What to Expect at an Allston Trading Interview
Allston Trading's interview process runs three to five rounds over three to six weeks, and it is built around two things the firm cares about above all else: correctness under time pressure and a genuine understanding of market microstructure. Founded in Chicago in 2002, Allston is a proprietary trading firm focused on high-frequency market making and statistical arbitrage, and it develops nearly all of its trading infrastructure in-house, which shapes an interview process that tests C++ depth and quantitative reasoning in equal measure.
This guide walks through the stages candidates report, the real question types for software engineer and quantitative researcher roles, and how to prepare. For the firm's own listing, see the Allston Trading firm page; for how Allston fits among the wider set of Chicago and global prop firms, see our prop trading firms guide.
Allston Trading at a Glance
- Founded: 2002
- Headquarters: Chicago, Illinois
- Size: Reportedly 100+ employees
- What they trade: High-frequency market making and statistical arbitrage across global electronic markets
- Roles they hire: Software Engineer, Quantitative Researcher, Systems Engineer
- Application route: the firm's careers page or the Allston Trading firm page on Quantt
The Process, Stage by Stage
Stage 1: CV Screen and Online Assessment
Applications are reviewed for strong STEM backgrounds, with a preference for candidates who have demonstrated genuine depth in mathematics, physics, computer science or electrical engineering. Many candidates then complete an online coding or quantitative reasoning assessment before the first live interview, typically within one to two weeks of applying.
Stage 2: Technical Phone Screens
One or two calls of 45 to 60 minutes each. Software engineering candidates face live coding in C++, often with follow-up questions on memory management, performance characteristics and low-latency design patterns, since Allston's infrastructure is built entirely in-house. Quantitative researcher candidates are tested on probability, statistics and market microstructure reasoning - how to think about a stale quote, how spread and inventory risk interact, and how to detect a statistical arbitrage opportunity that has decayed.
Stage 3: Onsite or Virtual Final Round
The final round typically runs three to five sessions in Chicago or over video. Engineers can expect systems design questions specific to trading infrastructure - building an order book, handling market data feeds, or designing for deterministic low-latency behaviour - alongside further coding. Researchers face harder statistical and market-microstructure questions, sometimes including a discussion of how they would approach designing or testing a statistical arbitrage strategy from scratch.
Stage 4: Offer
Because Allston is a smaller, technically-driven firm, decisions are reported to come reasonably quickly, often within one to two weeks of the final round.
Question Themes You'll Actually See
C++ and Low-Latency Systems
Given the firm's emphasis on building its own infrastructure, expect deep C++ questions: memory layout, cache behaviour, lock-free data structures and the trade-offs between throughput and latency. This is a firm where knowing the language at a surface level is not enough - interviewers probe for genuine systems-level understanding.
Market Microstructure
Statistical arbitrage and market making both depend on a precise understanding of how markets actually work at the tick level. Expect questions about bid-ask spread dynamics, adverse selection, and how a market maker should react to one-sided order flow. Candidates without prior market microstructure exposure should treat this as a distinct study area rather than an extension of general statistics.
Probability and Applied Statistics
Classic conditional probability and expected value problems appear alongside applied questions about statistical arbitrage: how you would test whether a pairs-trading relationship is genuinely mean-reverting versus spuriously correlated, and how transaction costs change a strategy's viable holding period. Our quant trader interview questions collection covers this style of problem in more depth.
Two Sample Questions
Stale quote (market microstructure). You are market making in a fast-moving instrument and your quote has not updated in 200 milliseconds while the underlying has moved meaningfully. What is the risk, and how should your system be designed to prevent it?
Approach: A stale quote exposes you to adverse selection - informed traders will pick off your quote at the old, now-incorrect price. The system should have a maximum quote age enforced independently of the pricing logic, with a fail-safe that pulls quotes entirely if the pricing engine has not refreshed within a defined window, rather than relying on the pricing model alone to always be fast enough.
Pairs trading validity (statistics). Two stocks have shown a correlation of 0.85 over the last year. How would you decide whether this relationship is tradeable as a pairs strategy?
