טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
M.Sc Thesis
M.Sc StudentElkabetz Yaron
SubjectStock Valuation and the Under-Pricing Phenomenon in
Initial Public Offerings
DepartmentDepartment of Industrial Engineering and Management
Supervisor Professor Arie Melnik


Abstract

The empirical research on Initial Public Offerings (IPO's) of equity securities identified four major phenomena. First, there is a significant underpricing in IPO's. That is, the price at the end of the first day of trading is significantly higher than the issuing price. Second, there is an observed cyclicality, both in the number and size of IPO's, and the degree of underpricing. These are the so-called "hot issue market" periods. Third, newly issued stocks yield lower returns to their holders when compared to benchmarks of the stock market as a whole. Fourth, there are a few studies that try to explain the underpricing of IPO's by background information that precedes the date of issue. The last point is the focus of this research.

The basic hypothesis of this thesis is that several factors impact the degree of underpricing. I use four groups of data. The first includes economic information that is contained in the financial reports, The second includes the ownership structure before and after the IPO, The third group includes data about the offering itself that appear in the prospectus, The last group includes the type of industry and the reputation of the underwriter.

  In this thesis I use a linear model, the dependent variable is the recorded price changes on the first day of trading minus the changes in the market index. The empirical results show that the size of underpricing can be predicted by several variables. In particular, it is impacted by the logarithm of total assets, the underwriter spread, the underwriter reputation, the type of industry and the number of days between filing to offer. On the other hand, other important variables that were mentioned in the literature did not produce a significant predictive value.