Find, test and defend an edge.
Inference, time series, cross-validation, portfolio construction, model risk and research lineage.
CH01 · CH02 · CH08 · CH09 · CH12 · CH14
Quantitative finance interview preparation
Quant interview questions that go beyond the whiteboard.
Quant Interviews is a two-volume guide for candidates who need to reason through mathematics, markets, research and the production systems behind real investment work. It contains 194 questions with derivations, implementation choices, failure modes and reproducible code.
Volume I
Volume II
Two volumes · Mathematics & Markets
Research & Systems
A technical book for the interview, the take-home and the job after both.
Many quant interview resources stop at a short answer or a puzzle. This book treats an interview question as evidence of how someone thinks: define the assumptions, derive the result, identify what breaks, implement it, test it and explain the production consequence. That makes it useful for interview preparation and as a reference once the interview is over.
1,630pages
194auditable questions
14chapters in two volumes
58,459lines of public companion code
What a quant researcher, trader, developer or PM is actually expected to connect.
Price risk and act under uncertainty.
Probability, derivatives, volatility, rates, market microstructure, execution and decision-making.
CH01 · CH05 · CH06 · CH07 · CH10 · CH13Turn a model into reliable software.
Numerical methods, data structures, C++, Python, SQL, reproducible backtests, APIs and deterministic replay.
CH02 · CH03 · CH10 · CH11 · CH12 · CH14Allocate capital with controls.
Evidence quality, risk aggregation, capacity, attribution, stress testing, governance and production controls.
CH01 · CH07 · CH09 · CH10 · CH12 · CH14A useful answer is more than the final formula.
Each question is designed to make the reasoning inspectable. The companion repository contains public Python, C++20 and SQLite examples that mirror the chapter structure, so a reader can inspect a result rather than accepting it on authority.
Prompt
The actual interview or desk scenario, stated precisely enough to expose hidden assumptions.
Derivation
A clear route from assumptions to answer, including units, edge cases and conditions for validity.
Implementation
Python, C++ or SQL where code makes the reasoning testable and operationally meaningful.
Failure modes
Leakage, instability, numerical error, market impact, stale data and the controls that make them visible.
Quant interview questions across fourteen connected chapters.
These are not isolated keywords. The chapters build from probability and numerical reasoning into pricing, research, portfolio construction, execution and investment-system design. Each card below names representative questions drawn from the public implementation tree.
Find the topic you are preparing for
- Probability and statistics interview questions
- Linear algebra and optimization interview questions
- Numerical methods and PDE interview questions
- Stochastic calculus interview questions
- Options and derivatives interview questions
- Volatility trading interview questions
- Fixed income and credit interview questions
- Time series and ML interview questions
- Portfolio management interview questions
- Market microstructure interview questions
- Quant developer C++, Python and SQL questions
- Backtesting and trading-system design questions
- Quantitative finance brainteasers
- Mock quant interviews
Probability and statistical inference
Base rates, dependence, Sharpe uncertainty, block bootstrap, false discoveries, optional stopping, Bayesian updates and expected utility.
- Bayesian trading edge
- Backtest selection bias
- Robust estimation
Linear algebra and optimization
Covariance matrices, factor models, Cholesky simulation, shrinkage, constrained Markowitz, risk parity and sparse portfolio design.
- PCA risk decomposition
- Woodbury identity
- Turnover constraints
Calculus, PDEs and numerical methods
Root finding, implied volatility, quadrature, Monte Carlo, finite differences, automatic differentiation, calibration and adjoint sensitivities.
- Newton-Raphson failure
- Crank-Nicolson stability
- Barrier-option PDE
Stochastic processes and stochastic calculus
Filtrations, Ito integrals, Brownian motion, martingales, GBM, Ornstein-Uhlenbeck processes, Girsanov and Feynman-Kac.
- Euler-Maruyama error
- Change of measure
- Correlated diffusions
No-arbitrage and derivatives
State prices, put-call parity, option-surface arbitrage, binomial exercise, Black-Scholes, barrier options, local volatility and exotic bounds.
- Static arbitrage audit
- American exercise
- Quanto drift
Volatility, Greeks and options trading
Greek sign checks, delta-hedged P&L, smile dynamics, skew, variance swaps, Heston, SABR and discrete hedging with jumps.
- Vanna and volga
- Volatility surface
- Variance replication
Fixed income, rates and credit
Curve bootstrapping, duration, DV01, multi-curve discounting, Hull-White, HJM, hazard rates, CDS and bond P&L explain.
- Discount curve bootstrap
- Key-rate hedging
- Credit survival
Time series, econometrics and machine learning
Stationarity, ACF/PACF, cointegration, Kalman filters, regime switching, GARCH, purging, embargoes, calibration and live drift.
- Time-series validation
- Label leakage
- Economic alpha
Portfolio construction, risk and performance
Mean-variance, Black-Litterman, risk parity, factor neutrality, transaction costs, expected shortfall, capacity, attribution and rebalancing.
- Robust optimization
- Tail risk
- Systematic attribution
Market microstructure and execution
Order books, queues, adverse selection, market impact, Almgren-Chriss, TCA, smart routing, icebergs, Hawkes processes and market making.
- Fill probability
- Execution benchmarks
- Production execution
Programming, Python, C++ and SQL
Complexity and locality, streaming algorithms, caches, dependency DAGs, C++ concurrency, floating point, NumPy, bitemporal SQL and numerical tests.
- False sharing
- Point-in-time SQL
- Stable APIs
Data, backtesting and production systems
Instrument master, as-of data, corporate actions, event-driven backtesting, portfolio accounting, lineage, event sourcing, OMS and pre-trade risk.
- Deterministic replay
- Research lineage
- Operational controls
Brainteasers, estimation and game theory
Fermi estimates, biased coins, the secretary problem, optimal search, auctions, gambler's ruin, matrix invariants and coordination games.
- Trading-notional estimate
- Selection traps
- Strategic decisions
Mock interviews and role tracks
Role-specific mock interviews for researchers, traders, desk quants, developers, PMs, risk and ML candidates, plus take-homes and calibration.
- Research case
- Platform design
- Scoring rubric
Why production systems belong in a quant interview book.
Investment teams do not only need a formula or a model. They need a way to know which data it used, whether it could have been known at the time, what changed after a vendor correction, how an order was approved and whether a result can be reproduced under pressure.
That is why the book connects probability, pricing and research with point-in-time data, instrument identity, execution, accounting, monitoring and audit evidence. It is the bridge from a strong technical answer to a credible production answer.
Questions candidates often ask before starting.
Is this only for quant researchers?
No. The role tracks deliberately span quant research, trading, development, systematic PM, risk and platform design. Chapter 14 turns the shared material into role-specific mock interviews.
How technical is the book?
It begins with core probability and linear algebra, then reaches stochastic calculus, derivatives, econometrics, market microstructure, C++, SQL, backtesting and systems design. It is intended as a serious technical reference, not a list of memorized answers.
Can I inspect the implementation?
Yes. The public companion repository contains the chapter-organized Python, C++20 and SQLite examples plus public code-only tests. The book and code have distinct licenses and scopes, explained on the license page.
Is the PDF a shortened sample?
No. The digital edition is the complete two-volume book: all fourteen chapters and all 194 questions. The printed set is for readers who prefer a physical reference.
Start with the complete book.
Request both PDF volumes free, then use the topic map above to plan the parts that match your target role. The code companion is available publicly for readers who want to inspect the implementations.