{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,25]],"date-time":"2026-10-25T14:34:35Z","timestamp":1792938875720,"version":"4.5.0"},"posted":{"date-parts":[[2026]]},"group-title":"SSRN","reference-count":24,"publisher":"Elsevier BV","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>We observe that small-sample bias can significantly affect both constant volatility (CV) model estimates and sample Campbell-Shiller (CS) regression coefficients and that, to a large extent, the reported consistency between the two is driven mechanically by the \"built-in\" VAR\/OLS estimate of the mean reversion matrix in the CS regression. We also find that, when CV models are fitted to yields generated by a stochastic volatility model, there is substantial bias in model-implied CS regression coefficients.<\/jats:p>","DOI":"10.2139\/ssrn.7168358","type":"posted-content","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T17:33:01Z","timestamp":1784827981000},"source":"Crossref","is-referenced-by-count":0,"title":["Does the slope of the yield curve actually predict Treasury returns?"],"prefix":"10.2139","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3546-4916","authenticated-orcid":true,"given":"Andrea","family":"Berardi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen M.","family":"Schaefer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.jfineco.2013.04.009","article-title":"Pricing the term structure with linear regressions","volume":"110","author":"T Adrian","year":"2013","journal-title":"Journal of Financial Economics"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1111\/j.1540-6261.2009.01546.x","article-title":"Do bonds span volatility risk in the U.S. Treasury market? 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