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Maven Securities Interview Questions 2026: 62 Trader, Quant & Internship Questions
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2026 trading & quantitative interview playbook

Maven Securities Interview Questions & Answers

Train for timed mental maths, probability assessments, options market making, trading games and quant research interviews.

Last updated: · 62 practice questions · 14-day plan

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MAVEN INTERVIEW // MARKET SIMULATOR● PRACTICE MODE
ILLUSTRATIVE BID99.80
ILLUSTRATIVE ASK100.20
SPREAD0.40
FAIR VALUE100.00
Illustrative numbers only — not live market data.

How to prepare for a Maven Securities interview

Maven Securities is a proprietary trading firm known for options market making. Its early-career routes span trading, quantitative research and technology, each requiring a different combination of maths, decision-making and coding skills.

01

Trading

Fast mental maths, expected value, options Greeks, quoting, risk and simulated markets.

02

Quant research

Probability, statistics, data analysis, signal validation, modelling and code.

03

Technology

Algorithms, software engineering, low-latency systems, testing and reliability.

Research note: Maven’s official Emerging Talent pages establish its programme tracks. Interview-stage descriptions below also draw on candidate reports and should not be interpreted as a guaranteed sequence.

What the Maven Securities interview process may involve

Candidate reports from 2026 repeatedly mention time-pressured probability, mental maths and sequence assessments. Some report coding tests, recorded interviews, trading games and assessment centres. Exact stages vary by programme and office.

01 · ApplyChoose the appropriate trading, quant research or technology pathway.
02 · Online testsReported arithmetic, probability, sequences and role-specific coding.
03 · InterviewsDiscuss motivation, technical reasoning, risk and decisions.
04 · Practical exercisesSome candidates report market-making games or assessment centres.

Maven separately publishes an experienced-hire three-stage process. Do not assume that experienced-hire stages are identical to graduate or internship recruitment.

62 Maven Securities interview questions with answers

Filter by topic and open each question for a worked answer or structured explanation. These are independently authored practice questions, not leaked or verified assessment items.

1. Why Maven Securities rather than an investment bank? Motivation & fit

Suggested approach: Explain liquidity provision and the feedback loop of trading decisions; connect to rapid learning, probabilistic thinking and teamwork.

2. What does an options market maker do? Motivation & fit

Suggested approach: Quotes bid and ask prices, provides liquidity and manages inventory and Greeks while competing for order flow.

3. Why are you interested in trading rather than quantitative research? Motivation & fit

Suggested approach: Trading emphasises live decisions and risk; research emphasises models, data and systematic improvement. Show your fit.

4. Tell me about a decision you made with incomplete information. Motivation & fit

Suggested approach: Structure around available evidence, probability, downside, action and updating after new information.

5. Describe a mistake under pressure. Motivation & fit

Suggested approach: Take ownership, quantify the impact, explain risk containment and what changed in your process.

6. How would you react after losing three simulated trading rounds? Motivation & fit

Suggested approach: Avoid chasing losses; review your estimates, sizing, spreads and opponents' behaviour.

7. Why Maven's emerging talent programme? Motivation & fit

Suggested approach: Discuss its trading, quant research and technology pathways and training, without claiming a guaranteed placement.

8. How do you explain a technical idea to a nontechnical teammate? Motivation & fit

Suggested approach: Lead with intuition, then a simple numerical example, then limitations.

9. Calculate 37 × 24 without a calculator. Mental maths & sequences

Suggested approach: 37×(20+4)=740+148=888.

10. Calculate 349 × 24. Mental maths & sequences

Suggested approach: 349×(6×4) or 349×(20+4)=6,980+1,396=8,376.

11. What is 17% of 240? Mental maths & sequences

Suggested approach: 10%=24; 5%=12; 2%=4.8; total 40.8.

12. Estimate 1/17 as a percentage. Mental maths & sequences

Suggested approach: Approximately 5.88%; use 1/16=6.25% as a nearby anchor.

13. Compute 125 × 48. Mental maths & sequences

Suggested approach: 125×(50−2)=6,250−250=6,000.

