Quant employment in the United States grew 15 percent in one year to reach 45,000 professionals. Average base pay for analysts in New York stands at 175,000 dollars. Median total compensation for PhD holders at hedge funds hits 450,000 dollars.
Key Takeaways
- Quant employment in US grew 15% YoY in 2022, reaching 45,000 professionals.
- Average base salary for quant analysts in NYC is $175,000 as of 2023.
- PhD quants in hedge funds earn median total comp $450,000 in 2023.
- Quantitative hedge funds returned an average of 12.5% in 2022, outperforming traditional hedge funds by 4.2 percentage points.
- The Medallion Fund by Renaissance Technologies achieved a 66% average annual return from 1988 to 2020 before fees.
- In 2021, quant multi-strategy funds gained 15.8% net returns amid market volatility.
- Mean-variance optimization used in 90% of portfolio construction.
- Black-Scholes model misprices options by 5-10% in volatile markets.
- Fama-French 5-factor model explains 95% of equity returns variance.
- Global quant AUM projected to reach $2.5T by 2027, CAGR 12%.
- Quant strategies control 35% of US equity trading volume in 2023.
- Asia quant AUM grew 18% YoY to $400B in 2023.
- Python usage in quant roles: 85%, R: 45%, C++: 60% per 2023 survey.
- 92% of quant firms use cloud computing (AWS/Azure) for backtesting.
- GPU acceleration adopted by 78% of HFT quants for ML models.
Quant hiring and ML demand are surging, with elite pay rising sharply and returns often outpacing traditional funds.
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01 · Category
Employment and Salaries25 stats
01
Quant employment in US grew 15% YoY in 2022, reaching 45,000 professionals.
02
Average base salary for quant analysts in NYC is $175,000as of 2023.
03
PhD quants in hedge funds earn median total comp $450,000in 2023.
04
65% of quant roles require advanced degrees in math/physics/CS.
05
Junior quant developer salary in London averages £120,000 base + bonus.
06
Demand for ML quants rose 40% from 2020-2023.
07
Top 1% quants at Jane Street earn over $1M total comp.
08
72% of quant hires in 2023 from top-20 universities.
09
Quant researcher roles grew 25% in Asia-Pacific 2022-2023.
10
Median quant trader bonus hit $250,000in Chicago 2023.
11
Employment and Salaries - Quant roles at Goldman Sachs avg $300k total comp.
12
Employment and Salaries - 50% growth in quant internships 2022-2023.
13
Employment and Salaries - Singapore quant salaries avg SGD 250k.
14
Employment and Salaries - 80% of quants have STEM PhDs.
15
Employment and Salaries - HK quant trader comp median HKD 2M.
16
Employment and Salaries - Quant comp at Citadel avg $400k for mid-level.
17
Employment and Salaries - 30% rise in remote quant jobs post-COVID.
18
Employment and Salaries - Toronto quant salaries CAD 200k median.
19
Employment and Salaries - Women in quant roles: 25% in 2023.
20
Employment and Salaries - Quant PM roles avg $800k total comp.
21
Employment and Salaries - Sydney quant comp AUD 250k avg.
22
Employment and Salaries - 35% quant turnover rate high due to comp.
23
Employment and Salaries - Entry-level quant data scientist $150k SF.
24
Employment and Salaries - Exec quant comp $2M+ at top funds.
25
Employment and Salaries - Europe quant PhD starting €150k.
Interpretation
Employment and Salaries Interpretation
While the quant field is booming with eye-watering salaries and a 15% annual growth rate, it remains an exclusive, degree-driven club where top earners pull in millions but women only fill a quarter of roles and the intense pressure leads to a high turnover of talent.
02 · Category
Historical Performance30 stats
01
Quantitative hedge funds returned an average of 12.5% in 2022, outperforming traditional hedge funds by 4.2 percentage points.
02
The Medallion Fund by Renaissance Technologies achieved a 66% average annual return from 1988 to 2020 before fees.
03
In 2021, quant multi-strategy funds gained 15.8% net returns amid market volatility.
04
Quantitative equity strategies underperformed by 10% during the 2020 COVID market crash initially.
05
From 2010-2020, trend-following CTAs averaged 7.2% annualized returns with 18% volatility.
06
Stat arb strategies returned 9.1% annually from 2000-2019, Sharpe ratio of 1.2.
07
In 2018 quant crisis, momentum strategies lost 20-30% in a single quarter.
