Why Markowitz weights explode
Expected return and portfolio variance by hand, then in code; see how ρ → 1 and tiny estimate errors create extreme long/short weights.
The first Critical Quant labs are coming soon
Learn quant models through their failures.
Build Markowitz, Black–Scholes, and regression in small Python steps, then break one assumption to see what the model misses and why its output can fail.
Picture and hand calculation first. Then short, runnable Python — one formula at a time — so weights, greeks, and betas are not magic symbols.
The Critical Quant method
Model failure is not a bonus module. It is where understanding clicks.
Textbook formulas look safe until their assumptions stay invisible. Each lab moves from intuition to a checkable calculation, then to small Python that mirrors the formula — and finally to the single assumption that makes the output lie.
01
See what the formula means
Story, diagram, and tiny numbers. Every symbol is named before you type code.
02
Build it in small Python steps
Run one line at a time — covariance, inversion, weights — so you watch the math happen, not memorize it.
03
Break one assumption
ρ → 1, discrete hedging, or a collider selection. Weights explode, signs flip, or labels change — immediately.
Finish with contrast, limits of the setup, and a transfer question without code — so you own the trap, not the syntax.
Launch labs
Learn the model by finding its breaking point.
Not a generic “learn Python” course. Each lab makes a quant model intuitive, builds it step by step, and reveals the assumption that makes its output fail.
Core model
Where Black–Scholes stops working
Payoff, d₁/d₂, and put–call parity built stepwise; then continuous hedging, constant vol, jumps, and costs as visible limits.
Why regression signs flip
OLS in small Python steps, control the confounder, then see collider selection invent a relationship.
Why profitable bets can still make you go bust
Positive expected value is not enough: use multiplicative wealth, drawdowns, and Kelly sizing to see why overbetting can destroy a genuine edge.
Coming soon
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