PeopleofSuperintelligence

Researcher

Kevin Sheppard

Also known as K Sheppard, Kevin Keith Sheppard, bashtage

Kevin Sheppard is a financial econometrician at the University of Oxford who co-authored the 2020 Nature paper on NumPy, the array library that the scientific Python ecosystem is built on. In 2004, they completed an economics PhD at the University of California, San Diego, and became a University Lecturer at Oxford. With Neil Shephard, Sheppard developed the HEAVY volatility model, which makes low-frequency volatility forecasts from high-frequency data, and their paper won the Richard Stone Prize in Applied Econometrics in 2012. They also maintain the Python packages arch, for volatility models and unit root tests, and linearmodels, for panel data and instrumental-variable estimation. At Oxford's Department of Economics, they are Associate Professor of Financial Economics, with research on volatility and uncertainty.

Badges

Timeline

  1. 2004

    PhD at UC San Diego

    They complete a PhD in economics at the University of California, San Diego, in 2004. They also hold a BS in Mathematics and a BA in Economics from the University of Texas at Austin.

  2. 2004

    Lecturer at Oxford

    In 2004, they become a University Lecturer at the University of Oxford. They are also a Fellow of the Oxford-Man Institute.

  3. 2010

    The HEAVY volatility model

    With Neil Shephard, they develop the high-frequency-based volatility (HEAVY) model, which uses high-frequency data to make low-frequency volatility forecasts. Their paper "Realising the future: forecasting with high frequency based volatility (HEAVY) models" appears in the Journal of Applied Econometrics in 2010.

  4. 2012

    A Richard Stone Prize

    Their HEAVY paper wins the Richard Stone Prize in Applied Econometrics in 2012.

  5. 2012

    Multivariate HEAVY models

    With Diaa Noureldin and Neil Shephard, they publish "Multivariate high-frequency-based volatility (HEAVY) models" in the Journal of Applied Econometrics in 2012. Man Group's AHL derives its spike detection strategy, a component of the TailProtect Fund, from this predictive model.

  6. September 2020

    Co-authoring the NumPy paper

    In September 2020, they are among the authors of "Array programming with NumPy" in Nature. The review presents NumPy as the primary array programming library for Python and the foundation of the scientific Python ecosystem, and notes that the growth of data science, machine learning and artificial intelligence has boosted the scientific use of Python.

  7. 2021

    The arch and linearmodels packages

    In March 2021, they release version 4.18 of arch, a Python toolbox for univariate volatility models, bootstrapping, multiple comparison procedures, unit root tests and cointegration analysis. They also maintain linearmodels, which supplies panel data, system regression and instrumental-variable models missing from statsmodels.

  8. As of October 2026

    Associate Professor at Oxford

    They are Associate Professor of Financial Economics in the Department of Economics at the University of Oxford, affiliated with Keble College. Their research focuses on volatility and uncertainty, including the modelling of conditional correlation, a key input into portfolio risk models.

Career

  1. Since 2004University of OxfordUniversity Lecturer

Education

  1. 2004University of California, San DiegoPhD in Economics
  2. University of Texas at AustinBS in Mathematics and BA in Economics

From the biography.

  1. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Oxford. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  2. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Oxford. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  3. Companies supply the most prior-work hires at 7 of the 9 frontier AI labsIncludes University of Oxford. Our estimates of the organizations where 550 people worked directly before joining 9 frontier AI labs across 620 career transitions, comparing the main feeder organizations per lab.
  4. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes University of Oxford. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorate. Across 2,116 people with both an undergraduate degree and a doctorate recorded, we trace which undergraduate schools feed which doctoral programs, how often students stay at the same school, and how paths differ by birth-country region.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. index | Kevin Sheppard kevinsheppard.com. Checked 21 October 2026.
  2. Kevin Sheppard | IDEAS/RePEc ideas.repec.org. Checked 21 October 2026.
  3. Designing financial instruments to protect against financial stress impact.ref.ac.uk. Checked 21 October 2026.
  4. Array programming with NumPy | Nature nature.com. Checked 21 October 2026.
  5. arch 8.0.0 bashtage.github.io. Checked 21 October 2026.
  6. linearmodels 7.1 bashtage.github.io. Checked 21 October 2026.
  7. Kevin Sheppard | Department of Economics economics.ox.ac.uk. Checked 21 October 2026.