Literature DB >> 35814849

Testing the animal spirits theory for ethical investments: further evidence from aggregated and disaggregated data.

Fredj Jawadi1,2, Nabila Jawadi3, Abdoulkarim Idi Cheffou4.   

Abstract

This study aims to test the animal spirits theory by Akerlof and Shiller (Animal spirits - how human psychology drives the economy, and why it matters for global capitalism? Princeton University Press) for ethical stock markets using Islamic and sustainable stock indexes during calm and crisis periods. This question helps determine whether ethical finance is driven more by its specific rules or determined by animal spirits. We used data covering January 1996-September 2021, which includes both calm periods and crisis periods (dot-com bubble of 2000, subprime crisis of 2007, global financial crisis of 2008-2009, and COVID-19 recession). Accordingly, we applied different time series tests, ran a quantile regression, and built an econometric framework to empirically test the animal spirits theory. We provide two key findings. First, investor sentiment and consumer confidence significantly affect the dynamics of both ethical stock returns, suggesting further evidence of animal spirits. This finding supports the assumption that investors' emotions and sentiments affect their behaviors and related feelings, for example, spontaneous instinctive that urge to action than inaction, optimism, and so forth, might help to apprehend some investment actions. Second, and interestingly, animal spirit effects enter asymmetrically and nonlinearly as their effects on ethical stock returns are time-varying and vary with the quantile under consideration.
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.

Entities:  

Keywords:  Animal spirits; Ethical investments; Nonlinearity; Quantile regression

Year:  2022        PMID: 35814849      PMCID: PMC9252570          DOI: 10.1007/s10479-022-04832-y

Source DB:  PubMed          Journal:  Ann Oper Res        ISSN: 0254-5330            Impact factor:   4.820


  1 in total

1.  Past, present, and future of sustainable finance: insights from big data analytics through machine learning of scholarly research.

Authors:  Satish Kumar; Dipasha Sharma; Sandeep Rao; Weng Marc Lim; Sachin Kumar Mangla
Journal:  Ann Oper Res       Date:  2022-01-04       Impact factor: 4.820

  1 in total

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