Meta-Analysis in Finance Research: Opportunities, Challenges, and Contemporary Applications

Abstract

The number of empirical research studies in finance exhibits a strong upward trajectory, producing large differences in empirical results, which often 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 previous empirical findings. 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, like 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 its recent applications, as well as to discuss related challenges and limitations. Thereby, we aim at increasing the awareness and acceptance of meta-analysis in finance and stimulating its future application in the field.

Keywords: meta-analysis, meta-regression, synthesis, publication bias, financial economics

JEL Classification: G00, C83