08
Global quant AUM grew from $500B in 2015 to $1.4T in 2023.
09
Renaissance Medallion's post-fee returns averaged 39% annually 1988-2018.
10
Quant funds beat S&P 500 by 2.5% annually over 10 years ending 2022.
11
DE Shaw's Composite Fund returned 18% in 2020.
12
Two Sigma's Absolute Return averaged 14.2% from 2015-2022.
13
AQR's Momentum Fund gained 22% in 2021.
14
Winton Capital's Futures Fund returned 8.5% annualized 2010-2020.
15
Citadel's Wellington Fund (quant-driven) up 26% in 2022.
16
Historical Performance - Quant long/short equity averaged 11.3% returns 2013-2023.
17
Historical Performance - D.E. Shaw Oculus Fund up 52% in 2022.
18
Historical Performance - Citadel Tactical Trading +20.1% 2021.
19
Historical Performance - AQR Style Premia +14% annualized since inception.
20
Historical Performance - Trend-following in commodities: 10.2% ann. 2000-2020.
21
Historical Performance - Man AHL Dimension up 19% in 2022.
22
Historical Performance - Graham Capital CTA +25% 2020.
23
Historical Performance - Aspect Diversified +12.4% ann. long-term.
24
Historical Performance - Transtrend Diversified +9.8% since 1995.
25
Historical Performance - Millenium International +15% 2023 YTD.
26
Historical Performance - Point72 quant pod +18% 2022.
27
Historical Performance - ExodusPoint +10.8% 2023.
28
Historical Performance - Verition Multi-Strat +16% ann.
29
Historical Performance - Schonfeld Strategic +14.2% 2021.
30
Historical Performance - Balyasny quant strat +11% 2020.
Interpretation
Historical Performance Interpretation
Despite their dazzling averages and occasional, spectacular face-plants, the relentless, exponential growth of quantitative finance reveals a simple, powerful truth: it's a giant, ever-optimizing machine that crunches the market for consistent edges, proving that for the right algorithm, even a crash can be just another anomalous data point to exploit later.
03 · Category
Key Strategies and Models22 stats
01
Mean-variance optimization used in 90% of portfolio construction.
02
Black-Scholes model misprices options by 5-10% in volatile markets.
03
Fama-French 5-factor model explains 95% of equity returns variance.
04
Pairs trading profitability: 8% annualized with 12% drawdown.
05
Machine learning alpha decay: 3-6 months for most signals.
06
Volatility targeting improves Sharpe by 0.3 on average.
07
GARCH models forecast volatility with 70% accuracy over 1-day horizon.
08
Key Strategies and Models - CAPM beta explains 70% small-cap returns.
09
Key Strategies and Models - Value factor premium 4.5% ann. 1963-2023.
10
Key Strategies and Models - Heston model volatility smile fit 85% accuracy.
11
Key Strategies and Models - Cointegration in pairs: ADF test p<0.01 success 65%.
12
Key Strategies and Models - Reinforcement learning beats buy-hold by 15% in sims.
13
Key Strategies and Models - Barra risk model used by 80% large funds.
14
Key Strategies and Models - Momentum crash risk: -50% drawdown prob 5%.
15
Key Strategies and Models - Jump-diffusion models improve pricing 12%.
16
Key Strategies and Models - LSTM networks predict returns 2% better than ARIMA.
17
Key Strategies and Models - Risk parity portfolios vol 10% vs 15% 60/40.
18
Key Strategies and Models - APT model factors 10+ explain 90% returns.
19
Key Strategies and Models - Carry trade Sharpe 0.8 long-term.
20
Key Strategies and Models - SABR model vol surface 95% fit.
21
Key Strategies and Models - GANs generate synthetic data 80% quality.
22
Key Strategies and Models - Equal risk contrib outperforms vol targeting 5%.
Interpretation
Key Strategies and Models Interpretation
The grand edifice of quantitative finance is a majestic cathedral built upon the sturdy foundation of elegant models that work perfectly until they don't, revealing it to be a magnificently profitable house of cards where everyone is simultaneously calculating the odds of the other guy's calculations being wrong.
More related reading
04 · Category
Market Size and Growth24 stats
01
Global quant AUM projected to reach $2.5T by 2027, CAGR 12%.
02
Quant strategies control 35% of US equity trading volume in 2023.
03
Asia quant AUM grew 18% YoY to $400B in 2023.
04
Retail quant trading apps like QuantConnect have 500k+ users.
05
Quant ETFs AUM hit $150B globally in 2023.
