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Out‐of‐sample stock return predictability in emerging markets
Author(s) -
Bahrami Afsaneh,
Shamsuddin Abul,
Uylangco Katherine
Publication year - 2018
Publication title -
accounting and finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.645
H-Index - 49
eISSN - 1467-629X
pISSN - 0810-5391
DOI - 10.1111/acfi.12234
Subject(s) - predictability , econometrics , stock (firearms) , sample (material) , computer science , economics , statistics , mathematics , engineering , mechanical engineering , chemistry , chromatography
This article builds on the widely debated issue of stock return predictability by applying a broad range of predictor variables and comprehensively considering the in‐sample and out‐of‐sample stock return predictability of ten advanced emerging markets. It compares forecasts from models with a single predictor variable, multiple predictor variables and a combination forecast approach. The results confirm the findings of Welch and Goyal (2008) for US data that only a limited number of individual predictor variables are able to deliver significant out‐of‐sample forecasts. However, a combination forecast approach provides statistically and economically significant out‐of‐sample forecast results.