시공간적 허딩 정보가 내생적 IPO 타이밍, 초기 수익률과 상장물량에 미치는 영향: 시장 정보에 대한 순차적 시공간 윈도윙

This study investigates the herding patterns of IPO companies listed on Chinese listed exchanges from 2010 to 2020, and presents a new herding research methodology and measures. Clusters in herding patterns of IPO firms are studied and identified using expectation maximization (EM) for the firms in the close range both in space and in time. Using the new market herding measures, market information, cluster and firm specific information, we have analyzed their effects on their market timing, offer price and volume, and market returns in the initial and long-term secondary markets. The results are summarized as follows. First, the IPO waiting period of firms have a positive effect on IPO offer price and quantity of shares, while guaranteeing strong demand from investors. Second, spatio-temporal herding information has a positive effect on the waiting period of IPO firms. This implies that herding with firms close in time and distance between firms provides opportunity for higher offer price and more shares to sell by controlling the listing to make best use of temporal and spatial herding. Third, spatio-temporal herding information has a negative effect on IPO offer prices, initial returns, and long-term abnormal returns, implying that IPO firms in hot herding markets close in distance and time can enjoy both higher offer price for themselves and higher returns for their IPO investors, leading to more severe winners’ curse for the long-term investors who invest immediately after listing.