Momentum Facing an Intermediate Trend Shift.
Happy weekend, everyone.
Taking a step back from the intraday noise to look at the macro picture, and there is some serious food for thought on the charts.
After an incredible, aggressive compounding run through April and May, the BTF has officially locked in a regime change, decoupling from the upper trend line and printing a clean, structural sell signal via a new solid red block.
The Interconnected Narrative:
We need to realise that we are operating in a highly concentrated, symbiotic macro loop right now.
Memory Stocks & AI Infrastructure: The engine of this entire global cycle.
The Liquidity Siphon (SpaceX, High-Beta Tech): Blockbuster liquidity events and mega-cap tech crowded trades have concentrated market depth into a very tight cluster.
When the global tech supply chain bellwether (#KOSPI) flashes a structural pause like this, it tells us the global liquidity tide is temporarily shifting.
To be absolutely clear: This is NOT a call for a secular 'bubble top' or an end-of-days market crash. (although bear markets do start with a trend shift of course)
Instead, what we are witnessing is a well-defined intermediate trend shift.
The market has moved from a smooth, low-volatility markup phase into a high-volatility distribution/correction phase.
As student-traders of the market know, the highest up and down days historically cluster inside corrective and bearish structures.
Bull markets walk up a slow escalator; corrective regimes ride a violent elevator.Expect wide, two-way tracking ranges ahead.
This incoming volatility shouldn't scare you—it should open up massive multi-turn trading ranges for those using mechanical, trend-following frameworks to manage risk.
Protect your capital, respect the block flips, and don't chase the wild intraday squeezes blindly.
The Bull Case: Data centers require an endless, non-negotiable stream of High Bandwidth Memory (HBM) to run AI models, decoupling memory demand from old-school PC/smartphone upgrade cycles and turning it into a secular growth story.
The Bear Case: "Every memory cycle in history feels 'different' at the top, but massive capital expenditure booms inevitably lead to factory over expansion, a sudden supply glut, and a brutal collapse in pricing power.
Will There Be a "DeepSeek Round 2"?
We are possibly living in it.
The disruption DeepSeek caused wasn't a one-time fluke; it validated an entirely new playbook that the market has fully institutionalised.
DeepSeek proved to the global market that a smart, sparse Mixture-of-Experts (MoE) architecture paired with aggressive Multi-head Latent Attention (MLA) and reinforcement learning (RL) could match the raw intelligence of Western frontier models at 1/10th or 1/30th of the training and inference cost.
DeepSeek has continued pushing its iterative release cadence, launching DeepSeek V4.
The innovations coming out of this "Round 2" clarify exactly how iterative AI improvements are scaling: Context Efficiency Upgrades: Processing long context windows (like V4's 1-million token limit) used to require prohibitive computational budgets.
DeepSeek's newer iterations use architectural mechanisms like Compressed Sparse Attention (CSA) and Manifold-Constrained Hyper-Connections (mHC) to maintain training stability and slice memory footprints by up to 90%.
Algorithmic Efficiency Gains: The shift away from standard training optimisers toward custom alternatives like the Muon optimiser allows newer models to achieve rapid convergence on massive datasets (exceeding 32 trillion tokens) while bypassing traditional, expensive GPU clusters.
The "Think" Compute Multiplier: Instead of relying entirely on massive static parameter counts, modern iterations introduce multi-tier reasoning effort modes ("Think High", "Think Max"). This shifts the heavy lifting from the training phase to inference time, allowing a leaner model to dynamically scale its compute depending on how hard the user's question actually is.
The Structural Bottom Line
The "Round 2" of AI iteration is focused on unit economics and structural efficiency.
The industry has pivoted from asking "How large can we build this model?" to "How much performance can we extract out of minimal active parameter footprints?"
Expect the models in your pocket to rapidly match the intelligence of yesterday's cloud giants, while the cloud giants focus on running heavy, multi-step agentic pipelines.
#KOSPI
#TradingView
#BallaJiTrendFollower
#TechnicalAnalysis
#Macro
#AIInfrastructure
#TrendFollower
#Markets
#Volatility
#RiskManagement
#PriceAction
Happy weekend, everyone.
Taking a step back from the intraday noise to look at the macro picture, and there is some serious food for thought on the charts.
After an incredible, aggressive compounding run through April and May, the BTF has officially locked in a regime change, decoupling from the upper trend line and printing a clean, structural sell signal via a new solid red block.
The Interconnected Narrative:
We need to realise that we are operating in a highly concentrated, symbiotic macro loop right now.
Memory Stocks & AI Infrastructure: The engine of this entire global cycle.
The Liquidity Siphon (SpaceX, High-Beta Tech): Blockbuster liquidity events and mega-cap tech crowded trades have concentrated market depth into a very tight cluster.
