• Graduate Programs
  • Research
  • Browse our Courses
  • Events
    • Events Calendar
    • Events Archive
    • Summer School
      • Applied Public Policy Evaluation
      • Deep Learning
      • Development Economics
      • Economics of Blockchain and Digital Currencies
      • Economics of Climate Change
      • The Economics of Crime
      • Foundations of Machine Learning with Applications in Python
      • From Preference to Choice: The Economic Theory of Decision-Making
      • Inequalities in Health and Healthcare
      • Marketing Research with Purpose
      • Markets with Frictions
      • Modern Toolbox for Spatial and Functional Data
      • Sustainable Finance
      • Tuition Fees and Payment
      • Business Data Science Summer School Program
    • Tinbergen Institute Lectures
    • 2026 Tinbergen Institute Opening Conference
    • Annual Tinbergen Institute Conference
  • News
  • Summer School
    • Applied Public Policy Evaluation
    • Deep Learning
    • Development Economics
    • Economics of Blockchain and Digital Currencies
    • Economics of Climate Change
    • The Economics of Crime
    • Foundations of Machine Learning with Applications in Python
    • From Preference to Choice: The Economic Theory of Decision-Making
    • Inequalities in Health and Healthcare
    • Marketing Research with Purpose
    • Markets with Frictions
    • Modern Toolbox for Spatial and Functional Data
    • Sustainable Finance
    • Tuition Fees and Payment
  • Alumni

Van Oordt, M.R.C. and Zhou, C. (2016). Systematic tail risk Journal of Financial and Quantitative Analysis, 52(2):685--705.


  • Journal
    Journal of Financial and Quantitative Analysis

We test for the presence of a systematic tail risk premium in the cross section of expected returns by applying a measure of the sensitivity of assets to extreme market downturns, the tail beta. Empirically, historical tail betas help predict the future performance of stocks in extreme market downturns. During a market crash, stocks with historically high tail betas suffer losses that are approximately 2 to 3 times larger than their low-tail-beta counterparts. However, we find no evidence of a premium associated with tail betas. The theoretically additive and empirically persistent tail betas can help assess portfolio tail risks.