Section 1: Mathematical Foundations (30 questions)
The text organizes questions into distinct mathematical and technical domains: 150 Most Frequently Asked Questions On Quant Interviews
| # | Question | Difficulty | Key Idea | |---|----------|------------|-----------| | 101 | What is a martingale? | ★★★ | E[X_n+1 | F_n] = X_n | | 102 | What is Brownian motion? | ★★ | Continuous, Gaussian increments, independent | | 103 | What is a Poisson process? | ★★ | Exponential interarrival times | | 104 | What is a random walk? | ★ | S_n = X_1 + … + X_n | | 105 | What is the difference between AR(1) and MA(1)? | ★★ | AR uses past values, MA uses past errors | | 106 | What is stationarity? | ★ | Mean and variance constant over time | | 107 | What is a unit root? | ★★★ | Non-stationary, e.g., random walk | | 108 | What is the autocorrelation function? | ★ | Correlation with lagged self | | 109 | What is the Wiener process? | ★★ | Another name for Brownian motion | | 110 | What is Itô’s lemma? | ★★★ | Stochastic chain rule | | 111 | What is a stopping time? | ★★ | Decision rule based on info up to now | | 112 | What is the reflection principle for Brownian motion? | ★★★ | P(sup > a) = 2P(B_t > a) | | 113 | What is the Markov property? | ★ | Future independent of past given present | | 114 | What is a Kalman filter? | ★★★ | Recursive Bayesian estimation | | 115 | What is GARCH? | ★★★ | Volatility clustering model | Section 1: Mathematical Foundations (30 questions) The text
Quantitative Trading: How to Build Your Own Algorithmic Trading Business Option volatility and pricing strategies How to compute matrix inverse quickly for structured