David Tepper's Appaloosa Management disclosed a $7.7 billion equity portfolio with 40% — roughly $3.1 billion — concentrated in three names: Amazon, Micron Technology, and Taiwan Semiconductor Manufacturing. The allocation surfaced in the fund's latest 13F filing, marking one of the sharpest concentration tilts in Appaloosa's public history outside crisis-era financials.
Amazon represents the largest single position, followed by Micron and TSMC in descending order. The three holdings span the AI infrastructure stack: hyperscale cloud capital expenditure (Amazon Web Services), high-bandwidth memory for training clusters (Micron), and advanced node logic manufacturing (TSMC). Appaloosa entered the Micron stake during Q3 2024, adding 1.8 million shares at an average cost near $105, then held through the stock's November earnings volatility. The TSMC position expanded by 22% quarter-over-quarter, now totaling approximately 4.2 million ADRs. Amazon remained the anchor, with minimal trimming despite the stock's 38% year-to-date gain through December.
The sizing matters because Tepper historically reserves 30%-plus concentration for macro conviction trades — Citigroup and Bank of America in 2009, energy in 2016. This is not portfolio drift. The tilt implies Appaloosa sees semiconductor demand from AI training and inference workloads sustaining through 2026, even as hyperscaler commentary on capital discipline has caused rotations elsewhere. Micron's HBM3E ramp, contracted primarily to Nvidia and Google, represents 15%-20% of its FY25 revenue forecast. TSMC's N3E and N2 nodes are sole-sourced for the majority of AI accelerator production, with utilization rates above 90% through mid-2025. Amazon's AWS segment posted 19% year-over-year revenue growth in Q3, driven by compute-intensive workloads that correlate directly with GPU instance scaling. Tepper's bet assumes these dynamics tighten, not loosen.
The structure also highlights supply-chain interdependence. TSMC manufactures the logic dies. Micron supplies the memory stacks. Amazon buys the finished systems and sells the inference capacity. A disruption at any node — geopolitical risk in Taiwan, HBM yield issues, hyperscaler capex cuts — compresses returns across all three. Appaloosa's willingness to accept that correlation, rather than hedge it, suggests internal models price tail risks below consensus.
Operators should track AWS capex guidance in Amazon's Q4 earnings (late January), TSMC's N2 yield commentary in its January 16 earnings call, and Micron's HBM pricing power in its March quarter guidance. Any divergence between hyperscaler infrastructure spend and semiconductor revenue growth will test the thesis. Family offices with equity hedge exposure should note that Tepper's disclosure lag means the positions could have shifted since September 30; monitor Form 4 filings for Appaloosa principals or amendments to the 13F for material changes.
The filing also revealed Appaloosa trimmed Meta by 18% and exited Microsoft entirely, reallocating capital down the stack. The message: Tepper prefers semiconductor picks-and-shovels over application-layer platform risk. Taiwan Semiconductor's January earnings will clarify whether 3nm demand from hyperscalers can offset any smartphone or automotive softness. If TSMC guides N3 wafer starts above 140,000 per month for Q1, the Appaloosa thesis tightens. If guidance lands below 130,000, the concentration becomes a test of conviction in the face of inventory normalization.
The takeaway
Tepper's $3.1B AI-stack concentration mirrors his crisis-era bank trades in structure — and carries similar correlation risk.
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