JPMorgan Chase Interview Questions
95 quant questions from JPMorgan strats/QR loops: options pricing and derivatives, stochastic calculus, regression and time-series, probability, and brain-teasers.
Inside the JPMorgan Chase interview
JPMorgan Chase runs one of the largest sell-side quant franchises, and its Quant Researcher and Quant Strategist loops lean into derivatives pricing and the stochastic calculus beneath it, backed by a heavy dose of statistics, regression, and time-series modeling. Expect to derive, not just recall.
What they test
The single largest block is options pricing and derivatives — Black-Scholes assumptions, put-call parity and arbitrage, Greeks and delta-hedging, Breeden-Litzenberger replication, and risk-neutral martingale arguments — sitting on a stochastic-process core (Brownian motion, first-passage and hitting times, Feynman-Kac). Around it sits a deep econometrics wing: regression (OLS derivation, ridge/LASSO, endogeneity and IV, diagnostics) and time-series (ARMA stationarity, cointegration, GARCH, realized volatility). A steady stream of probability, expectation, and brain-teasers opens most interviews.
The recurring shapes
Several patterns repeat. Risk-neutral pricing: show the discounted stock is a martingale, then price by expectation. Hedging and replication: build a portfolio that cancels a Greek or statically replicates a payoff. Estimator reasoning: state an estimator (OLS, MLE, a Bayesian posterior), prove a property, then stress it under endogeneity, multicollinearity, or heavy tails. Expected-time setups recur in the warm-up — expected tosses for a run, hitting times, first passage.
How to approach
Lead with assumptions: name the measure, the model, and what you are conditioning on before you compute. For derivatives, anchor on no-arbitrage and put-call parity as sanity checks; for econometrics, say out loud which OLS assumption could break and how you would detect it. On the brain-teasers, set up the recursion or symmetry argument cleanly rather than reaching for brute force — interviewers grade the derivation, not just the number.
The mix leans medium (48) with a substantial hard tail (32 derivations-heavy pricing and econometrics problems) and 15 easy warm-ups.
Reported from a real JPM QR interview (August 2026)
A candidate interviewing for a fixed income desk strat seat (Quantitative Research & Trading) shared their round with us right after sitting it. The questions, with worked answers:
- Find the coefficient of x⁹ in (2x + 3)¹³. By the binomial theorem the x⁹ term is C(13,9)·(2x)⁹·3⁴ = C(13,4)·2⁹·3⁴·x⁹, so the coefficient is 715 · 512 · 81 = 29,652,480.
- Closed form of 1 + x² + x³ + … + xⁿ. Careful: the x¹ term is missing. Take the full geometric series (1 − xⁿ⁺¹)/(1 − x) and subtract the missing x: (1 − xⁿ⁺¹)/(1 − x) − x for x ≠ 1 (and n + 1 − 1 = n terms… sanity check with n = 3: 1 + x² + x³). The derivation they wanted is the standard telescoping: S − xS collapses the sum.
- Fair coin flipped 15 times: P(exactly 7 heads). C(15,7)/2¹⁵ = 6435/32768 ≈ 0.196.
- $100 bond, duration 5, yields move 1 bp. ΔP ≈ −D · Δy · P = −5 · 0.0001 · 100 = −$0.05 — five cents, or 0.05%.
- 10 million sorted numbers: count how many fall between two values. Two binary searches: index of the first element ≥ lower bound and the first > upper bound; the difference is the count. O(log n), no scan.
Pattern check: quick combinatorics, a series identity with a trap, exact binomial probability, duration mechanics, and one algorithmic question — consistent with other recent JPM QR reports. Drill the matching sets: Combinatorics, Probability, and the finance list for duration and convexity.
