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Happiness sentiments and the prediction of cross-border country exchange-traded fund returns

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  • Lee, Chien-Chiang
  • Chen, Mei-Ping
Abstract
This research examines whether social media (Twitter) happiness sentiment and country-level happiness sentiment indices predict cross-border ETF returns. To account for complicated associations between happiness sentiment and ETF returns, we use a quantile regression approach and find that Twitter and trading market (U.S.) happiness sentiments are strong predictors of future ETF returns, for which both have far greater predictive power than those of their home countries. Home country happiness indices exhibit asymmetric impacts across quantiles, suggesting the importance of trading country (U.S.) and Twitter happiness sentiments. Higher U.S. and home countries’ freedom to make life choices, absence of corruption perception, and confidence in national government precede higher ETF returns, while U.S. GDP, social support, health life expectancy, positive affect, and negative affect precede lower (abnormal) returns. We find that higher return quantile country ETFs provide a safe haven for U.S. investors during a U.S. bear market.

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  • Lee, Chien-Chiang & Chen, Mei-Ping, 2020. "Happiness sentiments and the prediction of cross-border country exchange-traded fund returns," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    • Handle: RePEc:eee:ecofin:v:54:y:2020:i:c:s1062940820301510
    DOI: 10.1016/j.najef.2020.101254
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    More about this item

    Keywords

    Happiness sentiment; Twitter happiness; Exchange-traded funds (ETFs); Country happiness; Quantile regression;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G40 - Financial Economics - - Behavioral Finance - - - General

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