Neural network models for initial public offerings

An interpretable neural fuzzy inference system for predictions of underpricing in initial public offerings

“…The first well-known IPO pricing study using neural networks was conducted back in 1995 [23], wherein Jain and Nag closely approximated the pricing of IPOs according to IPO first day closing price. Similarly, Robertson et al [24] and Reber et al [25] also constructed neural network models to predict the post-IPO market price. Alternatively, Yao and Zhou employed rough set theory and support vector machine to identify the most influential factors in Chinese IPOs [26].…”

Prediction of Demand for Primary Bond Offerings Using Artificial Neural Networks

“…The neural network model significantly improved accuracy of prediction and reduced under-pricing costs. Robertson et al (1998) proposed neural networks models in order to estimate the first-day return of an initial public offering. They divided the data set into technology and nontechnology offerings and constructed a regression model and two neural network models.…”

Textual analysis in finance

“…In a similar fashion, Meng (2008) and Chen and Wu (2009) use artificial neural networks to predict the first-day closing price of Chinese IPOs, and by extension, the level of underpricing. Several other studies demonstrate the superiority of artificial neural networks over linear regression models at predicting the mispricing of IPOs (Robertson et al, 1998;Reber et al, 2005).…”