I built a stock portfolio optimizer where risk controls structure, not stock selection

I’ve been working on a side project called StockRisker — a stock portfolio optimizer built around a simple idea:

Risk shouldn’t just mean “riskier stocks”.

It should control how concentrated and asymmetric a portfolio is allowed to be.

Most tools I tried treat risk as a label:

Low risk → safe stocks

High risk → risky stocks

In reality, risk tolerance usually affects:

• how concentrated you’re willing to be

• how much sector exposure you allow

• how strict diversification constraints are

So in StockRisker, risk directly controls:

• max allocation per stock

• sector caps

• penalty strength for concentration

Higher risk doesn’t mean “more dangerous stocks” — it means fewer constraints and more asymmetric portfolios.

This is not an AI picker and not a “beat the market” tool.

It’s more of a constraint-based optimization experiment focused on transparency and tradeoffs.

Built with:

• TypeScript / Node.js

• a modular optimizer (risk mapping → constraints → scoring)

• curated stock universes

I’d love feedback from anyone who’s built:

• optimization engines

• fintech tools

• decision systems with explainability concerns

Live here if you’re curious:

https://stockrisker.com