The best quant interview books by role (and the free guides firms publish)

Which quant interview book should you buy? It depends on the role, and on what the firms themselves tell you to read: some of them do, in writing, for free. This guide gives a short answer first, then compares the four standard books by topic and role, sets them against the official prep material Jane Street and G-Research publish, and covers the part of the interview that reading cannot train. Every claim is labeled as official (firm, author or publisher material), third-party (library, university and bookseller records) or self-reported (forums), with a date.

Last reviewed 2026-10-24. Editions and firm guidance change; check the publisher's current edition before you buy, and the firm's careers pages before you interview.

The short answer

These are our picks, based on each book's contents and the firm material below. No firm or author makes these role assignments, and every firm's process differs.

• Quant trading: Xinfeng Zhou's A Practical Guide to Quantitative Finance Interviews (the "green book") for probability and brain teasers, then Crack's Heard on the Street. Pair either with your target firm's own guide: Jane Street's covers probability, expected value and making markets.
• Quant research: Stefanica, Radoičić and Wang's 150 Most Frequently Asked Questions on Quant Interviews, the one standard interview book G-Research recommends by name, plus Zhou's probability chapters. For ML-heavy research roles, statistics and ML texts matter more than any interview book.
• Quant development: books are secondary. In the firm pages and candidate reports we collected, coding rounds and language depth carry most of the weight; Joshi's C++ and numerical chapters help, and our quant developer prep page lists the skills to practice.
• Bank and derivatives quants: Joshi, Denson and Downes for option pricing, and Crack for derivatives and financial economics.

Before buying anything, read what your target firm publishes for free (covered below).

The four standard books at a glance

Zhou. The library record for the 2008 CreateSpace edition lists chapters on general principles, brain teasers, calculus and linear algebra, probability theory, stochastic processes and stochastic calculus, finance (option pricing, the Greeks, exotic options) and algorithms and numerical methods. (Third-party: Open Library catalog record, 2008 edition, accessed October 2026.) The nickname is forum shorthand: asked in a 2022 Blind thread what "the green book" is, a commenter answered "Practical guide to quantitative finance interviews." (Self-reported, 2022.)

Crack. The book is revised often. Cornell's career office described it in May 2026 as "Currently in its 24th edition" (Third-party: Cornell Career Development, May 2026), and library records list editions published in 2023 and 2025. (Third-party: Open Library records for the 2023 and 2025 editions, accessed October 2026.) The figures that follow come from the revised 23rd edition, published in August 2022. It contains 242 quantitative questions "collected from actual job interviews in investment banking, investment management, and options trading", plus 264 non-quantitative ones. Questions likely to come up in corporate finance or investment banking interviews carry a bank symbol in the margin, and the option-pricing appendix of early editions became a separate book, Basic Black-Scholes. (Third-party: bookseller listing, 23rd edition, August 2022.) Counts can change between editions, so read the current edition's description before you buy.

Joshi, Denson and Downes. The second edition was published by Pilot Whale Press in Melbourne in 2013 and runs to 375 pages. (Third-party: KIT library catalog, 2013 edition, accessed October 2026.) Its description promises over 300 questions "taken from actual interviews in the City and Wall Street", each with a full solution, a note on what the interviewer is looking for and possible follow-ups, covering "option pricing, probability, mathematics, numerical algorithms and C++" and the non-technical interview. (Third-party: bookseller listing, 2013 edition.)

Stefanica, Radoičić and Wang. The publisher's page lists a 265-page softcover covering calculus and differential equations, covariance matrices and linear algebra, options, bonds, swaps, forwards and futures, C++ with algorithms and data structures, Monte Carlo and numerical methods, probability and stochastic calculus, and brainteasers. The authors teach in the Baruch College financial engineering master's program, and the page offers a free 15-question sample with solutions. (Official: Financial Engineering Press, accessed October 2026.) G-Research's reading list cites a 2013 FE Press printing; the publisher now sells a second edition.

Which book for which role

A book covers one part of the preparation. The table lists the skills each role is tested on beyond the book, and where to practice them. As above, this is our reading and describes no single firm's process.

Two caveats. For trading roles at firms that say they do not test advanced math, a book's stochastic calculus chapters are low priority, and Jane Street's own page says as much about higher-level college math. For quant developer roles, one forum account suggests the coding round dominates: a 2023 Blind commenter described the quant developer interview as "just regular SWE with leetcode maybe more focused on mathy or DP problems." (Self-reported, 2023.)

Not sure what to practice first? The problem bank groups practice questions by topic. Preparing for a specific firm? The firm guides collect each firm's published process and practice.

What the firms publish for free

Official material is free, comes directly from the firm, and is a useful starting point for understanding what it values in candidates. It describes the topics; the interviews themselves can go deeper.

Jane Street. The firm publishes a 13-page Probability & Markets guide for its quantitative trading and research interviews. Its contents run from randomness, counting and independence through random variables, expected value, confidence intervals and conditional probability, to making markets, adverse selection and problem-solving tools such as recursion and edge cases. The firm calls it an introduction to "the basic concepts we ask about" and adds: "This isn't required reading by any means." (Official: Jane Street, accessed October 2026.)

The guide itself closes with a section on interview myths that matters for how you study. On mental math, it says numeracy helps, but "we're not going to judge you harshly for not being able to mentally multiply double-digit numbers in 5 seconds." On advanced math, it says the firm tries "to ask creative problems that you can reason through with minimal outside knowledge" and often prefers "the simple, intuitive answer to the one that involves a bunch of esoteric theorems." (Official: Jane Street Probability & Markets guide, accessed October 2026.)

