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What we are seeing now is primarily a leverage and positioning event.
Too much capital, too much leverage and too many investors became concentrated in the same trade.
Those positions are now being reduced, mainly through forced selling rather than a genuine change in the long term fundamentals.
This is important because the underlying memory shortage is still tthere. AI infrastructure demand has created acute supply constraints, while chipmakers have prioritized higher-margin data centres products.
Memory availability has tightened and prices have risen sharply.
However, the market did not simply price in that fundamental improvement but It also added momentum, leverage and increasingly crowded positioning on top of it.
Yes, the easy money in the AI trade has probably already been made.
That does not mean the AI investment cycle is over. It means investors can no longer assume that every company exposed to AI will continue rising simply because demand remains strong.
Parabolic share-price moves are not always evidence of equally strong fundamentals and they can often be a sign that momentum investors, leveraged funds and short-term traders are reinforcing the same move.
As more capital enters, rising prices appear to confirm the original thesis, attracting even more capital.
Eventually, price stops reflecting only the underlying balance between supply and demand.
It also begins to reflect how much speculative money has entered the trade and how much of that money may be forced to exit when volatility rises.
The AI demand story remains intact, and the supply-demand imbalance in memory has not suddenly disappeared, companies are still competing for limited memory supply, while manufacturers continue to prioritise the most profitable products used in AI servers and data centres.
But not every daily or weekly price move is driven by fundamentals.
Narratives frequently follow price and when memory stocks are rising, investors focus on shortages, pricing power and AI demand.
When the same stocks fall, the discussion quickly shifts towards Chinese competition, improved efficiency or the risk of future oversupply.
I am seeing some comparisons with the 1990s telecom boom or the housing bubble but they are only partly appropriate.
In both of those periods, supply eventually moved far ahead of genuine demand. Too much fibre-optic capacity was built during the telecom boom, while too many houses were constructed ahead of the financial crisis.
The current AI cycle is different.
Demand has initially grown faster than supply, particularly in advanced memory and data-centres infrastructure.
The problem is that financial markets then placed excessive leverage and unrealistic expectations on top of a genuine bottleneck.
Benjamin Graham famously described the market as a voting machine in the short term and a weighing machine in the long term.
Right now, the voting is being dominated by crowding, leverage and forced liquidation.
Investors are selling because they need to reduce risk, not necessarily because the structural demand for AI infrastructure has disappeared.
Over time, the market will return to weighing the actual fundamentals - AI investment, memory demand, supply additions, pricing and corporate earnings.
What is currently being liquidated is not the existence of AI demand.
It is the excessive leverage and speculative positioning that has accumulated around the story.
With this being said, I am still being cautious as we have the upcoming Fed decision and big tech earnings,