A Systematic Literature Review of Price Gaps in Closed-End Funds Using the Meta-Synthesis Method

Over the years, it has been observed that shares of closed-end funds (CEFs) are frequently traded at prices that differ significantly from the total market value of the underlying assets held by these funds, resulting in a gap between the share price and the net asset value (NAV). Despite numerous studies, no single explanation or identified component from traditional or behavioral finance has fully accounted for the price gaps in CEF share trading. This issue remains a significant and longstanding debate between traditional and behavioral finance paradigms. The primary objective of this study is to review existing research on closed-end funds to identify key indicators influencing price gaps in the trading of these funds’ units, from both traditional and behavioral finance perspectives. A deeper understanding of CEF behavior encourages further research into these funds, market efficiency, asset pricing, and the paradigms of traditional and behavioral finance.This study is classified as developmental research and adopts a qualitative research methodology, utilizing a meta-synthesis approach. To achieve the research objectives, 389 studies conducted between 1968 and 2024 were reviewed, with 88 articles meeting the inclusion criteria analyzed using the Sandelowski and Barroso meta-synthesis method. The analysis identified four components comprising 35 indicators, categorized into four dimensions: political factors, economic factors, fund-specific factors, and psychological factors. These components were further classified into two overarching dimensions—traditional (rational) finance and behavioral finance—based on the existing literature. The traditional finance dimension, grounded in the theory of rational investor behavior, attributes price gaps to logical, fundamental reasons and fund-specific characteristics, identifying 25 indicators across three components (political factors, economic factors, and fund-specific factors). Conversely, the behavioral finance dimension, rejecting the assumption of rational investor behavior, posits that investors’ behavioral biases play a critical role in the deviation of fund prices from their NAVs, identifying 10 indicators within one component (psychological factors)