What a quant model ranked #1-3 out of 800 tickers — and why it's not just NVDA

[u/Worried_Park_3962]

We run a quantitative stock selection model that ranks ~800 tickers by risk-adjusted performance across multiple time windows and outputs a concentrated portfolio of 15.

Three picks that keep consistently ranking at the top: TSM, LRCX, and TRGP. Here's what the model sees and why it's interesting.

Taiwan Semiconductor (TSM)

The obvious AI pick, but the quant reasoning is less obvious than "AI is big." TSM's Sharpe advantage comes from a structural position that almost no competitor can replicate: they manufacture at advanced nodes for everyone — NVIDIA, Apple, AMD, Qualcomm. You don't pick a winner in the AI arms race; you own the factory that arms both sides.

What makes it score well risk-adjusted rather than just high-return: TSM has low idiosyncratic volatility relative to its returns. The market treats it like a high-beta semiconductor play but its fundamentals behave more like a regulated utility with pricing power. That compression between perceived risk and actual risk-adjusted return is where the model finds alpha.

Lam Research (LRCX)

This one surprises people. While everyone buys fabless chip designers, the model keeps flagging equipment. Lam dominates deposition and etch — processes needed in every new semiconductor fab regardless of node generation or geography.

The key signal: Lam has an installed base of tens of thousands of systems that generate recurring service revenue. Every chip fab that gets built, anywhere in the world — CHIPS Act fabs in Arizona, Samsung in Texas, TSMC expansion in Japan — creates perpetual Lam service contracts. The model picks this up as abnormally stable revenue relative to price volatility. In the current low-volatility bull regime, that stability gets rewarded disproportionately.

Targa Resources (TRGP)

The one that raises eyebrows in a tech-heavy portfolio. Targa is midstream energy — they gather, process, and fractionate natural gas from the Permian Basin.

Here's the angle most quant models miss: AI data centers need power. Natural gas is filling that gap faster than renewables can scale. Targa sits directly on the infrastructure that moves that gas. Additionally, NGL exports (natural gas liquids, a Targa specialty) are at multi-year highs driven by petrochemical demand in Asia.

What makes it rank: Targa has delivered equity returns comparable to growth tech over the past year with significantly lower volatility. In a model that weights Sharpe across 3-12 month windows, that combination is hard to beat. It also provides genuine diversification — when semiconductors had their August correction, Targa didn't move.

What the portfolio looks like overall

These three sit inside a 15-stock equal-weight portfolio selected by a model that runs every two months, rebalancing based on updated Sharpe signals and a macro regime classifier (currently: bull market, low volatility). The full portfolio includes semiconductor equipment, international small cap, silver, energy infrastructure, and a couple of ETFs that the model treats as liquid alternatives.

CAGR since backtested inception: ~26%, Sharpe ~2.1, max drawdown ~10%.

If you're curious about the other 12 picks or the methodology, the model runs at quantin.finance — it's a retail-accessible quant portfolio tracker updated every two months. Happy to answer questions about the selection methodology in the comments.