IPO Performance in Short- and Long-Run
This project investigates the underpricing phenomenon of initial public offering (IPO) both in the short- and long-run. The project uses a variety of empirical methods used in IPO research. Following are the
detail of this project:
- Importing different files from Excel
- Reshaping the data to a long format
- Merging different datasets
- Finding summary statistics of the variables
- Outliers are detected and winsorized
- To investigate the short-run performance of IPOs, we find first-day returns and market-adjusted returns
- And to investigate the long-run performance of IPOs, we find and test the following:
- Cumulative Abnormal returns (CARs)
- Buy and Hold Returns over a 36 month period or until the firm is delisted.
- Testing the above returns for statistical significance using ttests
- Further, returns are adjusted for risk factors using CAPM, Fama and French 3 Factor model, etc.
Our Stata Code
We have developed easy to use yet robust codes for the above steps. The codes need just a basic understanding of Stata. Further, our comments on each line of code make the code easy to run and understand. We normally share all Stata files, the raw data files, the final files that result from the completed project, and Stata codes with comments. The purpose is to help researchers to learn and apply these codes on their own. We also try to answer questions that might arise when the researcher applies these codes.
The code is available for $199 with some example data. The Fama and French factors are downloaded from Fama and French library. Incase the Fama and French Factors need to be developed from scratch, there is an additional fee of $100. Payment can be made using any of the following methods.
Wise bank transfer (preferred due to low transaction costs).
Any major crypto currency
For further details, please contact us at:
See our full list of completed projects
Project tags: Initial Public offerings, IPO, Fama and French, BHAR, CAR, cumulative abnormal returns, market-adjusted returns, event study, Stata, FinTechprofessor