Investment Portfolio
Selected holdings shown for illustrative purposes only. This is not a recommendation to buy or sell any security. Private investments are shown on an anonymized basis to protect confidentiality.
IMPORTANT NOTICE: The securities listed herein are held by funds managed by AlphaStone and are not available for direct investment. Past performance does not guarantee future results. Holdings are subject to change without notice. This presentation does not constitute investment advice or an offer to sell or solicitation to buy securities. Prospective investors should consult their own investment, legal, and tax advisors.
Public Markets
NVIDIA (NVDA)
The full-stack AI platform: dominant accelerators, the CUDA software moat, and a move into the model and developer layer. Its fiscal-2028 outlook answered the market's main doubt about how durable the growth is; we think it is durable on a three-year horizon.
Thesis: 2016
Micron (MU)
Memory is the binding constraint of the AI buildout: high-bandwidth memory remains supply-limited, and as gains shift from transistor density to packaging and bandwidth, memory content per system rises. Held through volatility on a multi-year view.
Thesis: 2024
Alphabet (GOOGL)
Search at record levels, Cloud compounding at high margins on a large committed backlog, and its in-house AI chips (TPUs) now sold to outside customers. Fully valued near term; a core, multi-year hold.
Thesis: Early 2025
AMD (AMD)
Two engines: the second-largest GPU supplier in a market growing faster than share can shift, and the CPUs that autonomous AI agents run on. Consolidating after a large run; a hold, not a buy, at these levels.
Thesis: 2015
Meta Platforms (META)
The social graph as an AI-leveraged advertising engine, with compute and model upgrades compounding monetization and the litigation overhang now settled. We expect earnings momentum to carry through 2027; a stall in ad monetization would change that view.
Thesis: 2026
Private Markets
Private Portfolio
A broad portfolio of private positions built across multiple vintages, concentrated in financial technology and the AI compute stack, from silicon to infrastructure. The themes below are a small, representative sample, shown on an anonymized basis.
Confidential — Private Capital Marketplace
Fintech building a marketplace for illiquid pools of private capital, bringing price discovery and liquidity to assets that have historically had neither.
Confidential — AI Silicon
AI chip company rethinking how AI processors use memory, with new designs for on-chip (SRAM) and off-chip (DRAM) memory aimed at the bandwidth bottleneck between compute and memory.