The Timing of Initial Public Offerings - Non-Numerical Model Based on Qualitative Trends

Abstract

The objective of this study is to develop a qualitative model supporting chief financial officers (CFOs) while considering the timing of initial public offerings (IPOs) under conditions of underdeveloped capital markets, where decision making is often made under information shortage. A lack of adequate statistical data in connection with turbulently changing environment suggests that additional research is needed to develop new IPO timing models based not only on statistical analyses. We used a qualitative research approach based on trends, which are increasing, constant or decreasing. Firstly, we identified key variables influencing IPO timing, which have sufficient support in the relevant IPO academic literature, e.g. GDP growth rates, level of compliance, stock market returns, etc. Next, a qualitative model working with 9 variables was developed. The result is represented by 19 scenarios and their qualitative solutions. The transitional graph represents all possible transitions among the 19 scenarios. The main message of the findings presented is what scenarios can occur and what actions might be implemented by CFOs in order to increase the chances of IPO success. We believe that our findings provide valuable implications for local issuers, investment bankers, stock exchanges and macroeconomic policy makers.The objective of this study is to develop a qualitative model supporting chief financial officers (CFOs) while considering the timing of initial public offerings (IPOs) under conditions of underdeveloped capital markets, where decision making is often made under information shortage. A lack of adequate statistical data in connection with turbulently changing environment suggests that additional research is needed to develop new IPO timing models based not only on statistical analyses. We used a qualitative research approach based on trends, which are increasing, constant or decreasing. Firstly, we identified key variables influencing IPO timing, which have sufficient support in the relevant IPO academic literature, e.g. GDP growth rates, level of compliance, stock market returns, etc. Next, a qualitative model working with 9 variables was developed. The result is represented by 19 scenarios and their qualitative solutions. The transitional graph represents all possible transitions among the 19 scenarios. The main message of the findings presented is what scenarios can occur and what actions might be implemented by CFOs in order to increase the chances of IPO success. We believe that our findings provide valuable implications for local issuers, investment bankers, stock exchanges and macroeconomic policy makers.