Probability & Statistics

Learn Quantitative Problem-Solving

Interview-style quant problems built on the math you already know: which correlation matrices are even possible, geometric probability and conditioning, regression beta from a joint distribution, the linearity/indicator/symmetry reflexes, and portfolio variance with diversification.

Free to start · adaptive placement finds your level · reviews timed to your own forgetting.

What you'll learn

30 lessons in Quantitative Problem-Solving

Which correlation matrices are even possible?Geometric probability & conditioningRegression beta from a joint distributionExpectation: linearity, indicators & symmetryPortfolio variance & diversificationNo-arbitrage & the law of one priceThe one-period binomial (CRR) modelRisk-neutral valuation & the martingaleThe Black–Scholes PDE via delta-hedgingThe Black–Scholes formula & deltaThe Greeks beyond deltaPut-call parityBrownian motion & Itô's lemmaValue at Risk & tail measuresImplied volatility & the smileOptimal stopping & early exerciseMonte Carlo pricingDiscounting & the yield curveForwards, futures & the cost of carryStatic bounds on an option priceThe multi-period tree & backward inductionFeynman-Kac: the PDE is the expectationDelta-hedging in discrete timeEstimating volatility from returnsPayoffs that depend on the pathMerton's structural view of defaultUtility, risk aversion & the certainty equivalentThe mean-variance efficient frontierThe tangency portfolio & the Sharpe ratioCAPM & the security market line
How Erudia teaches

Built to be understood — and remembered.

Every idea is taught with motivation and a worked example before the drills, and an FSRS spaced-repetition engine schedules each review for the day its model predicts you would forget it. A short placement check finds what you already know, so you start Quantitative Problem-Solving exactly where it's useful.

Related Probability & Statistics subjects