JPMorgan Chase options pricing questions (22)
- Volatility Smile and Model Risk
- CVA with Exposure Profile and Wrong-Way Risk
- Crank-Nicolson Scheme for the Black-Scholes PDE
- Counterparty Credit Risk and CVA
- Binomial Tree Option Pricer
- Breeden-Litzenberger Formula
- Merton Structural Credit Model
- American Option Early Exercise Analysis
- Static Replication via the Breeden-Litzenberger Integral
- Delta-Normal VaR with Correlation
- Local Volatility vs Stochastic Volatility
- Feynman-Kac and Option Price Convexity
- American Put Pricing via Projected SOR
- Put-Call Parity and Arbitrage Construction
- Discounted Stock as Martingale Under Risk-Neutral Measure
- Discrete Delta-Hedging Error
- Forward Measure and Caplet Pricing
- Delta-Gamma-Vega Hedging With Two Options
- Bond Duration, Convexity, and Futures Hedging
- Black-Scholes Assumptions and the American Call Delta
- Numerical / Monte Carlo Greek Estimation
- Implied Volatility via Newton-Bisection
JPMorgan Chase regression questions (11)
- R-Squared, Adjusted R-Squared, and the F-Test for Linear Restrictions
- Robust Regression with Heavy-Tailed Noise
- OLS Estimator Derivation and t-Test
- WLS Weights When Observations Are Averages
- LASSO for Return Prediction with Time-Series Validation
- Logistic Regression: Log-Likelihood, Gradient, and Threshold Selection
- HAC vs Two-Way Clustered Standard Errors
- Regression Diagnostics: Outliers, Influence, and Multicollinearity
- Multicollinearity and the Variance Inflation Factor
- Ridge vs. Lasso Regression: Theory and Practice
- OLS Unbiasedness, Endogeneity, and Instrumental Variables
JPMorgan Chase expected value questions (9)
- Expected Hitting Time of a Geometric Brownian Motion
- Covariance of Sums of Independent Brownian Motions
- Expected Waiting Time for Three Consecutive Heads
- Expected Radial Distance on a Circular Disk
- Conditional Expectation of a Linear Combination Given a Sum
- Second Moment of a Gaussian Random Variable
- Expected Rolls for a Consecutive 4-5 Sequence
- Pool Filling Rate with Two Hoses and an Open Drain
- Expected Hitting Time to a Linear Boundary
JPMorgan Chase statistics questions (9)
- MLE, Confidence Interval, and Bayesian Posterior for a Coin
- Missing Data in Regression: MCAR, MAR, and MNAR
- HMM-Based Conditional Coverage Backtest for VaR
- Optimal Predictors Under Squared and Absolute Loss
- Type I and Type II Error Trade-off in a Gaussian Z-Test
- Blocked Randomization for Causal Inference
- Classification Calibration and Platt Scaling
- Proper Scoring Rules and Time-Series Forecast Evaluation
- Reduction Formula for the Wallis Sine Integral
JPMorgan Chase time series questions (8)
- Engle-Granger Cointegration Trading Signal
- Identifying and Fitting an MA(q) Model from ACF and PACF Patterns
- GARCH Parameters and Estimation
- Random Walk: Moments, Differencing, and Spurious Regression
- Johansen Cointegration Test and Walk-Forward Spread Validation
- ARMA Process Stationarity, Invertibility, and Diagnostic Workflow
- Realized Volatility and Microstructure Noise
- Kalman Filter for a Latent Mean-Reverting Signal
JPMorgan Chase probability questions (8)
JPMorgan Chase stochastic processes questions (6)
JPMorgan Chase coding questions (6)
JPMorgan Chase optimization questions (5)
JPMorgan Chase finance questions (3)
JPMorgan Chase linear algebra questions (2)
JPMorgan Chase random variables questions (1)
JPMorgan Chase game theory questions (1)
JPMorgan Chase brain teasers questions (1)
JPMorgan Chase market microstructure questions (1)
JPMorgan Chase combinatorics questions (1)
JPMorgan Chase machine learning questions (1)
JPMorgan Chase interview FAQ
What kind of questions does JPMorgan Chase ask in quant interviews?
Candidates most often report options pricing, regression and expected value questions. This page collects 95 of them, 93 stamped with the month they were last reported — each with a full worked solution.
How hard are JPMorgan Chase interview questions?
The set spans 16 easy, 47 medium and 32 hard problems. Most sit at medium difficulty — solvable in a few minutes with clean reasoning — with a harder tail that rewards knowing the canonical tricks.
How do I prepare for the JPMorgan Chase quant interview?
Work through this set by topic (use the sidebar), starting from your weakest area. 13 problems are free to open with their full solution, so you can judge the quality before anything else. Then broaden out with the related firms below — the question families overlap heavily.
Are these the actual JPMorgan Chase interview questions?
They are built from candidate-reported JPMorgan Chase questions. We rewrite each prompt for clarity and author the worked solutions ourselves — we don't claim the wording is verbatim, and we never invent questions or recycle generic lists. 93 of 95 carry the month they were last reported.