Resources

Curated books, papers, and guides for quant researcher preparation.

📚 Essential Reading

Probability & Statistics

A First Course in Probability — Sheldon Ross
All of Statistics — Larry Wasserman
Introduction to Probability Models — Sheldon Ross
Probability and Statistics for Engineering and the Sciences — Jay Devore

Stochastic Calculus & Financial Math

Stochastic Calculus for Finance I & II — Steven Shreve
Options, Futures, and Other Derivatives — John Hull
Paul Wilmott on Quantitative Finance — Paul Wilmott
Concepts and Practice of Mathematical Finance — Mark Joshi

Linear Algebra & Optimization

Introduction to Linear Algebra — Gilbert Strang
Convex Optimization — Stephen Boyd & Lieven Vandenberghe
Matrix Analysis and Applied Linear Algebra — Carl D. Meyer

Interview Preparation

A Practical Guide to Quantitative Finance Interviews — Xinfeng Zhou (the "Green Book")
Heard on The Street — Timothy Crack
Quant Job Interview Questions and Answers — Mark Joshi
Fifty Challenging Problems in Probability — Frederick Mosteller

Programming & Data Science

Python for Data Analysis — Wes McKinney
Hands-On Machine Learning — Aurelien Geron
Elements of Statistical Learning — Hastie, Tibshirani, Friedman

📋 Quick Reference Formulas

Key Formulas to Know

Black-Scholes: $C = S_0 N(d_1) - Ke^{-rT}N(d_2)$ where $d_1 = \frac{\ln(S/K) + (r + \sigma^2/2)T}{\sigma\sqrt{T}}$

Put-Call Parity: $C - P = S_0 - Ke^{-rT}$

Ito's Lemma: $df = f'(S)dS + \frac{1}{2}f''(S)(dS)^2$

VaR: $\text{VaR}_\alpha = \mu + z_\alpha \sigma$ (parametric, normal)

Portfolio Variance: $\sigma_P^2 = \mathbf{w}^T \Sigma \mathbf{w}$

Bayes' Theorem: $P(A|B) = \frac{P(B|A)P(A)}{P(B)}$

OLS Estimator: $\hat{\beta} = (X^TX)^{-1}X^TY$

Duration: $D = -\frac{1}{P}\frac{dP}{dy}$, price change $\approx -D \cdot \Delta y \cdot P$

💡 Interview Tips

General Approach

1. Think out loud — Interviewers want to see your thought process, not just the answer.

2. Start simple — Solve a simpler version first, then generalize.

3. Check edge cases — Does your answer make sense for extreme values?

4. Know your distributions — Be fluent with Normal, Poisson, Exponential, Geometric.

5. Practice mental math — Quick estimation is valued highly.

Common Question Types

Probability Expected value, conditional probability, counting, Markov chains

Statistics Estimation, hypothesis testing, regression, Bayesian reasoning

Finance Options pricing, Greeks, risk measures, portfolio theory

Brain Teasers Logic puzzles, Fermi estimation, game theory