From Black-Scholes to Machine Learning — the models that move markets, explained from the intuition up, without getting lost in the formalism.
§ What you'll understand
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§1 Inside the guide
01
The fair price of an option. The equation that opened the derivatives era.
02
When there is no closed formula, you simulate thousands of futures and average them.
03
How to split capital to maximise return for the risk you are willing to take.
04
Statistical arbitrage: betting that two assets return to their equilibrium.
05
Pulling the clean signal out from under the market's noise.
06
Why volatility arrives in bursts, and how to model it.
07
Where ML genuinely helps in predicting markets — and where it is only sophisticated noise.
§2 Who's writing
I hold a degree in Physics from USC and a Master's in Nuclear and Particle Physics. I spent years among Feynman propagators, stochastic processes and simulations.
Today I apply that same rigour to markets: from the formalism of physics to pricing and risk management. In Quantum Club I translate all of it into something you can actually understand and build, wherever you are starting from.