in model training, while the second act focuses on power and operational optimization.
The power grid is the bottleneck.
- In data centers, power allocation is tantamount to growth rate.
- Lead times for transformers and switchgear, backup from gas turbines and fuel cells, and regions capable of load shifting are critical factors.
Memory is a bottleneck with HBM. - Packaging (like COWoS) and HBM stack yield influence high-end training and inference performance.
- During upward cycles, memory companies gain greater pricing power and cash flow leverage.
Cooling is shifting from air cooling to immersion and liquid cooling. - The rise in power density per rack increases the adoption of immersion cooling, stimulating the ASPs of thermal management components and materials.
The network upgrades to 400/800G create a ripple effect in investment. - The value chain from switches, optical modules, cables, to NICs broadly benefits.
Software transitions to ‘monetization of inference.’ - When copilots and agents connect with actual productivity metrics, corporate adoption accelerates.
- Combining open-source models with on-premise inference gains advantages in security and cost, while edge AI and NPU proliferate.
6) Risk checklist: Reheating inflation and liquidity reversal.
If inflation rises persistently, expectations for a pivot in interest rates may be delayed, leading to multiple compressions.
A surge in oil prices could trigger both margin squeezes and rising expectations for inflation.
Increased net issuance from the Treasury, ongoing QT, and depletion of RRPs could cause headwinds for system liquidity.
If big tech earnings fall short of expectations, the beta of indices can increase, directly contributing to volatility expansion.
AI is influenced in the short term by power, packaging, HBM yield, and regulatory issues that can pivot upon relistings.
7) Directly usable monitoring indicators and alarm settings.
Liquidity: Trends in global and U.S. M2 growth rates and the directionalities of Z-scores.
Dollar and interest rates: Trends of DXY, the 10-year U.S. treasury yield, and real interest rates.
Breadth: Ratios of advancing/declining stocks, 52-week new highs/lows, and the ratio of market cap-weighted indices to equal-weight indices.
Supply-demand: Net purchases of cash, options, and ETFs by individuals, institutions, and overseas traders; CFTC positions.
Options: Put/call ratios and skew, and the speed of normalization following spikes in the VIX.
Crypto liquidity: Track the trend of stablecoin market capitalization as a supplementary indicator.
8) Chronological roadmap: Execution checkpoints.
Weeks 1-2 of October.
- Adjust positions and activate hedges in anticipation of increased volatility.
- Confirm the acceleration of liquidity and whether breadth is deteriorating.
Weeks 3-4 of October. - If the price reaction to earnings season changes to being ‘less vulnerable to bad news’, take initial steps to buy the dip.
- Gradually increase positions in energy, value, and overseas markets.
November. - If breadth continues to improve, make a second purchase focusing on growth, quality, and the AI value chain.
- Despite simultaneous strength in gold and the dollar, manage risks and roll down.
December – year-end. - Take profits on overheating signals and rebalance.
- Reconstruct hedges for scenarios regarding inflation, interest rates, and liquidity for 2025.
Practical tips: Mechanical rules for ‘buying the dip.’
Divide purchases into 3-5 tranches, weighting according to the degree of decline rather than equal amounts.
The line in the sand for cutting losses or re-entering should be below the 200-day line or recent swing lows.
Focus on core positions through ETFs and only add individual stocks when earnings and guidance are confirmed to be positive.
Hedging should combine index puts and individual stock call spreads to minimize costs.
Why is this content ‘not found elsewhere’?
Most people only focus on the total amount of liquidity, but what drives the market is the ‘change in the rate of increase.’
The acceleration viewed through the Z-score, the transition of regional engines, and the subtle changes in central bank rebalancing are the keys to simultaneous rallies.
Regarding AI, it is not just about stock names; the physical constraints represented by power, memory, cooling, and networks dictate the upper limits of valuation.
Therefore, while the possibility of correction this October presents an opportunity, entering mechanically only when conditions are met increases the chances of success.
< Summary >
- Key points: The ‘acceleration’ of liquidity leads the rally in gold and the stock market.
- October strategy: Defensive measures against volatility, conditional buying of dips, checking breadth and options skews, and earnings reactions.
- Rotation: Energy, value, overseas markets, and the second act of AI, focusing on power, HBM, cooling, and networks.
- Risks: Reheating inflation, liquidity headwinds, and big tech performance.
- Execution: Gradual purchases, rule-based hedging, and momentum management year-end ahead of the 2025 rebalancing.
[Related articles…]
- Accelerating central bank gold purchases: A signal of dollar deleveraging
- AI Data Center Power Crisis: 2025 Investment Roadmap
*Source: [ Maeil Business Newspaper ]
– [홍장원의 불앤베어] 공격하는 개미 VS 방어하는 기관. “10월에 조정장 오면 바이더딥 해라”
