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Meta-analysis in finance research: Opportunities, challenges, and contemporary applications

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  • Geyer-Klingeberg, Jerome
  • Hang, Markus
  • Rathgeber, Andreas

Abstract

The number of empirical research studies in finance exhibits a strong upward trajectory, which often produces large differences in empirical results and impedes the drawing of consistent conclusions in relation to the phenomenon under examination. This creates demand for methods like meta-analysis that objectively consolidate and evaluate the empricial literature in a research field. Meta-analysis is a group of statistical methods to aggregate prior empirical studies, to discover and explain consistencies as well as inconsistencies within reported results, and to detect and filter out distorting effects from publication selection or model misspecification. While meta-analysis is a standard tool for research synthesis and evidence-based decisions in many related research disciplines, such as management, marketing, or economics, it has been rarely applied in finance. The goal of this article is to provide a comprehensive overview and discussion of the opportunities of meta-analytical research in finance, to present recent applications of meta-analysis in finance, as well as to discuss related challenges and limitations. Thereby, we aim at increasing the awareness and acceptance of meta-analysis and stimulating its future application in the finance field.

Suggested Citation

  • Geyer-Klingeberg, Jerome & Hang, Markus & Rathgeber, Andreas, 2020. "Meta-analysis in finance research: Opportunities, challenges, and contemporary applications," International Review of Financial Analysis, Elsevier, vol. 71(C).
  • Handle: RePEc:eee:finana:v:71:y:2020:i:c:s105752192030168x
    DOI: 10.1016/j.irfa.2020.101524
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    More about this item

    Keywords

    Meta-analysis; Reviews; Synthesis; Publication bias; Financial economics;
    All these keywords.

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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