{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T17:38:08Z","timestamp":1792517888756,"version":"4.5.0"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":0,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.uspto.gov\/ip-policy\/copyright-policy\/copyright-basics"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>We decompose variation in stock return predictions into aleatoric and epistemic uncertainty using a probabilistic machine learning framework. Aleatoric uncertainty reflects variability in outcomes among similar observations, and epistemic uncertainty captures limited knowledge of the underlying return-generating process. Utilizing U.S. stocks from 2001 to 2022, we find that aleatoric uncertainty is closely related to return volatility, while epistemic uncertainty is associated with weaker profitability. Both measures are associated with larger earnings-announcement price movements but weaker responses to earnings surprises. Furthermore, higher levels of aleatoric and epistemic uncertainty are associated with increased turnover, potentially reflecting a greater need for portfolio adjustments as new information arrives, and lower next-month returns. Firms with higher epistemic uncertainty continue to underperform over longer horizons after accounting for delistings. Overall, our study proposes new ML-based measures of stock return uncertainty and highlights the distinct economic implications of the two proposed measures.<\/jats:p>","DOI":"10.2139\/ssrn.7636078","type":"posted-content","created":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T16:38:20Z","timestamp":1792514300000},"source":"Crossref","is-referenced-by-count":0,"title":["The Anatomy of Uncertainty in Return Prediction"],"prefix":"10.2139","author":[{"given":"Sai","family":"Palepu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengyu","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","container-title":[],"original-title":[],"deposited":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T16:38:20Z","timestamp":1792514300000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ssrn.com\/abstract=7636078"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":0,"URL":"https:\/\/doi.org\/10.2139\/ssrn.7636078","relation":{},"subject":[],"published":{"date-parts":[[2026]]},"subtype":"preprint"}}