14. What is 15% of 15%? Mental maths & sequences

Suggested approach: 0.15×0.15=0.0225, or 2.25%.

15. Continue 2, 6, 12, 20, 30, … Mental maths & sequences

Suggested approach: Differences are 4,6,8,10; next difference 12, giving 42.

16. Continue 3, 7, 15, 31, … Mental maths & sequences

Suggested approach: Double and add one; next is 63.

17. Estimate 1.03 raised to the tenth power. Mental maths & sequences

Suggested approach: Approximately 1.344; for a quick approximation use compounding or ln(1.03)≈0.0296.

18. A price moves from 80 to 92. What is the percentage change? Mental maths & sequences

Suggested approach: 12/80=15%.

19. What is the square root of 1,225? Mental maths & sequences

Suggested approach: 35, because 35²=1,225.

20. A probability is 0.4. What are the odds against the event? Mental maths & sequences

Suggested approach: P(not)/P(event)=0.6/0.4=3:2.

21. Two fair dice: probability of a sum of 7? Probability & statistics

Suggested approach: Six of 36 equally likely outcomes: 1/6.

22. Probability of at least one six in four fair die rolls? Probability & statistics

Suggested approach: 1−(5/6)^4≈51.8%.

23. Expected number of fair coin tosses until the first head? Probability & statistics

Suggested approach: 2 tosses, by geometric distribution with p=0.5.

24. A coin is flipped three times. Probability of exactly two heads? Probability & statistics

Suggested approach: C(3,2)/8=3/8.

25. Expected value of a fair six-sided die? Probability & statistics

Suggested approach: (1+2+3+4+5+6)/6=3.5.

26. What is the variance of a Bernoulli variable with p=0.3? Probability & statistics

Suggested approach: p(1−p)=0.21.

27. You draw two cards without replacement. Probability both are aces? Probability & statistics

Suggested approach: (4/52)×(3/51)=1/221.

28. A test is 90% sensitive and 95% specific; prevalence 1%. P(disease | positive)? Probability & statistics

Suggested approach: 0.009/(0.009+0.0495)≈15.38%; apply Bayes' rule.

29. How many distinct arrangements of MISSISSIPPI? Probability & statistics

Suggested approach: 11!/(4!×4!×2!)=34,650.

30. If X and Y are independent with variances 4 and 9, variance of X+Y? Probability & statistics

Suggested approach: 13; add variances when covariance is zero.

31. What is the expected maximum of two fair six-sided dice? Probability & statistics

Suggested approach: 161/36≈4.472; use P(max=k)=(k²−(k−1)²)/36.

32. A fair coin pays +£3 for heads and −£2 for tails. EV? Probability & statistics

Suggested approach: 0.5×3−0.5×2=£0.50 per play.

33. Explain bid, ask and spread. Market making & options

Suggested approach: Bid is buying quote, ask selling quote; spread compensates for risk, costs and adverse selection.

34. You believe fair value is 100. How might you quote a two-sided market? Market making & options

Suggested approach: Start around fair value, e.g. 99–101, then adapt to volatility, inventory and information risk.

35. Why widen spreads in volatile markets? Market making & options

Suggested approach: Greater price uncertainty and adverse selection risk; trade-off with execution probability.

36. How does inventory affect your quotes? Market making & options

Suggested approach: If long, skew quotes to encourage selling inventory and discourage buying more, subject to risk limits.

37. What is delta? Market making & options

Suggested approach: Approximate option price sensitivity to a small change in underlying price.

38. What is gamma? Market making & options

Suggested approach: Rate of change of delta as underlying price changes.

39. What is vega? Market making & options

Suggested approach: Sensitivity of an option's value to a one-percentage-point change in implied volatility, under a stated convention.

40. What is theta? Market making & options

Suggested approach: Option value sensitivity to passage of time, all else equal.

41. Why do market makers delta hedge? Market making & options

Suggested approach: Reduce directional exposure while recognising gamma, volatility, jumps and hedging costs remain.

42. How does implied volatility differ from realised volatility? Market making & options

Suggested approach: Implied is extracted from option prices; realised is calculated from historical returns.

