PRACTICE GUIDE OPTIVER
Optiver Quant Developer Practice Test
Optiver does not publish the shape of its quant developer screen, and candidates describe it as 2 to 4 problems questions in 60 to 120 minutes, roughly 20 to 40 minutes per question, written in a code editor and run against tests you cannot see.
Those are ranges across firms running this format rather than Optiver's own figures, so treat them as the shape to train against and check the instruction screen on the day for the marking rule.
Outcry is not affiliated with Optiver and has no access to their assessment content. This guide describes an assessment format that candidates report publicly; the questions here are generated by Outcry and are not Optiver’s own.
What it screens
A global market maker headquartered in Amsterdam, trading options, ETFs and futures on major exchanges.
- ✓Reading concurrent code and pointing at the defective line
- ✓Order-book data structures: what happens on a cross, a cancel, a partial fill
- ✓Algorithmic complexity chosen for the input sizes stated in the problem
- ✓Monte Carlo methods and when a simulation beats a closed form
Where it sits at Optiver
A global market maker headquartered in Amsterdam, trading options, ETFs and futures on major exchanges. What that means for the screen is that the questions tend to be drawn from the work rather than from a textbook, so the format below is the shape to train against rather than a syllabus.
Candidates also report 4 other screens at Optiver, covered separately on this site. Where a firm runs several, they usually sit in one round rather than spread across the process, so the pacing of the whole set matters more than any single section.
The format
Optiver does not publish this screen's shape, and it varies between firms, so these are the ranges candidates report rather than exact figures.
| Questions | 2 to 4 problems |
|---|---|
| Time | 60 to 120 minutes |
| Per question | 20 to 40 minutes |
| Negative marking | No |
| Answer style | Code editor, run against hidden tests |
| Where it sits | First technical round, usually on HackerRank or CoderPad |
What it tests, with a worked example
Every example below is generated by Outcry, drawn from the same question generators the timed drills run. None of them is Optiver’s.
Complexity that is actually graded
Hidden tests sized so the naive solution times out. A correct answer that is too slow scores the same as a wrong one.
Reading someone else's code
A diff or a function with a bug in it, and the question is where.
Example
A hot loop does `results.push_back(x)` a million times with no other setup. What is the cheapest fix?
- reserve() the final size once before the loop
- Switch to std::list to avoid copying
- Make results a static global
- Use emplace_back instead of push_back
Answer reserve() the final size once before the loop
Growth reallocates and copies roughly log₂(n) times. One reserve makes it a single allocation. emplace_back saves a construction, not the reallocations.
Language and systems detail
Memory, references, undefined behaviour and the things that bite in production.
Example
A counting semaphore starts at 5. 7 completed wait operations and 5 completed signal operations have run against it. What is its value now?
- 2
- 3
- 10
- -2
Answer 3
Each completed wait subtracts one and each signal adds one: 5 - 7 + 5 = 3. Only completed waits count, which is why a negative reading would mean blocked processes rather than a legal value.
Numerical and data handling
Floating point, aggregation and joins on data that does not fit the obvious shape.
Example
A fund has volatility 20% and the index has volatility 24%. Their correlation is 0.8. What is the fund's beta to the index?
Answer 0.6666666666666666
Beta = correlation x (fund vol / index vol) = 0.8 x 20/24 = 0.667. Correlation and beta only agree when the two volatilities match, which here they do not.
Edge cases
Empty input, one element, duplicates and overflow. The hidden tests always include them.
Statistics in code
Rolling windows, correlations and quantiles, implemented rather than imported.
Example
The maximum likelihood estimate of a normal variance divides the squared deviations by n. With n = 8, how does it compare to the true variance on average?
- Too small by a factor of 0.875
- Too large by a factor of 1.143
- Too small by a factor of 0.125
- Unbiased - maximum likelihood estimators always are
Answer Too small by a factor of 0.875
E[MLE] = ((n − 1)/n)σ² = (7/8)σ² = 0.875σ². Maximum likelihood is consistent, not unbiased, and the gap only closes as n grows: at n = 8 the estimate is 12.5% low on average.
What a good score looks like
Coding screens are usually pass-fail on hidden tests rather than scored, and candidates commonly report that a solution passing every correctness test still fails on a timeout. Treat full marks as solving every problem inside the complexity bound, not merely solving it.
How to train for it
- 01Implement the core structures from scratch once each. The screens ask you to build them, not use them.
- 02State the complexity before you write. If it is worse than the input size allows, the approach is already wrong.
- 03Get the function signature exactly right before anything else. Return type and ordering are graded, and a correct algorithm behind a wrong signature scores zero.
TRAIN IT HERE
The drills that match each section
Concurrency Clash
Find the data race, name the fix - real C++ defect patterns, five levels.
Order Book
Matching-engine mechanics: crosses, cancels and partial fills.
Algorithm Lab
DP tables, Monte Carlo estimation and speed rounds at four difficulty tiers.
SIT THE FULL BATTERY
All the sections back to back on one clock, marked the way the real screen marks them, with a by-skill breakdown at the end. Included with any pass.
Also reported at Optiver
Common questions
- Is the Optiver quant developer test multiple choice?
- Reported as code editor, run against hidden tests. Formats move, so treat this as the shape rather than a guarantee.
- How long is the Optiver quant developer test?
- Candidates report 2 to 4 problems questions in 60 to 120 minutes, roughly 20 to 40 minutes per question.
- Is there negative marking on the Optiver quant developer test?
- No. A wrong answer costs nothing beyond the mark you would have earned, so leaving an item blank is never better than guessing at it.
- How do I practise for it free?
- Every drill linked on this page is free to play, with no account, inside a daily run cap. Questions are generated fresh each run, so there is nothing to memorise between attempts.