A hands-on way into quantitative finance
Learn finance.
Change the inputs.
See it click.
Turn “what if?” into a working model. Explore how markets behave, test your intuition, and build real pricing engines in Python. All in your browser.
Free for students. No installs. No signup to start.
Same stock. More uncertainty.
What changes?
Model values per share, not market quotesTry the full experiment ↗
Bring your whole club. Free seasons for your club, a private board, and a six-week meeting plan.
Bring your club ↗Less abstract. More “what if?”
Your first three experiments.
Predict the result, move one input, and explain what changed. Then write the Python behind it.
The price of uncertainty
Can an option become more valuable without the stock moving?
Predict. Experiment. Explain. →EXPERIMENT 02A clock with a price tag
Watch time value disappear while the stock stands still.
Predict. Experiment. Explain. →EXPERIMENT 03One move, different exposure
Move the stock, then inspect how a call responds.
Predict. Experiment. Explain. →How it works
Train, compete, prove it.
Train
Short lessons, then real Python: fill in the missing function, press Run, and tests tell you whether your model is right. Nothing to install.
Compete in a season
One timed challenge a week with numbers nobody else gets and the AI tutor off. Your code is scored on our server and ranked under a handle.
Prove it
Explain why your code works. Top finishes and capstones are verified in a short live conversation before they count, so the result means something.
The curriculum
Three tracks. Start anywhere.
For clubs and teachers
Bring your club. Play the season together.
Your club gets its own private leaderboard for the season, and a six-week plan if you want structure between challenges: one invite link, a plan for every meeting, and a view of who's keeping up. Free.
Week 1: Markets and risk
Price a share, read a bid-ask spread, and measure why two stocks are safer than one.
Week 2: Options and payoffs
Sketch call and put payoffs and spot a mispriced option with put-call parity.
Week 3: Pricing
Implement Black-Scholes in Python until it matches the reference price.
Week 4: Risk sensitivities
Compute the Greeks and explain one to the group with a real-world analogy.
Week 5: Research discipline
Backtest a strategy and find where look-ahead or survivorship bias could fool you.
Week 6: Portfolio capstone
Submit and present a capstone: a question, code that answers it, and an honest result.
The Greeks
Five numbers that run the trade
An option's price depends on the stock, the strike, time, volatility and interest rates. The Greeks measure how the price reacts to each one, and you'll code every one of them.
- Delta
- +0.224change in price per $1 move in the stock
- Gamma
- +0.052how fast Delta itself changes
- Theta
- −0.031value lost each day that passes
- Vega
- +0.086per 1 point of volatility
- Rho
- +0.018per 1 point of interest rates
Black-Scholes with 20% volatility and a 4.5% rate. Computed, not made up.
What you build
Work you can show, not a quiz score
A capstone is a real question, code that answers it, and an honest result: the kind of project a student can show a teacher or put in an application. These two examples were written by the StrikeLab team to show the bar.
Why it's different
Build the model instead of playing the market
| Question | Stock games and finance-literacy courses | StrikeLab |
|---|---|---|
| What students do | Pick stocks in a simulator or read about finance | Write the models themselves: pricing, risk, backtests |
| What they finish with | A leaderboard rank or a quiz score | A capstone: a question, working code and an honest result |
| What the leader gets | A class list | A weekly plan, ready-to-send messages and a scorecard |
Private by default
Safe for students and schools
- Built for ages 13–18. No ads, and we never sell data.
- No public profiles. Leaderboards show a handle the student picks, never a real name.
- Student work is private to the student (and their leader, in a club) unless they share it.
- Students can delete their account and everything in it at any time.
Why this exists
More about StrikeLabI qualified for AIME in 8th grade and went looking for what came next. High-school finance stopped at “pick a stock”; the real math was behind doors I couldn't walk through. So I built the lab I wanted, and made it free for students. Quant finance shouldn't require the right zip code.
Questions
Do I need to know finance or coding?
No. Lesson 1 starts at what a stock is. Python comes in gradually, with the hard parts already written, and it runs in your browser.
What is a season?
Season 1 runs Nov 30 to Dec 20. One challenge opens each week; when you start it, a timer starts and the AI tutor switches off until you submit. Your numbers are yours alone, your code is scored on our server, and the leaderboard shows a handle, never your name.
What does it cost?
Students never pay: every lesson, the playground and every season are free, and clubs play free. The one paid option is the January Intensive for parents, and nothing is charged until a cohort fills.
Do I need an account?
Not to start. Progress saves on this device; a free account syncs it across devices and keeps your code.
I lead a club. How much prep is it?
Light. Each week comes with a goal, discussion prompts, common sticking points and a message to send, and the lessons do the teaching. Read the week's plan before you meet. We're timing the real prep in the first pilots and will tell you the number.
Is it safe for students?
It's built for ages 13–18: no ads, no public profiles, leaderboards show a handle and never a real name, work is private unless the student shares it, and accounts can be deleted at any time.
Start tonight. It's free.
Train one short lesson at a time, then prove it in Season 1, starting Nov 30.
Leading a club and want to talk it through first? Book 15 minutes with the founder.