{"id":{"repo_id":"ubc","oai_identifier":"oai:circle.library.ubc.ca:2429/2276"},"canonical_url":"https://search.dev.ndltd.org/etd/ubc/oai:circle.library.ubc.ca:2429/2276","repository":{"repo_id":"ubc","name":"University of British Columbia","base_url":"http://circle.library.ubc.ca/oai/request"},"display":{"title":"Forecasting value-weighted real returns of TSE portfolios using dividend yields","abstract":"We assess the ability of dividend yields denoted by DYt, to forecast value-weighted real returns, denoted by Rt ,T of Toronto Stock Exchange (TSE) portfolios for following return horizons, T: monthly, quarterly, and one to four year. Fama and French [4] applied similar methods to the New York Stock Exchange and found the forecast power increases as the return horizon increases. We find that the Fama and French methods generalize to TSE portfolios, however, it does not apply to all portfolios. We also determine that the Fama and French approach may not lie on solid statistical ground, in that the residual variance is not time invariant. With these drawbacks in mind we consider using the methods of Dynamic Linear Models as discussed in West and Harrison [13], which allow the model parameters to be time varying. We conclude that for the majority of the portfolios, the two methods agree, however, the regression DLM approach does slightly better in comparison with the methods of Fama and French in terms of standarized forecast errors.","abstract_html":"We assess the ability of dividend yields denoted by DYt, to forecast value-weighted real returns, denoted by Rt ,T of Toronto Stock Exchange (TSE) portfolios for following return horizons, T: monthly, quarterly, and one to four year. Fama and French [4] applied similar methods to the New York Stock Exchange and found the forecast power increases as the return horizon increases. We find that the Fama and French methods generalize to TSE portfolios, however, it does not apply to all portfolios. We also determine that the Fama and French approach may not lie on solid statistical ground, in that the residual variance is not time invariant. With these drawbacks in mind we consider using the methods of Dynamic Linear Models as discussed in West and Harrison [13], which allow the model parameters to be time varying. We conclude that for the majority of the portfolios, the two methods agree, however, the regression DLM approach does slightly better in comparison with the methods of Fama and French in terms of standarized forecast errors.","abstract_has_math":false,"creators":["Blanchard, Joseph W."],"institution":"University of British Columbia","degree_name":"Master of Science - MSc","degree_level":"master's","degree_discipline":"Statistics","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1993,"date_issued":"1993","date_published":"1993","updated_at":"2026-07-24T05:07:21Z","subjects":[],"languages":["eng"],"rights":["For non-commercial purposes only, such as research, private study and education. 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We also determine that the Fama and French approach may not lie on solid statistical ground, in that the residual variance is not time invariant. With these drawbacks in mind we consider using the methods of Dynamic Linear Models as discussed in West and Harrison [13], which allow the model parameters to be time varying. We conclude that for the majority of the portfolios, the two methods agree, however, the regression DLM approach does slightly better in comparison with the methods of Fama and French in terms of standarized forecast errors."]},{"key":"dc:format","label":"Dc Format","values":["4286878","application/pdf"]},{"key":"dc:title","label":"Title","values":["Forecasting value-weighted real returns of TSE portfolios using dividend yields"]}]}],"canonical_facts":{"dc:creator":["Blanchard, Joseph W."],"dc:date":["1993"],"dc:description":["We assess the ability of dividend yields denoted by DYt, to forecast value-weighted real returns, denoted by Rt ,T of Toronto Stock Exchange (TSE) portfolios for following return horizons, T: monthly, quarterly, and one to four year. Fama and French [4] applied similar methods to the New York Stock Exchange and found the forecast power increases as the return horizon increases. We find that the Fama and French methods generalize to TSE portfolios, however, it does not apply to all portfolios. We also determine that the Fama and French approach may not lie on solid statistical ground, in that the residual variance is not time invariant. With these drawbacks in mind we consider using the methods of Dynamic Linear Models as discussed in West and Harrison [13], which allow the model parameters to be time varying. We conclude that for the majority of the portfolios, the two methods agree, however, the regression DLM approach does slightly better in comparison with the methods of Fama and French in terms of standarized forecast errors."],"dc:format":["4286878","application/pdf"],"dc:identifier":["http://hdl.handle.net/2429/2276","http://circle.library.ubc.ca/bitstream/2429/2276/3/ubc_1993_fall_blanchard_wade.pdf"],"dc:language":["eng"],"dc:publisher":["University of British Columbia"],"dc:rights":["For non-commercial purposes only, such as research, private study and education. 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