{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T09:23:54Z","timestamp":1790241834286,"version":"4.1.0"},"reference-count":38,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2020,9,15]],"date-time":"2020-09-15T00:00:00Z","timestamp":1600128000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J of Applied Econometrics"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:title>Summary<\/jats:title><jats:p>We propose new real\u2010time monitoring procedures for the emergence of end\u2010of\u2010sample predictive regimes using sequential implementations of standard (heteroskedasticity\u2010robust) regression <jats:italic>t<\/jats:italic>\u2010statistics for predictability applied over relatively short time periods. The procedures we develop can also be used for detecting historical regimes of temporary predictability. Our proposed methods are robust to both the degree of persistence and endogeneity of the regressors in the predictive regression and to certain forms of heteroskedasticity in the shocks. We discuss how the monitoring procedures can be designed such that their false positive rate can be set by the practitioner at the start of the monitoring period using detection rules based on information obtained from the data in a training period. We use these new monitoring procedures to investigate the presence of regime changes in the predictability of the US equity premium at the 1\u2010month horizon by traditional macroeconomic and financial variables, and by binary technical analysis indicators. Our results suggest that the 1\u2010month\u2010ahead equity premium has <jats:italic>temporarily<\/jats:italic> been predictable, displaying so\u2010called \u201cpockets of predictability,\u201d and that these episodes of predictability could have been detected in real time by practitioners using our proposed methodology.<\/jats:p>","DOI":"10.1002\/jae.2794","type":"journal-article","created":{"date-parts":[[2020,7,6]],"date-time":"2020-07-06T18:39:10Z","timestamp":1594060750000},"page":"45-70","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Real\u2010time detection of regimes of predictability in the US equity premium"],"prefix":"10.1002","volume":"36","author":[{"given":"David I.","family":"Harvey","sequence":"first","affiliation":[{"name":"School of Economics University of Nottingham  Nottingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen J.","family":"Leybourne","sequence":"additional","affiliation":[{"name":"School of Economics University of Nottingham  Nottingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Sollis","sequence":"additional","affiliation":[{"name":"Newcastle University Business School  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A.M. 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