Approach: Correlation alone is not sufficient; test for cointegration specifically, since a genuinely mean-reverting spread requires a stable long-run equilibrium relationship, not just correlated returns. Check the stability of the relationship across sub-periods, estimate a realistic half-life of mean reversion, and stress-test the strategy against transaction costs and the risk that the relationship breaks down structurally (a merger, a sector rotation, a change in one company's fundamentals).
How to Prepare - A Four-Week Plan
Week 1: C++ depth. Review memory management, cache-friendly data structures and concurrency primitives specifically, not just general algorithms. Work through problems that require reasoning about performance, not only correctness.
Week 2: Market microstructure. Study how order books work, how market makers manage inventory and adverse selection, and how statistical arbitrage strategies are constructed and risk-managed. This is the area most candidates under-prepare for relative to its weight in the interview.
Week 3: Probability and applied statistics. Drill conditional probability and expected value daily, then move into applied territory: cointegration, mean reversion, and how transaction costs affect strategy viability.
Week 4: Mock interviews. Run full mock loops covering both live coding and market microstructure discussion out loud. Being able to explain a stale-quote risk or a cointegration test clearly under time pressure is a distinct skill from understanding the concept alone.
Allston Trading vs Other Chicago Prop Firms
Chicago has one of the densest concentrations of proprietary trading firms in the world, and Allston sits alongside firms like Jump Trading, DRW and Tower Research in that cluster. What distinguishes Allston in candidate reports is scale and focus rather than prestige alone: it is a smaller, more concentrated operation than the largest Chicago firms, with a narrower strategic focus on high-frequency market making and statistical arbitrage rather than the broader multi-strategy remit some peers have expanded into.
That narrower focus shows up directly in the interview. Candidates report less time spent on broad behavioural or culture-fit questions and more time spent on the specific technical skills the firm's strategies actually require - C++ performance engineering and market microstructure reasoning in particular. For candidates deciding where to focus limited preparation time among several Chicago firm applications, the practical takeaway is that market microstructure depth pays off disproportionately at Allston relative to some larger, more generalist peers, where a broader spread of topics might appear across a longer interview process.
Compensation & recruiting notes
Allston is one of the older but more private of the Chicago HFT market makers, and it hires primarily on the engineering side rather than through a broad graduate scheme. That shapes the interview process into something closer to a targeted engineering loop than a standardised trader recruiting funnel, and the specifics vary by which team is hiring at the time. This guide is drawn from candidate reports and public sources; nothing here guarantees any specific interview format, question or outcome.
Frequently Asked Questions
How many interview rounds does Allston Trading have?
Typically three to five rounds spread across three to six weeks: a CV screen and online assessment, one or two technical phone screens, and a final round of three to five sessions. The exact structure varies by role.
What programming language does Allston Trading test?
C++ is the primary language for software engineering roles, reflecting the firm's in-house infrastructure. Python appears for research and tooling work, but C++ depth is treated as non-negotiable for engineering candidates.
Does Allston Trading ask market microstructure questions?
Yes, heavily. Given the firm's focus on high-frequency market making and statistical arbitrage, expect specific questions on order book dynamics, adverse selection and quote management, in addition to general probability and coding.
Is the Allston Trading interview harder for engineers or researchers?
They are demanding in different ways. Engineers face deep C++ and systems design questions; researchers face statistical arbitrage and market microstructure reasoning alongside probability. Candidates without a market microstructure background should expect that to be the steepest part of the learning curve regardless of track.
How does Allston Trading compare to Optiver or Akuna Capital?
All three are quantitative market-making and trading firms with technically rigorous interviews. Our Optiver interview guide and Akuna Capital interview guide cover comparable processes; Allston is smaller than either and leans somewhat more heavily on C++ systems depth given its in-house infrastructure focus.
How long does the Allston Trading hiring process take?
Allston's process usually runs three to six weeks from first application to offer. Because engineering hires are ultimately made by the teams a candidate would work on, the biggest source of variance is scheduling around the interviewing engineers themselves rather than any centralised recruiting backlog.
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