International Stock Return Predictability: Evidence from New Statistical Tests

Amélie Charles (), Olivier Darné and Jae Kim
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Amélie Charles: Audencia Recherche - Audencia Business School

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Abstract: We investigate whether stock returns of international markets are predictable from a range of fundamentals including key financial ratios (dividend-price ratio, dividend-yield, earnings-price ratio, dividend-payout ratio), technical indicators (price pressure, change in volume), and short-term interest rates. We adopt two new alternative testing and estimation methods: the improved augmented regression method and wild bootstrapping of predictive model based on a restricted VAR form. Both methods take explicit account of endogeneity of predictors, providing bias-reduced estimation and improved statistical inference in small samples. From monthly data of 16 Asia-Pacific (including U.S.) and 21 European stock markets from 2000 to 2014, we find that the financial ratios show weak predictive ability with small effect sizes and poor out-of-sample forecasting performances. In contrast, the price pressure and interest rate are found to be strong predictors for stock return with large effect sizes and satisfactory out-of-sample forecasting performance.

Keywords: Augmented regression method; Financial ratios; Forecasting; Technical indicators; Wild bootstrap (search for similar items in EconPapers)
Date: 2017-10
New Economics Papers: this item is included in nep-fmk
Note: View the original document on HAL open archive server: https://audencia.hal.science/hal-01626101
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Citations: View citations in EconPapers (9)

Published in International Review of Financial Analysis, 2017, 54, pp.97-113. ⟨10.1016/j.irfa.2016.06.005⟩

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Journal Article: International stock return predictability: Evidence from new statistical tests (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01626101

DOI: 10.1016/j.irfa.2016.06.005

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