IMC quant interview preparation: a role-specific study guide

Prepare probability, technical problem solving and a clear account of your work for an IMC application. Official recruitment guidance varies by region and stream, so begin with the correct careers page. The original practice below links numerical reasoning to market mechanics and coding. It is an editorial study plan, rather than a replica of IMC assessments.

Use current regional recruiting information

IMC's European recruitment page says the process is tailored to the candidate and role. Its interview preparation article describes an assessment and subsequent behavioural and technical stages in its own regional context. Treat the actual invitation as the source for the format you must follow.

The firm's careers material distinguishes trading, technology and research. Choose a preparation path from that role rather than assuming that every applicant takes the same timed maths test. Keep eligibility, working rights and graduation dates separate from your technical study progress.

Trading: join probability to a decision

Practise fair-value estimates and simple updates, then explain the trade or quote you would make under a stated risk limit. Separate expected value from the chance of winning and from the size of a possible loss. When order size exceeds the best displayed depth, calculate an average fill before discussing profit.

Use the market-making and order-book tools to expose those differences. Record what information a counterparty action provides and how a fill changes your inventory. The point of our exercises is to build transparent reasoning, rather than predict the content of an employer test.

Technology and research: make evidence reproducible

For technology, implement a small task with explicit input contracts and boundary tests. For research, explain the observation time, the prediction target and the holdout design. Both benefit from a project that can run from a clean environment with fixed inputs. Be able to describe a trade-off you made and the measurement behind it.

Practise the conversation

Explain a past project, then invite questions about an assumption you are least confident in. Describe how you would test it. Prepare examples of collaboration and a correction you made after feedback, using your actual experience. The aim is a coherent account of your work; avoid rehearsing a fictional ideal candidate story.

Original practice questions with worked answers

1. Probability versus expected value

A bet wins 1 with probability 0.9 and loses 20 otherwise. What is its expected payoff?

Answer. The mean is 0.9×1 − 0.1×20 = −1.1. A 90% win rate can coexist with a negative expected payoff because the loss is much larger than the gain.

2. An inventory check

You start flat, buy 3 units at 10 and sell 1 at 11. If settlement is 9, what is final P&L?

Answer. Trade cash is −30 + 11 = −19. Inventory is 2, worth 18 at settlement. Final P&L is −1. Track cash and inventory separately before combining them.

3. A streaming mean

How do you update the mean of n observed numbers after receiving x, without storing the earlier numbers?

Answer. Use new_mean = old_mean + (x − old_mean)/(n + 1). Store the count and mean. The update uses O(1) extra space; initialise the first observation explicitly and consider numerical precision for large counts.

Topic practice behind this plan

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Primary sources and scope

Employer information was checked on the review date. Our study activities and original questions are editorial suggestions. Recruiting requirements, regional processes and vacancies can change; the employer’s current instructions take priority.