Market making vs stat arb vs macro: how quant firms actually make money

"Quant firm" covers businesses that have very little in common day to day. One firm earns a sliver on millions of trades and holds most positions briefly. Another holds a book of stocks for days and lives or dies on whether a statistical signal survives contact with the market. A third rides price trends in futures for months and can lose money for a year straight by design. Candidates often pitch all three the same way, and interviewers notice.

This guide maps the four main ways quant firms make money, which firms are associated with each (from their own descriptions or press reporting), and what each model implies for your work. Evidence is labeled as official (a firm's own website or publications, or a regulator), reported (press), or self-reported (forums such as Blind), with dates. We claim no knowledge of any firm's actual strategies.

Last reviewed 2026-10-04. Firm descriptions and figures change, so check anything dated against the linked sources.

The short version

The horizon column is a rough relative ordering drawn from the sources cited in this article, and exceptions exist; eFinancialCareers, for example, notes that market makers increasingly run "mid-frequency market making strategies where positions are held from minutes to days" (reported, July 2026). Several of the largest firms now run more than one model, which is the last section of this guide.

Market making: getting paid to provide liquidity

A market maker continuously quotes a price to buy and a price to sell. eFinancialCareers' one-line summary: electronic market makers "generate revenue by quoting buyers one price, sellers another, and pocketing the difference" (reported, March 2026). The same piece says the model needs enormous scale: Citadel Securities is involved in roughly 25% of all US equities trades.

Firms in this group say so plainly. Optiver: "we continuously quote buy and sell prices across global financial markets," using "our own capital and advanced technology to provide liquidity at scale." Jane Street calls itself "a global liquidity provider and trading firm" and one of the world's largest market makers, active on more than 200 electronic exchanges and other venues, and highlights its ETF expertise. Flow Traders says it provides "liquidity continuously," and Maven describes itself as "a leading provider of liquidity for global listed derivatives." Hudson River Trading calls itself "a multi-asset class quantitative trading firm that provides liquidity on global markets and directly to our clients." XTX Markets says it uses machine learning to forecast prices for over 53,000 instruments and trades about $250bn a day. (All official, firm websites, read 2026-10-04.)

The money is large and tends to rise with volatility. GuruFocus, citing Bloomberg, reported that Jane Street made about $39.6bn in trading revenue in 2025, and Bloomberg (syndicated by The Business Times) reported that Citadel Securities posted a record $12.2bn, adding that the firm "capitalises on market turbulence, stepping in as a liquidity provider during dislocations" (reported, March and May 2026).

What the work looks like. Feedback tends to be fast, since a quoting change shows up in the same day's results. HRT says its trading teams are "very roughly organized by the time horizon at which they trade, and then by asset class and region" (official, October 2025). eFinancialCareers profiled a Citadel Securities quant who works on model improvements through the day, applies them about 90 minutes before leaving, and runs overnight experiments to shape the next day's changes (reported, July 2026). The same outlet, citing ex-Jane Street trader Grant Stenger's comments to FT Alphaville that "the core job is actually identical" to AI-lab research, sums up the loop as using data to build a model, executing it within constraints, and using feedback to improve it (reported, July 2026).

Culture can be engineering-heavy. One anonymous Blind commenter put it bluntly: "hft firms are more engineer focused," whereas at many hedge funds technologists rank behind traders and portfolio managers (self-reported, March 2023; one person's view). SIG says its traders learn probability, odds and expectancy "by regularly playing strategic game[s] with senior traders" (official).

That is why market-making interviews lean on mental math, probability and making prices under uncertainty. Our market-making games practice quoting and sizing, and the Optiver guide shows how one market maker assesses those skills.

Statistical arbitrage: many small, uncertain predictions

Stat arb is the classic quant hedge fund business. eFinancialCareers gives the textbook version: it puts "stocks into related pairs. If one stock in that pair does well and outperforms the other, it will be sold short" (reported, September 2026). Modern versions run many signals across large books, but the idea is the same: predict relative moves, stay roughly market neutral, and let a small edge compound.

One Blind poster's understanding was that HFT firms earn mostly from "low latency market making strategies whereas quant hedge funds are using mid-frequency strats like long/short or stat arb." One reply added that large funds such as AQR also run factor strategies, and another said "quant hedge funds do a lot more than stat [arb] or mid-freq" (self-reported, March 2023).

How these systematic firms describe their work (official). None of them uses the term stat arb on these pages; the grouping here is an editorial call (analysis):

• PDT Partners: "developing quantitative models to identify market inefficiencies and predict market movements," with ideas "thoughtfully explored, peer reviewed, and empirically validated" before going live.
• Cubist (Point72's systematic arm): "systematic, computer-driven trading strategies" across "multiple liquid asset classes," with 600+ team members.
• D. E. Shaw: strategies "spanning the continuum from systematic to discretionary," with more than $115bn in investment and committed capital as of 1 September 2026.
• Two Sigma: a scientific approach built on "10,000+ data sets."
• Millennium: lists "Quantitative Strategies" and "Equity Arbitrage" among its six strategy areas.