43. What happens to a call option when volatility rises? Market making & options

Suggested approach: All else equal, a standard vanilla call generally becomes more valuable.

44. What is adverse selection? Market making & options

Suggested approach: More-informed counterparties disproportionately trade when your quote is stale or mispriced.

45. How would you test whether a trading signal is real? Quant research & coding

Suggested approach: Specify hypothesis, avoid leakage, use out-of-sample data, transaction costs and robustness tests.

46. What is overfitting? Quant research & coding

Suggested approach: A model learns noise rather than generalisable structure; use validation and simplicity.

47. Explain the difference between correlation and causation. Quant research & coding

Suggested approach: Correlation measures association, while causal inference needs additional assumptions or experimental design.

48. How do you handle missing tick data? Quant research & coding

Suggested approach: Audit source, missingness patterns and timestamps; avoid blindly forward-filling.

49. What is look-ahead bias in backtesting? Quant research & coding

Suggested approach: Using information not available at decision time; enforce point-in-time features.

50. How would you detect an outlier in high-frequency prices? Quant research & coding

Suggested approach: Check venue, timestamps, crossed quotes, spread, trade size and neighbouring observations.

51. What is the complexity of binary search? Quant research & coding

Suggested approach: O(log n) time on sorted random-access data.

52. How would you implement a rolling mean on a stream? Quant research & coding

Suggested approach: Use a fixed-size queue and running sum for O(1) updates.

53. Why is latency important in market making? Quant research & coding

Suggested approach: Stale quotes raise adverse selection and execution risk; correctness and stability remain essential.

54. How would you monitor a production trading model? Quant research & coding

Suggested approach: Track prediction drift, realised P&L, fill rates, latency, errors, exposure and kill switches.

55. Quote a market on the number of cars passing a bridge per hour. Trading games & cases

Suggested approach: Define assumptions, estimate volume, choose uncertainty bounds and a bid–ask spread; update after trades.

56. You are long inventory and another trader aggressively sells to you. What do you do? Trading games & cases

Suggested approach: Reassess fair value and information, reduce size or skew quotes, respect limits.

57. A game offers +£8 with probability 0.4 and −£4 otherwise. EV? Trading games & cases

Suggested approach: 0.4×8−0.6×4=+£0.80.

58. Should you always bet on a positive-EV game? Trading games & cases

Suggested approach: No; consider variance, drawdowns, bankroll, correlations, liquidity and limits.

59. Two independent games have identical EV but different variance. Which is better? Trading games & cases

Suggested approach: Depends on utility, capital constraints and portfolio diversification; EV alone is insufficient.

60. How do you estimate the number of piano tuners in London? Trading games & cases

Suggested approach: Fermi decomposition: population, households, piano ownership, service frequency and annual capacity.

61. What is the Kelly fraction for +1/-1 payoff with p=0.55? Trading games & cases

Suggested approach: f*=2p−1=10% of bankroll under idealised independent repeated bets.

62. If you observe informed buyers repeatedly lifting your ask, what changes? Trading games & cases

Suggested approach: Increase fair-value estimate, adjust quotes and inventory, check adverse-selection risk.

Know the theory. Can you answer under pressure?

Rehearse technical and behavioural questions in a realistic mock interview.

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Worked case 1: probability, expected value and bet sizing

Suppose a game costs nothing to enter and pays +£8 with probability 40%, or −£4 with probability 60%. Should you play?

Calculate the expected value

Win probability40%
Expected value / play+£0.80
Break-even win rate33.3%

EV = 0.4 × £8 + 0.6 × (−£4) = +£0.80. Break-even probability solves 8p−4(1−p)=0, so p=1/3.

Variance: E[X²] = 0.4×64 + 0.6×16 = 35.2; Var(X)=35.2−0.8²=34.56; standard deviation≈£5.88.

Interview insight: Positive EV does not mean betting unlimited capital. Consider drawdown, repeatability, correlation with other positions and risk limits.

Follow-up: what if the game changes?

Explain how your decision changes if the win probability falls, if losses become larger, if you can play many independent rounds, or if capital is constrained. Interviewers may be assessing your reasoning as much as the arithmetic.