When the global tech supply chain bellwether (#KOSPI) flashes a structural pause like this, it tells us the global liquidity tide is temporarily shifting.
To be absolutely clear: This is NOT a call for a secular 'bubble top' or an end-of-days market crash. (although bear markets do start with a trend shift of course)
Instead, what we are witnessing is a well-defined intermediate trend shift.
The market has moved from a smooth, low-volatility markup phase into a high-volatility distribution/correction phase.
As student-traders of the market know, the highest up and down days historically cluster inside corrective and bearish structures.
Bull markets walk up a slow escalator; corrective regimes ride a violent elevator.Expect wide, two-way tracking ranges ahead.
This incoming volatility shouldn't scare you—it should open up massive multi-turn trading ranges for those using mechanical, trend-following frameworks to manage risk.
Protect your capital, respect the block flips, and don't chase the wild intraday squeezes blindly.
The Bull Case: Data centers require an endless, non-negotiable stream of High Bandwidth Memory (HBM) to run AI models, decoupling memory demand from old-school PC/smartphone upgrade cycles and turning it into a secular growth story.
The Bear Case: "Every memory cycle in history feels 'different' at the top, but massive capital expenditure booms inevitably lead to factory over expansion, a sudden supply glut, and a brutal collapse in pricing power.
Will There Be a "DeepSeek Round 2"?
We are possibly living in it.
The disruption DeepSeek caused wasn't a one-time fluke; it validated an entirely new playbook that the market has fully institutionalised.
DeepSeek proved to the global market that a smart, sparse Mixture-of-Experts (MoE) architecture paired with aggressive Multi-head Latent Attention (MLA) and reinforcement learning (RL) could match the raw intelligence of Western frontier models at 1/10th or 1/30th of the training and inference cost.
DeepSeek has continued pushing its iterative release cadence, launching DeepSeek V4.
The innovations coming out of this "Round 2" clarify exactly how iterative AI improvements are scaling: Context Efficiency Upgrades: Processing long context windows (like V4's 1-million token limit) used to require prohibitive computational budgets.
DeepSeek's newer iterations use architectural mechanisms like Compressed Sparse Attention (CSA) and Manifold-Constrained Hyper-Connections (mHC) to maintain training stability and slice memory footprints by up to 90%.
Algorithmic Efficiency Gains: The shift away from standard training optimisers toward custom alternatives like the Muon optimiser allows newer models to achieve rapid convergence on massive datasets (exceeding 32 trillion tokens) while bypassing traditional, expensive GPU clusters.
The "Think" Compute Multiplier: Instead of relying entirely on massive static parameter counts, modern iterations introduce multi-tier reasoning effort modes ("Think High", "Think Max"). This shifts the heavy lifting from the training phase to inference time, allowing a leaner model to dynamically scale its compute depending on how hard the user's question actually is.
The Structural Bottom Line
The "Round 2" of AI iteration is focused on unit economics and structural efficiency.
The industry has pivoted from asking "How large can we build this model?" to "How much performance can we extract out of minimal active parameter footprints?"
Expect the models in your pocket to rapidly match the intelligence of yesterday's cloud giants, while the cloud giants focus on running heavy, multi-step agentic pipelines.
#KOSPI
#TradingView
#BallaJiTrendFollower
#TechnicalAnalysis
#Macro
#AIInfrastructure
#TrendFollower
#Markets
#Volatility
#RiskManagement
#PriceAction
บันทึก
My Trend follower is flashing a high value sell zone, and a clear change in trend... lets see how it opens monday
บันทึก
samsung บันทึก
SK HYNIX บันทึก
Hyundai บันทึก
#kospi is ripping บันทึก
sk hynix down -8%stochastics embedded
BTF still green
บันทึก
2nd JulyBallaji Trend Follower on the 1D timeframe
ปิดการเทรด ด้วยตนเอง
currently off -27% officially a bear market
#kospi
#memorystocks
#AI
คำจำกัดสิทธิ์ความรับผิดชอบ
ข้อมูลและบทความไม่ได้มีวัตถุประสงค์เพื่อก่อให้เกิดกิจกรรมทางการเงิน, การลงทุน, การซื้อขาย, ข้อเสนอแนะ หรือคำแนะนำประเภทอื่น ๆ ที่ให้หรือรับรองโดย TradingView อ่านเพิ่มเติมใน ข้อกำหนดการใช้งาน
คำจำกัดสิทธิ์ความรับผิดชอบ
ข้อมูลและบทความไม่ได้มีวัตถุประสงค์เพื่อก่อให้เกิดกิจกรรมทางการเงิน, การลงทุน, การซื้อขาย, ข้อเสนอแนะ หรือคำแนะนำประเภทอื่น ๆ ที่ให้หรือรับรองโดย TradingView อ่านเพิ่มเติมใน ข้อกำหนดการใช้งาน