Its trading interviews page describes phone interviews followed by in-person final rounds that may include problem solving, probability and statistics, coding in any language, data analysis and general interests, and says the interviews won't require previous knowledge of finance or "any complicated math, such as what you might learn in a higher-level math course in college." The same page hosts a recorded mock trading interview of about 23 minutes, built around a three-part sample question. (Official: Jane Street, accessed October 2026.) For software engineers there is a separate mock interview page with this advice: "start a timer, talk through your ideas out loud, write out all parts of the problem." It points to LeetCode and HackerRank for algorithmic practice while noting those questions "aren't exactly what you'll answer in a Jane Street interview." (Official: Jane Street, accessed October 2026.) Our Jane Street interview guide and Jane Street firm page go through the process in more detail.

G-Research, current guidance. G-Research is unusually specific about books. Its quantitative researcher interview guide says candidates take one of two online quizzes, a general quantitative one or an ML-specific one, typically followed by four one-hour technical interviews, or two for candidates on the ML route. For preparation it says to "Start with 150 Most Frequently Asked Questions on Quant Interviews", which it calls "a classic for building range and confidence, focusing on numerical methods and problem-solving at the level of our triage interview." For the ML quiz it adds Cracking the Coding Interview and The Elements of Statistical Learning. For coding practice it suggests Project Euler, then Codility, Kaggle and TopCoder, and it links to a community reading list on Quant Stack Exchange. (Official: G-Research, accessed October 2026.)

The recommended-reading PDF that page links to describes the process as an online quiz, then a triage stage, then further technical interviews. It recommends the Stefanica book for its typical quiz, says the book "emphasises numerical methods more and statistics less", and that its "more advanced questions are closer to the level of our triage interview questions than of our quiz questions." It states "We do not assume a detailed knowledge of finance" and names Rishi Narang's Inside the Black Box as a casual introduction if you want one source. It suggests searching for "programming brain teasers" before the programming interview, and lists Emanuel Derman's My Life as a Quant and Jack Schwager's Hedge Fund Market Wizards as background reading. (Official: G-Research, accessed October 2026.)

G-Research, earlier guidance. An earlier version of the same list explained what the triage interview was for at the time: it identified the technical interviews you would take, one of them in maths and two "drawn from Stats, Finance, Programming, and ML." (Official: G-Research, July 2025.) That breakdown describes the process as of 2025. Older still, G-Research has a Sample Quant Exam (copyright 2017) with eleven questions that it says represent its written quant exam, questions it has asked at interview, or ones it thinks are fun: regression slopes, conditional probability, a stock's move given its beta, breaking a stick into three pieces, the delta of a binary option near expiry, domino tilings and a gambler's ruin variant. (Official: G-Research, 2017.) It is a historical example and may not match the current quiz, but it is free and makes a good timed self-test.

Two things stand out. Both firms say they do not expect detailed finance knowledge, although finance was listed among G-Research's possible technical interview topics in 2025. And of the four standard books, the only one either firm recommends by name is the Stefanica title, suggested for G-Research's typical quiz and pitched up to the level of its triage interview. That recommendation covers these two firms only.

If you want to see the whole reading landscape, the Quant Stack Exchange community answer that G-Research links to has an "Interviews" shelf listing Joshi, Crack, Stefanica and Dirk Bester's An Interview Primer for Quantitative Finance, among a much longer list of textbooks. (Third-party: community wiki, last edited February 2022.) One free extra: the authors of The Elements of Statistical Learning offer the book as a free PDF on their site. (Official: authors' site, accessed October 2026.)

What books cannot train

Books like these pair questions with worked solutions (the Crack and Joshi descriptions say so explicitly). That is good for learning methods. Three skills the interviews and screens also test need a different kind of practice.

Speed under a clock. Some screening tests are timed arithmetic. A 2020 Blind poster described Optiver's mental math test as "8 mins 80 questions." (Self-reported, 2020.) How much speed matters varies by firm: Jane Street's guide says it will not judge you harshly for slow double-digit multiplication. Where a timed screen exists, reading solutions can improve your technique, but performing consistently under time pressure takes timed practice. Our speed math drills include an 80-in-8 style preset and sequence drills, and our Optiver online assessment guide collects what candidates report about that screen.

Producing an answer cold. A worked solution read after a few minutes of thought feels like understanding. Answering the same type of question a week later, without the book, is the real test. Working through a problem bank without peeking, and returning to the topics you miss through lessons by topic, turns recognition into recall. Three free problems in the style of these books, to try before you buy anything:

• Probability: 3 Consecutive Heads II, a run-counting question close to the coin-flip exercises in Jane Street's guide.
• Brain teaser: The Counterfeit Coin, eight coins and two weighings on a balance.
• Mental math: Square Root Estimation, the square root of 300 without a calculator.

Thinking out loud. Jane Street's trading interviews page lists four short tips: "Approach the problem methodically. Communicate clearly. Correct your mistakes. Ask why." Its software engineering mock-interview page adds that practice should be "as much like a real interview as you can", with a timer and your ideas spoken aloud. G-Research says the best candidates "revise, simulate mock interviews and learn to think out loud." (Official: Jane Street and G-Research, accessed October 2026.) Books cannot reproduce the pressure and unpredictability of a live interview. Practicing with a peer or mentor who presses on each step helps you put your reasoning into words and handle follow-up questions. A timed mock interview helps you rehearse the structure, pacing and pressure of a firm's rounds.

A practical order

1. Read the official guide for each firm you are applying to, and note what it says it does not test.
2. Pick one book that matches your role from the tables above and work it with the solutions covered.
3. If any target firm screens with a timed test, drill that format separately and early.
4. Rehearse out loud, ideally with a timer and someone asking follow-ups.

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