Worked case 2: make a two-sided market

You estimate fair value at 100.00. Initially, you quote 99.80 bid and 100.20 ask. Another participant repeatedly buys from you at your ask.

Quote → trade → update

StepDecisionReasoning
Initial quote99.80 / 100.20Illustrative 0.40 spread around estimated value
Customer buysYou sell at 100.20You become shorter inventory
Repeated buyingReassess fair valuePotential informed flow or price discovery
RequoteAdjust price, size and skewManage inventory and adverse selection

Key lesson: A market maker does not simply maximise spread. Quoting quality balances execution, inventory risk, information risk and hedging costs.

What a strong answer sounds like

“I would check whether the flow signals new information, whether the underlying market moved, and how much inventory I have accumulated. I would update fair value if justified, skew quotes to control exposure, and avoid offering stale prices.”

Prepare for your specific Maven Securities role

Graduate Trader

Prioritise arithmetic speed, probability, market making, options intuition and composure.

Quant Researcher

Prioritise statistical inference, backtesting, Python, research design and model validation.

Software Engineer

Prioritise algorithms, data structures, concurrency, system performance and testing.

Maven’s official emerging talent offering includes trading spring weeks, summer internships and graduate programmes, plus quant research and technology pathways. Check the current vacancy for location and eligibility.

14-day Maven interview preparation plan

Day 1 · Learn Maven's options market-making business and role tracks
Day 2 · Benchmark 60-second arithmetic accuracy
Day 3 · Practise percentages, fractions and sequences
Day 4 · Master permutations, combinations and conditional probability
Day 5 · Work through expected value and variance
Day 6 · Practise Bayes and independent-event puzzles
Day 7 · Learn bid/ask, spreads and inventory management
Day 8 · Study option delta, gamma, vega and theta
Day 9 · Run market-making estimation games
Day 10 · Solve bankroll sizing and EV-versus-risk problems
Day 11 · Prepare quant research or coding questions for your track
Day 12 · Run a timed mixed assessment and review mistakes
Day 13 · Rehearse market-making game explanations and behavioural stories
Day 14 · Complete a mock interview and revisit weak areas

Maven Securities interview FAQs

What is the Maven Securities interview process?

It depends on the role. Candidate reports describe timed online assessments, recorded interviews, technical discussions and trading games. Maven's experienced-hire process is documented separately and should not be assumed to apply to graduates.

Does Maven Securities test mental maths?

Yes, numerous candidate reports describe time-pressured arithmetic, probability and sequence questions, particularly for trading tracks.

Are there market-making games at the assessment centre?

Some trading candidates report simulated markets, card games and group exercises; this is not a guaranteed universal stage.

What should I prepare for a quant researcher interview?

Probability, statistics, coding, signal testing, data cleaning, time series, backtesting bias and model validation.

What should I prepare for a trading internship?

Fast mental arithmetic, expected value, conditional probability, option Greeks, quoting and inventory risk.

Does Maven offer technology graduate opportunities?

Yes. Maven lists technology early-career pathways, alongside trading and quant research.

Is Maven Securities an investment bank?

No. Its core activity includes proprietary trading and options market making, so preparation differs from M&A and corporate finance interviews.

Are these actual Maven interview questions?

This guide uses independently written practice questions informed by official role descriptions and candidate-reported themes; it does not claim to reproduce confidential assessments.

How long should I prepare?

Use a structured two-week plan as a starting point and extend it if speed or technical accuracy remains inconsistent.

How can I practise under time pressure?

Run short timed sets, record accuracy by category, revisit errors and rehearse explaining market-making decisions aloud.

Research sources and methodology

Official Maven materials establish its business, programmes and role pathways. Candidate reports are anecdotal and may vary by date, office and position. Numerical examples and question explanations on this page are original educational material.

Maven Emerging Talent ↗Maven Careers Overview ↗Maven FAQs ↗Maven Experienced Hires Process ↗Candidate-reported interview experiences ↗Quant Trading Intern candidate reports ↗

Independent educational guide by Senna, not affiliated with or endorsed by Maven Securities. Confirm the proposed canonical URL and publication timestamp when deploying.