Are financial returns really predictable out-of-sample?: Evidence from a new bootstrap test
Li Liu,
Ruijun Bu,
Zhiyuan Pan and
Xu Yuhua
Economic Modelling, 2019, vol. 81, issue C, 124-135
Abstract:
Testing the out-of-sample return predictability is of great interest among academics. A wide range of studies have shown the predictability of stock returns, but fail to test the statistical significance of economic gains from the predictability. In this paper, we develop a new statistical test for the directional accuracy of stock returns. Monte Carlo experiments reveal that our bootstrap-based tests have more correct size and better power than the existing tests. We use the forecast combinations and find that the stock return predictability is statistically significant in terms of reduction of mean squared predictive error relative to the benchmark of historical average forecasts. However, the results from our tests show that the predictability is not economically significant. We conclude that there will be still a long way to go for forecasting stock returns for market participants.
Keywords: Mean predictability; Block bootstrap; Stock returns; S&P 500 index (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:81:y:2019:i:c:p:124-135
DOI: 10.1016/j.econmod.2018.12.014
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