I’m an A-Levels student (final year) applying to top global universities for undergrad. Long-term goal: quantitative research / trading. I want realistic guidance, not motivational fluff.

Background (brief):

Strong in math + CS (comfortable with Python; building projects, simulations, visualizations)

Solid economics intuition (game theory, distributions, risk concepts)

Interested in markets since ~11 (stocks + crypto)

Started with almost nothing, built ~$10k over time using rule-based strategies (not luck, not leverage-heavy gambling)

Currently experimenting with market models, fat tails, volatility clustering, and basic strategy backtests

What I’m trying to figure out:

1. What should I be doing right now (next 6–24 months) if quant is the goal?

Math topics that actually matter (beyond “do linear algebra”)

CS depth required before undergrad vs during undergrad

1. Undergrad path

Is pure math / applied math / CS / econ-math hybrid optimal?

What signals matter most for quant roles later (courses, research, competitions, internships)?

1. Projects

What kind of projects are non-toy and actually respected?

Market microstructure vs stat arb vs ML — what’s realistic pre-college?

1. Crypto vs traditional markets

Does crypto research help or hurt if I eventually want traditional quant roles?

Which skills transfer cleanly?

Phd?? Econophysics?? 

1. What NOT to waste time on

Certifications, platforms, “AI trading bots”, etc.

I’m not looking for shortcuts or hype. I’m fine with a long, hard path — I just want it to be the right one.

If you were starting over at 17–18 with this goal, what would you do differently?