Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation

Detalhes bibliográficos
Autor(a) principal: Faias, José Afonso
Data de Publicação: 2022
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10400.14/38328
Resumo: I provide a new monthly cross-sectional measure of stock market tail risk, SCSTR, defined as the average of the daily cross-sectional tail risk, rather than the tail risk of the pooled daily returns within a month. Through simulations, I find that SCSTR better captures monthly tail risk rather than merely the tail risk on specific days within a month. In an extended period from 1964 until 2018, this difference is important in generating strong in- and out-of-sample predictability and performs better than the historical risk premium and other commonly-used predictors for short- and long-term horizons.
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spelling Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlationEquity premiumPredictionCross-sectionalI provide a new monthly cross-sectional measure of stock market tail risk, SCSTR, defined as the average of the daily cross-sectional tail risk, rather than the tail risk of the pooled daily returns within a month. Through simulations, I find that SCSTR better captures monthly tail risk rather than merely the tail risk on specific days within a month. In an extended period from 1964 until 2018, this difference is important in generating strong in- and out-of-sample predictability and performs better than the historical risk premium and other commonly-used predictors for short- and long-term horizons.VeritatiFaias, José Afonso2022-07-21T12:55:01Z2023-03-012023-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.14/38328eng1386-418110.1016/j.finmar.2022.100769info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-13T13:04:57Zoai:repositorio.ucp.pt:10400.14/38328Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T01:53:36.001517Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation
title Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation
spellingShingle Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation
Faias, José Afonso
Equity premium
Prediction
Cross-sectional
title_short Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation
title_full Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation
title_fullStr Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation
title_full_unstemmed Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation
title_sort Predicting the equity risk premium using the smooth cross-sectional tail risk: the importance of correlation
author Faias, José Afonso
author_facet Faias, José Afonso
author_role author
dc.contributor.none.fl_str_mv Veritati
dc.contributor.author.fl_str_mv Faias, José Afonso
dc.subject.por.fl_str_mv Equity premium
Prediction
Cross-sectional
topic Equity premium
Prediction
Cross-sectional
description I provide a new monthly cross-sectional measure of stock market tail risk, SCSTR, defined as the average of the daily cross-sectional tail risk, rather than the tail risk of the pooled daily returns within a month. Through simulations, I find that SCSTR better captures monthly tail risk rather than merely the tail risk on specific days within a month. In an extended period from 1964 until 2018, this difference is important in generating strong in- and out-of-sample predictability and performs better than the historical risk premium and other commonly-used predictors for short- and long-term horizons.
publishDate 2022
dc.date.none.fl_str_mv 2022-07-21T12:55:01Z
2023-03-01
2023-03-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.14/38328
url http://hdl.handle.net/10400.14/38328
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1386-4181
10.1016/j.finmar.2022.100769
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dc.format.none.fl_str_mv application/pdf
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