About

Robert F. Engle is a Professor Emeritus of Finance at NYU Stern and the Co-Director of the Volatility and Risk Institute. He was awarded the 2003 Nobel Prize in Economics for his research on autoregressive conditional heteroskedasticity (ARCH), a method for statistical modeling of time-varying volatility that accurately captures properties of many time series. His work has significantly advanced the analysis of financial markets, with his ARCH model and its generalizations becoming essential tools for researchers and market analysts in asset pricing and portfolio risk evaluation. Engle has also developed innovative statistical methods such as cointegration, autoregressive conditional duration (ACD), CAViaR, and dynamic conditional correlation (DCC) models. His academic background includes a B.A. in Physics from Williams College, an M.S. in Physics, and a Ph.D. in Economics from Cornell University. Throughout his career, he has held positions at the University of California, San Diego, and MIT, and has been recognized with numerous awards and appointments, including membership in the World Economic Forum and the International Advisory Panel of the Risk Management Institute.

Research topics

• Machine Learning
• Computer Science
• Algorithm
• Econometrics
• Actuarial science
• Engineering
• Environmental science
• Mathematics
• Statistics
• Environmental planning
• Business
• Mathematical optimization
• Risk analysis (engineering)

Selected publications

• CRISK: Measuring the climate risk exposure of the financial system

  Journal of Financial Economics · 2025-05-27 · 45 citations

  article
  PublisherDOI

• Factor Modeling for Volatility

  SSRN Electronic Journal · 2024-01-01 · 1 citations

  preprintOpen access
  PublisherDOI

• Measuring the Climate Risk Exposure of Insurers

  SSRN Electronic Journal · 2023 · 18 citations

  • Business
  • Risk analysis (engineering)
  • Actuarial science
  PublisherDOI

• Fitting Vast Dimensional Time-Varying Covariance Models

  Journal of Business and Economic Statistics · 2020 · 153 citations

  Senior authorCorresponding
  • Computer Science
  • Computer Science
  • Econometrics

  Estimation of time-varying covariances is a key input in risk management and asset allocation. ARCH-type multivariate models are used widely for this purpose. Estimation of such models is computationally costly and parameter estimates are meaningfully biased when applied to a moderately large number of assets. Here, we propose a novel estimation approach that suffers from neither of these issues, even when the number of assets is in the hundreds. The theory of this new method is developed in some detail. The performance of the proposed method is investigated using extensive simulation studies and empirical examples. Supplementary materials for this article are available online.

  PublisherDOI

• SRISK_all_countries_monthly.tab

  Harvard Dataverse · 2019-01-01

  datasetOpen access1st authorCorresponding

  :unav

  PublisherDOI

• tobit_estimation_sample.txt

  Harvard Dataverse · 2019-01-01

  datasetOpen access1st authorCorresponding

  :unav

  PublisherDOI

• measures_RR_countries.txt

  Harvard Dataverse · 2019-01-01

  datasetOpen access1st authorCorresponding

  :unav

  PublisherDOI

• README.pdf

  Harvard Dataverse · 2019-01-01

  datasetOpen access1st authorCorresponding

  :unav

  PublisherDOI

• tobit_estimates.do

  Harvard Dataverse · 2019-01-01

  datasetOpen access1st authorCorresponding

  :unav

  PublisherDOI

• Liquidity, Volatility, and Flights to Safety in the U.S. Treasury Market: Evidence from a New Class of Dynamic Order Book Models

  SSRN Electronic Journal · 2012-01-01 · 47 citations

  articleOpen access1st authorCorresponding
  PublisherDOI

Frequent coauthors

• Éric Ghysels

  8 shared

• Kevin Sheppard

  7 shared

• Victor Ng

  College of Family Physicians of Canada

  5 shared

• Neil Shephard

  Harvard University

  5 shared

• Tianyue Ruan

  National University of Singapore

  5 shared

• Yingying Li

  Peng Huanwu Center for Fundamental Theory

  4 shared

• Xinghua Zheng

  University of Chinese Academy of Sciences

  4 shared

• Giang Nguyen

  2 shared

Awards & honors

• Distinguished Alumni Award, Cornell University, Department o…
• Financial Engineer of the Year Award, IAFE/SunGard (2011)
• Distinguished Visiting Scholar, UNC Chapel Hill Kenan-Flagle…
• Presidential Medal, Hofstra University (2009)
• Member, World Economic Forum (2007)