This study analyses the impact of initial return, post-issue liquidity, and third-party certification on downside risk of initial public offerings (IPOs). Downside risk, measured by value-at-risk (VaR) and conditional value-at-risk… Click to show full abstract
This study analyses the impact of initial return, post-issue liquidity, and third-party certification on downside risk of initial public offerings (IPOs). Downside risk, measured by value-at-risk (VaR) and conditional value-at-risk (CVaR), draws upon Extreme Value Theory (EVT) and the Peak over Threshold (POT) approach. Initial return and downside risk exhibit a positive association which is consistent with a market-overreaction explanation but contradicts the validity of signalling models in which underpricing acts as a costly and difficult to imitate signal of firm quality. Post-issue liquidity, measured by seven distinct definitions to capture different aspects of liquidity, also has a positive association with downside risk. In contrast, third-party certification, measured by the reputation and size of underwriter syndicate and venture capital-backed IPOs do not persistently explain the variation in downside risk. Quantile regression analysis constitutes more rigour in the testing and offers new insights into the sensitivity among variables and their covariates at different quantiles of downside risk. While initial return affects downside risk evenly across the entire distribution, quantile covariates for liquidity measures are statistically significant and generally outside the confidence interval of least squares regression coefficients. Sensitivity of liquidity measures is greater towards the upper end of the downside risk distribution.
               
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