How do I prepare for a quant interview?

Three muscle groups: probability/brainteasers at speed, stochastic calculus and derivatives pricing on paper, and statistics/ML fundamentals. KomFi gives you 2,000 quant practice questions with full derivations — the daily rep structure interviews reward.

How do I learn quantitative finance?

Mathematics first (probability, linear algebra, calculus), then the finance layer (pricing, hedging, risk), then computation. Worked problems beat passive reading at every stage — every question here carries its full derivation.

What math do I need for quantitative finance?

Probability theory and stochastic processes, linear algebra, multivariable calculus, and statistics through regression and time series. The bank drills each at interview depth, including Itô calculus and martingale arguments.

Free sample questions

1. If the underlying stock price S moves by +$2.00 over a very short interval, what is the estimated second-order
2. What is the estimated OLS slope hatβ?
3. If the flat yield curve is at 4% (continuously compounded), what is the bond's price?
4. As the number of assets n approaches infinity, what happens to the total portfolio variance?
5. What is the fair no-arbitrage price for a six-month (T = 0.5) forward contract?
6. If the risk-neutral probability of an up move is p = 0.6 and the risk-free rate is zero, what is the price of
7. When pricing a 'Digital' (or Binary) call option near expiry with the spot price very close to the strike, why
8. Calculate the price of a zero-coupon bond that pays $1000 in two years, given that the one-year discount facto
9. If today's conditional volatility is 2.09%, what is the forecasted daily volatility five days from now (k=5)?
10. Assuming 252 trading days in a year, what is the annualized historical volatility?
11. If the risk-neutral probability of an up move is p = 0.6, what is the expected stock price at the end of two s
12. According to the Merton portfolio problem, what is the optimal fraction π^* of wealth to hold in the risky ass
13. If the correlation between two assets is ρ = 0.6, what is the R^2 of a linear regression of one asset's return
14. Under Girsanov's Theorem, what does a change of probability measure primarily alter in a stochastic process dr
15. In the context of the HJM framework, what is the primary lesson regarding the drift of the forward rate curve?
16. If the slope β is positive, what is the correlation coefficient ρ between x and y?
17. In the context of the Black-Scholes PDE, the Greek 'Theta' (Theta) measures the sensitivity of the option pric
18. What is the defining property of the 'Cumulative Distribution Function' F(x)?
19. Which 'standardized moment' should they measure to quantify this?
20. A portfolio has a daily expected return of 0.05% and a daily volatility of 1.2%. Using the parametric method a
21. If yesterday's return was 2% and the conditional variance was 0.0001, what is the updated conditional volatili
22. If the investor's coefficient of relative risk aversion is γ = 4, what is the Merton optimal fraction (π^*) to
23. When calibrating a Heston stochastic volatility model, a pra… — Does this calibration satisfy the Feller condi
24. Two assets are 'cointegrated'. What does this imply for a pairs-trading strategy that 'correlation' alone does
25. In the Vasicek short-rate model dr_t = κ(θ - r_t) dt + σ dW_t, what happens to the drift when the current rate
26. Based on put-call parity, what is the arbitrage-free relationship?
27. For a standard Brownian motion W_t, what is the expected value of W_t^2?
28. A bond's price P is a function of its yield y. If the second derivative P''(y) is positive, how does the durat
29. To solve for the implied volatility of an option when the market price is known, which numerical method is mos
30. What is the probability the stock outperforms given the signal fired?