A Decomposition of Conditional Risk Premia and Implications for Representative Agent Models

• 成果类型: Article
• 署名作者: Chabi-Yo, Fousseni; Loudis, Johnathan A.
• 署名单位: University of Massachusetts System; University of Massachusetts Amherst; University of Notre Dame
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2022.01663
• 发表日期: 2024
• 页码: 6804-6834
• 关键词: market risk premium; Variance risk premium; Crash risk; Risk-neutral moments; preferences; stochastic discount factor

摘要

We develop a methodology to decompose the conditional market risk premium and risk premia on higher-order moments of excess market returns into risk premia related to contingent claims on down, up, and moderate market returns. The decomposition exploits information about the risk-neutral market return distribution embedded in option prices, but does not depend on assumptions about the functional form of investor preferences or about the market return distribution. The total market risk premium is highly time-varying, as are the contributions from downside, upside, and central risk. Time-series variation in risk premia associated with each region is primarily driven by variation in risk prices associated with the probability of entering each region at short horizons, but it is primarily driven by variation in risk quantities at longer horizons. Analogous decompositions implied by prominent representative agent models generally fail to match the dynamic risk premium behavior implied by the data. Our results provide a set of new empirical facts regarding the drivers of conditional risk premia and identify new challenges for representative agent models.