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How Google Trends can improve market predictions— the case of the Warsaw Stock Exchange

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  • Kropiński Paweł

    (Department of Operations Research and Mathematical Economics, Poznań University of Economics and Business, al. Niepodległości 10, 61-875 Poznań, Poland)

  • Anholcer Marcin

    (Department of Operations Research and Mathematical Economics, Poznań University of Economics and Business, al. Niepodległości 10, 61-875 Poznań, Poland)

Abstract

The aim of this paper is to investigate interdependencies between the WIG20 index and economic policy uncertainty (EPU) related keywords quantified by a Google Trends search index. Tests for two periods from January 2015 till December 2019 and from June 2016 till May 2021 have been performed. This allowed the period of relative stability from the time of economic shock caused by the COVID-19 pandemics followed by various restrictions imposed by the governments to be distinguished. A bivariate VAR model to selected search terms and the value of the WIG20 index was applied. After using AIC to establish the optimal number of lags the Granger causality test was performed. The increased empirical relationship has been confirmed between twelve EPU related terms and changes in the WIG20 index in the second period versus six terms for the pre-COVID period. It was also found that in the post-COVID period the intensity of reverse relations increased.

Suggested Citation

  • Kropiński Paweł & Anholcer Marcin, 2022. "How Google Trends can improve market predictions— the case of the Warsaw Stock Exchange," Economics and Business Review, Sciendo, vol. 8(2), pages 7-28, July.
    • Handle: RePEc:vrs:ecobur:v:8:y:2022:i:2:p:7-28:n:5
    DOI: 10.18559/ebr.2022.2.2
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    References listed on IDEAS

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    1. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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