https://www.socictopen.socict.org/files/original/440d7f8177e1b134034cce2cb5f49e63.pdf f172740895fb7bca64073708381d8576 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case Creator An entity primarily responsible for making the resource Michael Scholz, Jens Perch Nielsen, Ioannis Kyriakou, Parastoo Mousavi Description An account of the resource Long-term return expectations or predictions play an important role in planning purposes and guidance of long-term investors. Five-year stock returns are less volatile around their geometric mean than returns of higher frequency, such as one-year returns. One would, therefore, expect models using the latter to better reduce the noise and beat the simple historical mean than models based on the former. However, this paper shows that the general tendency is surprisingly the opposite: long-term forecasts over five years have a similar or even better predictive power when compared to the one-year case. We consider a long list of economic predictors and benchmarks relevant for the long-term investor. Our predictive approach consists of adopting and implementing a fully nonparametric smoother with the covariates and the smoothing parameters chosen by cross-validation. We consistently find that long-term forecasting performs well and recommend drawing more attention to it when designing investment strategies for long-term investors. Furthermore, our preferred predictive model did stand the test of Covid-19 providing a relatively optimistic outlook in March 2020 when uncertainty was all around us with lockdown and facing an unknown new pandemic. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Prediction, benchmark, Cross-validation, stock returns, Long-term forecasts, Overlapping returns Identifier An unambiguous reference to the resource within a given context DOI: 10.3390/math8060927 Source A related resource from which the described resource is derived Mathematics Publisher An entity responsible for making the resource available MDPI AG Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mathematics