The proxies used in empirical works investigating in short run IPO anomaly to value the investor sentiment and to measure its impact on underpricing anomaly are numerous. One of the most important proxies often used by researchers is the discount on closed-end funds. The choice by many authors of the discount on closed-end funds as a proxy of investor sentiment in their works is based on the findings of Lee et al. (1991).
Lee, Shleifer and Thaler (1991) find that both closed-end funds and small stocks are mostly held by individual investors who tend to be noise traders, suggesting that they are more likely than large stocks to be affected by investor sentiment. Lee et al. find that almost a quarter of the variation in monthly returns on the smallest decile of firms is explained by discount changes, even after controlling for general market movements. Their findings suggest that when investor sentiment is higher, individual investors pay relatively more for closed-end funds, and the discount is smaller.
Lee, Shleifer and Thaler (1991), and Lowry (2002) document that “hot issue” periods and “hot IPO market” characterized by high sentiment and over optimism among individual investors coincide with low discount on closed-end funds, their measure of noise traders’ optimism and sentiment. They also show that the annual number of IPOs is negatively related to the closed-end fund discount which they argue is a measure of retail investor sentiment: the smaller the closed-end funds discount, the higher the sentiment and optimism among individual investors and the higher the number of IPOs. Over optimistic and enthusiastic investors are more accepting to invest in new issues, and companies are encouraged to take advantage of this opportunity to go public and to offer their shares in the stock market.
Based on these findings, many researchers are convinced that discount on closed-end funds is a relevant proxy that can be used to value the investor sentiment and to study its impact on IPO underpricing anomaly that still a puzzle right now. They use it in their econometrical models.
Ivanov and Lewis (2008)(17) try to identify the determinants of market-wide issue cycles for initial public offerings (IPOs) using an autoregressive conditional count model. They consider whether IPO volume is related to business conditions, investor sentiment, and time variation in adverse selection costs caused by asymmetric information between managers and investors.
To value the investor sentiment, they use the quarterly first-difference in the index of closed-end fund discounts as proposed by Lee et al. (1991).
17 “The determinants of market-wide issue cycles for initial public offering” (2008)