首次公開發行公司 (initial public offerings；IPOs) 期初報酬率的決定因素一直是IPOs研究之重要議題。本文以中國A股股票市場為研究對象，除了一般線性迴歸分析方法外，本文進一步利用分量迴歸 (quantile regression)分析方法來探討個別公司在IPO之前的行銷費用支出，對低、中與高期初報酬率公司的影響情形。OLS的實證結果顯示，公司上市前的行銷費用支出能顯著降低該公司的期初報酬率，此研究結果與Luo (2008)一致；另一方面，本文的分量迴歸結果顯示，對低期初報酬的股票而言，其上市前行銷費用與該公司的期初報酬率的關係顯著為負，即行銷費用能有效解釋低折價股票的期初報酬；但對於中及高折價幅度之股票而言，該公司的上市前行銷費用支出，對中及高期初報酬率之股票與否並無顯著的效果。本文推論：對低期初報酬率的股票而言，行銷活動應有助於提高該公司之透明度，故投資人所要求的風險溢酬應會減少。

Recently, there has been considerable concern with determining underpricing of initial public offerings (IPOs). This study utilizes both OLS and quantile regression model to examine whether pre-listing marketing expenditure reduce IPO underpricing using China A-share IPOs data. Our OLS result shows that firm‘s marketing expenditure could reduce IPO underpricing significantly that was consist with Luo‘s (2008) finding who investigate US IPOs market. With regard to quantile regression results, we find that pre-listing IPO marketing expenditures are significantly associated with lower underpricing for lower-underpricing stocks but with no significant effects for median-, and higher-underpricing stocks. We infer that: for lower-underpricing stocks, the risk premium investors require would be lowered because pre-listing marketing expenditures can help for raising transparency of the firm.

1. Introduction.......................................................................1
2. Literature Review.............................................................6
2.1 IPO Underpricing..........................................................6
2.2 Information Asymmetry...............................................6
2.2.1 Information Asymmetry and Underpricing............6
2.2.2 Information Asymmetry and Marketing..................8
2.3 Quantile Regression...................................................9
2.4 Other Related Literatures.........................................12
3. Model and Methodology...............................................14
3.1 Empirical Model.........................................................14
3.2 Variable Specification...............................................15
4. Data and Sample Description....................................19
5. Results and Analysis...................................................21
5.1 Results of OLS Analysis...........................................22
5.2 Results of Quantile Regression Analysis.............23
5.3 Robustness of Results............................................27
6. Conclusion.....................................................................33
Reference...........................................................................35

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