EVALUATION OF SHORT-RUN MARKET PERFORMANCE AND ITS DETERMINANTS USING BINARY MODELS: EVIDENCE FROM AUSTRALIAN IPOS

Abstract

To determine whether Australian initial public offerings (IPOs) underprice in the short run, and to identify their determinants, this study investigated the short-run market performance of 254 IPOs listed during 2006 to 2011 by industry and year (listing and issue). To measure their short-run performance, the first listing day returns were divided into the primary market, the secondary market, and the total market. The investigation was then extended to a post-day listing analysis that included returns of up to nine trading days. To identify the determinants of short-run market performance, this study estimated binary regression models with offer, firm and market characteristics. Marginal probability analysis was also carried out to estimate the associated probability of each determinant that indicated a directional change in market performance. The study found that, overall, the Australian IPOs underpriced by 25.47% and 23.11% based on the market-adjusted average abnormal return (AAR) in the primary and total market respectively. However, the secondary market analysis indicated that the Australian IPOs overpriced by 1.55% based on the AAR. The examination of post-listing returns showed that the Australian IPOs underpriced based on the average cumulative abnormal return (CAR), and this signals that investors’ wealth can be diluted in the long run. The overall results varied by industry and year. The IPO period, time to listing, LISDs, total net proceeds ratio and market volatility were the main determinants for the observed short-run performance. Marginal probability analysis also indicated that the market volatility and total net proceeds ratio had a significant effect on the directional changes of the short-run performance. The findings support Rock’s hypothesis and the uncertainty hypothesis.

Keywords: Australian IPOs, underpricing, binary models, marginal probability analysis

For full Paper: fmscresearch@sjp.ac.lk