“1011 Inner Circle Whale” Representative: Maintains BTC Position Built Around $60,000, AI Storage Demand Remains Strong but No Chasing for Now

Odaily News, Garrett Jin, representative of the "1011 Inner Circle Whale," released a weekly market report stating that gold was previously under observation but has recently broken out of its consolidation range and has now shifted to a long-term allocation opportunity, with the investment thesis still based on the long-term trend of a weakening US dollar. Regarding Bitcoin, he stated that since approaching the low of approximately $57,700 in July, the market has consistently met the conditions for bottoming out. He has not changed his view and maintains the position built near $60,000.

Regarding AI storage, he previously suggested gradually building positions in memory chips and buying on dips, but the market skipped the pullback and rallied directly. He has since sold half of his rebound positions, not because the investment thesis has changed, but because he believes the short-term rally is more driven by capital flows. The risk from leveraged ETFs in South Korea has not been fully released. Although JPMorgan claims related exposure has declined 66% from its peak, his calculations show a decline of approximately 38%, mainly due to a drop in net asset value rather than investor exits. The leverage effect has weakened but not disappeared.

Garrett Jin emphasized that this does not mean he is bearish on storage demand. SK Hynix's 2026 capacity is already sold out, and Micron's orders extend through 2028. AI storage demand is expected to remain strong until the second half of 2027. However, the storage industry remains cyclical in nature, and related stocks have already risen by hundreds of percentage points. Cyclical stocks find it difficult to sustain rallies through valuation expansion alone over the long term. The current AI investment cycle is transitioning from the "early capital expenditure phase" to the "mid-term return validation phase." Previously, the market rewarded companies for expanding AI capital expenditures, but now it is beginning to focus on whether those investments can translate into revenue.