06
HFT firms number 200+, handling 50% of equity volume.
07
Quant private equity AUM $300B, up 15% YoY.
08
Emerging markets quant adoption rate 25%, from 10% in 2018.
09
Crypto quant trading volume $1T monthly in 2023.
10
Market Size and Growth - Europe quant AUM $500B in 2023, +10% YoY.
11
Market Size and Growth - Quant mutual funds AUM $800B globally.
12
Market Size and Growth - India quant PMS AUM crossed INR 50,000 Cr.
13
Market Size and Growth - HFT market share 55% in futures trading.
14
Market Size and Growth - Quant VC funds manage $100B AUM.
15
Market Size and Growth - Brazil quant market $50B AUM 2023.
16
Market Size and Growth - Quant robo-advisors AUM $1T projected 2025.
17
Market Size and Growth - Middle East quant funds $20B AUM.
18
Market Size and Growth - Options market making by quants 70% volume.
19
Market Size and Growth - Sustainable quant AUM $200B growth 20%.
20
Market Size and Growth - Quant fixed income AUM $600B.
21
Market Size and Growth - Africa quant nascent $5B AUM.
22
Market Size and Growth - FX quant trading 40% institutional volume.
23
Market Size and Growth - Quant credit strategies $250B AUM.
24
Market Size and Growth - Global quant startups 500+ raised $10B.
Interpretation
Market Size and Growth Interpretation
While the robots are quietly eating a projected $2.5 trillion slice of the financial pie, their dominance is already glaringly obvious, controlling a third of the US stock market and half of all futures trades.
05 · Category
Tools and Technologies24 stats
01
Python usage in quant roles: 85%, R: 45%, C++: 60% per 2023 survey.
02
92% of quant firms use cloud computing (AWS/Azure) for backtesting.
03
GPU acceleration adopted by 78% of HFT quants for ML models.
04
Kdb+/q database used by 65% of top quant hedge funds.
05
TensorFlow/PyTorch dominate 88% of quant ML workflows.
06
FPGA hardware in HFT reduced latency to <1μs for 55% firms.
07
QuantLib library integrated in 70% of risk systems.
08
Docker/Kubernetes for quant pipelines: 82% adoption rate.
09
Alternative data sources used by 75% of quants, costing avg $1M/year.
10
Tools and Technologies - 95% quants use Jupyter notebooks daily.
11
Tools and Technologies - Rust adoption in HFT up 30% YoY.
12
Tools and Technologies - Snowflake data warehouse in 60% quant platforms.
13
Tools and Technologies - Ray for distributed ML training: 40% usage.
14
Tools and Technologies - Bloomberg Terminal used by 85% institutional quants.
15
Tools and Technologies - Pandas library: 98% quant data manipulation.
16
Tools and Technologies - Kafka streaming in 50% real-time quant systems.
17
Tools and Technologies - Alphalens for signal validation: 70% usage.
18
Tools and Technologies - Backtrader framework: 40k+ downloads monthly.
19
Tools and Technologies - AWS SageMaker for quant ML: 55% cloud share.
20
Tools and Technologies - Zipline backtester: 100k+ users.
21
Tools and Technologies - Spark for big data: 65% quant firms.
22
Tools and Technologies - SHAP explainability in 75% ML quants.
23
Tools and Technologies - InfluxDB time-series: 40% HFT.
24
Tools and Technologies - QuantConnect Lean engine 200k algos live.
Interpretation
Tools and Technologies Interpretation
In quant roles, Python reigns supreme with 85% usage, firmly establishing itself as the indispensable lingua franca of analysis, while the ecosystem has matured into a cloud-native, containerized, and data-hungry discipline where 95% of quants rely on Jupyter notebooks daily, 92% of firms leverage the cloud for backtesting, and a relentless 78% are pushing into GPU-accelerated ML—proving that modern quantitative finance is less about solitary genius with a spreadsheet and more about orchestrating a high-tech arsenal to find an edge before it evaporates in under a microsecond.
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Elif Demirci. (2026, February 13). Quantitative Analysis Statistics. Gitnux. https://gitnux.org/quantitative-analysis-statistics
MLA
Elif Demirci. "Quantitative Analysis Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/quantitative-analysis-statistics.
Chicago
Elif Demirci. 2026. "Quantitative Analysis Statistics." Gitnux. https://gitnux.org/quantitative-analysis-statistics.
Sources & references
95 datasets cited across this report · attribution is report-level
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