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Technology shocks and stock returns: A long-term perspective

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  • Sharma, Susan Sunila
  • Narayan, Paresh Kumar

Abstract

Using patent data dating as far back as 1870, we compute local and global technology shocks. United States data reveal strong evidence of in-sample predictability particularly at longer horizons and during economic expansions, principally driven by global technology factors. We also discover strong evidence of time-varying predictability for the United States. We find that the global technology shock is a stronger time-varying predictor of stock returns, predicting returns in as many as 41% of sub-samples of data. Using OECD data for 11 countries, we find evidence of time-varying return predictability for seven countries; however, in-sample and long horizon predictability are, in general, weak.

Suggested Citation

  • Sharma, Susan Sunila & Narayan, Paresh Kumar, 2022. "Technology shocks and stock returns: A long-term perspective," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 67-83.
    • Handle: RePEc:eee:empfin:v:68:y:2022:i:c:p:67-83
    DOI: 10.1016/j.jempfin.2022.06.002
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    4. Jo, Karam, 2023. "The role of digital technology in climate technology innovation," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 45(2), pages 21-50.

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