Quant interview preparation
Prop market making and quantitative research, weighted the way the interviews actually are: probability and expected value, statistics and machine learning, market making logic, programming and options. Every question is either traced to a named firm from a public candidate report, or tagged at desk level when we could not trace it, and every probability answer shows the reasoning path rather than just the number.
100 questions, mapped to the firms that asked them
- Questions
- 100
- Traced to a firm
- 53
- Firms
- 15
- Updated
- September 2026
082Something in your C++ program is overwriting memory it should not. How do you find it?Tower Research CapitalForeign Exchange · London · 2019
Say this
Reach for the sanitisers first. AddressSanitizer catches out-of-bounds writes and use-after-free with roughly a two times slowdown and tells you both the write site and the allocation site. If the corruption is timing-dependent, add ThreadSanitizer for data races.
Then walk it
- Order of tools: compile with -fsanitize=address,undefined and run the failing case. That resolves most buffer overruns and use-after-free immediately. Valgrind memcheck is slower but needs no recompile and catches uninitialised reads that ASan misses.
- If the corrupted location is known but the writer is not, set a hardware watchpoint in gdb on that address with watch, and let it break when something writes. Four watchpoints on x86, which is usually enough.
- If the corruption is not reproducible, make it reproducible before anything else. Record the inputs, pin the threads, disable randomisation, and consider record-and-replay with rr. A bug you cannot reproduce cannot be fixed, only guessed at.
- Common causes to check by inspection while the tools run: writing past the end of a fixed buffer, a dangling reference into a vector that reallocated, a stale pointer into an object that moved, a struct written with memcpy at the wrong size, and two threads writing the same cache line without synchronisation.
- And the systems answer for a production trading process where you cannot run ASan in the hot path: build with sanitisers in a test environment and in a canary, add canary values or guard pages around suspect buffers, and turn on the allocator's own debug checks. I would also say plainly that the fastest fix for a class of these bugs is to stop using raw buffers, because bounds-checked containers and spans eliminate the whole category.
Where candidates lose it
Answering add print statements. That is the answer of someone who has never used a sanitiser, and at a firm running C++ in production it is disqualifying. Name ASan specifically, name the gdb watchpoint technique for a known address, and say how you would make an intermittent bug reproducible before you try to find it.
Expect next
- What does AddressSanitizer not catch?
- How would you debug this in production where you cannot run sanitisers?
- What is a data race and why is it undefined behaviour?
Reported by candidates at Tower Research Capital (Foreign Exchange, London, 2019). Source: Wall Street Oasis.
084How would you design a system to troubleshoot latency in a trading stack?CitadelProp Trading · New York · 2026
Say this
Timestamp at every hop with one clock, measure distributions not averages, and make the whole path attributable so you can say which segment consumed the microseconds. The design principle is that you cannot fix what you cannot decompose.
Then walk it
- Instrumentation: hardware timestamps at the network card for packet in and packet out, plus software timestamps at each stage, market data decode, book update, strategy decision, order encode, and kernel bypass send. Carry a correlation id through the whole chain so a single event can be reconstructed end to end.
- Clocks are the hard part. Use PTP with hardware timestamping across hosts, not NTP, and record clock offset and drift as first-class data. Two hosts disagreeing by fifty microseconds will invent latency that does not exist and hide latency that does.
- Statistics: report the median, the 99th, the 99.9th and the maximum. Averages are useless here because the distribution is heavily right-tailed and the tail is exactly what costs money. Track per-segment histograms, ideally with HDR histograms so the tail resolution survives.
- Storage and analysis: stream the records off the critical path into a time-series store, then build the two views that actually get used, a per-segment breakdown over time and a drill-down into the slowest individual events. Alert on percentile regressions against a rolling baseline rather than on fixed thresholds.
- Then the causes to design for, because the system exists to distinguish them: garbage collection or allocation pauses, page faults, context switches and CPU migration, interrupt coalescing settings, cache misses and false sharing, queueing at the exchange gateway, and simple network congestion. And I would say the measurement must not itself be on the hot path, so lock-free ring buffers with a separate reader thread, because an observability system that adds ten microseconds has destroyed what it measures.
Where candidates lose it
Describing logging and monitoring generically. This is a specific systems question and the differentiators are clock synchronisation, percentile rather than mean reporting, and keeping instrumentation off the critical path. Talk in microseconds, and be able to name concrete causes of a tail latency spike.
Expect next
- How do you synchronise clocks across hosts, and to what accuracy?
- Why report the 99.9th percentile rather than the average?
- Walk me through diagnosing a spike that happens once a day.
Reported by candidates at Citadel (Prop Trading, New York, 2026). Source: Wall Street Oasis.
Firm tags come from public, anonymous candidate reports on Wall Street Oasis: strong signal, not sworn testimony. Firms are named as the places a question was reported, not as partners of Fin Maverick. Answers are written for this page to show how to think out loud; they are not scripts to recite.