What the work looks like. The loop is slower and more statistical: form a hypothesis, find data, backtest, have it reviewed, then deploy. Feedback is noisy; a signal can look good for months and still be luck. The hardest problems are overfitting, transaction costs and crowding. In July 2025 Business Insider reported that "Qube, Cubist, and Man Group have suffered prolonged losses in recent weeks" with quants "scrambling to identify the cause," and in July 2026 FT Alphaville reported that Goldman Sachs' prime brokerage estimated quants had just had their worst five days since December 2023, a 3.1% aggregate loss concentrated in the short side of their portfolios (reported). Interviews here weight statistics, regression, probability and coding over arithmetic speed.

Systematic macro and CTAs: trends across markets

A Commodity Trading Advisor is, in the US regulator's definition, someone who "for compensation or profit, advises others ... as to the value of or the advisability of trading futures contracts, options on futures, retail off-exchange forex contracts or swaps" (official, NFA). In practice "CTA" usually means a systematic fund trading futures, and the signature strategy is trend following. AQR researchers define it as "going long markets with recent positive returns and shorting those with recent negative returns" and found it profitable across roughly 110 years of data (official firm research, 2017).

Man AHL says it was "founded in 1987 as a Commodity Trading Advisor" and has since "evolved into a multi-strategy quant business," with momentum programmes spanning 800+ markets. Winton says it has pioneered trend following "since 1997" and trades "thousands of exchange-traded and over-the-counter instruments" (both official).

Returns are lumpy. With Intelligence called CTAs "the weakest-performing primary hedge fund strategy in 2025" midway through that year, after a 13-month drawdown for large trend followers, and the Wall Street Journal ran "A Wild Year for Markets Hits Trend-Following Hedge Funds" in August 2025. By January 2026 a Bloomberg headline read "Trend-Chasing Quants Soar Just as Market Whiplash Tests Models" (reported).

What the work looks like. Fewer, larger, slower decisions. Research centers on robustness across decades and asset classes, portfolio construction, risk targeting and futures mechanics; microseconds rarely matter. You need patience: a strategy can be correct and still lose for a year. Interviews tend to probe time series, econometrics and portfolio maths. Our Winton guide covers one firm in this group.

Event-driven quant: trading the calendar

Event-driven funds, in eFinancialCareers' definition, "try to profit from one-off events," merger arbitrage being the classic case (reported, September 2026). The quant version focuses on events with predictable mechanics, the best known being index rebalances. Business Insider describes the strategy as portfolio managers betting "on which stocks will be added to or removed from indexes such as the Russell 3000 or S&P 500 with the help of quantitative tools" (reported, December 2025).

It is a lucrative but risky niche. Business Insider reported that Millennium's index-rebalance teams were down "hundreds of millions of dollars" at one point in November 2025. BI said the cause was not immediately clear, though industry sources said many index-rebalance PMs were caught out by MSCI's reconstitution. Both Business Insider and eFinancialCareers cite Bloomberg for a loss of about $900m earlier in 2025, describing the window differently (March, or the three months to March). eFinancialCareers also reports large gains from the same teams in earlier years (all reported, December 2025). Maven, best known as a market maker, has a multi-strategy group that "operates similarly to a pod-based hedge fund" with "a mix of 25 discretionary and systematic teams"; in 2025 that group was reported to be hiring "short-term or event-driven traders" (reported, June 2025).

What the work looks like. Your calendar is the strategy: index methodology, announcement dates, deal terms. It mixes quantitative forecasting (who gets added, how much passive money must trade) with judgment about crowding, since many funds trade the same events.

The lines are blurring

The four boxes are less separate than they were. Bloomberg (syndicated by The Business Times) reported that "Jane Street and Hudson River Trading each have hedge fund-style trading units, in addition to market-making operations" (reported, March 2026). Business Insider says prop firms have been "edging into medium-frequency quant strategies long considered the dominion of hedge funds," and that Tower Research backs more than 10 external trading teams (reported, November 2025). In the other direction, Squarepoint launched a market-making spinout, STG Securities, and Qube hired HRT's former head of options market making (reported, March 2026). In September 2025 FT Alphaville described the two industries converging on holding periods of a few hours to a few days, with prop firms stretching into slower signals and stat-arb funds speeding up. At Tower Research, mid-frequency trading had grown to about 25 to 30% of revenues, according to a person familiar with the matter (reported).

Structure differs too. Multi-manager funds such as Millennium run "pods," small teams each with their own capital (reported, eFinancialCareers, September 2026), while HRT says it is "not a 'pod' system where trading teams are siloed with IP barriers" (official).

What this means for you

Before an interview, find out which model your specific team runs. Useful questions:

1. What is the holding period? It tells you whether latency, signal research or portfolio construction matters most.
2. How fast is feedback? Daily P&L on a market-making desk feels very different from a signal that needs a year to judge.
3. Who owns the P&L? A pod, a central book, or a trading team that shares code across the firm?
4. How does research reach production? Peer review, paper trading, gradual capital allocation?

Then prepare for the matching interview: market makers test speed and pricing under uncertainty, while stat arb and macro shops test statistics and research judgment. The D. E. Shaw guide is a useful contrast to the Optiver one.

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