Prospectus Content as Predictor of IPO Outcome: A topic model approach
(2022) DABN01 20221Department of Statistics
Department of Economics
- Abstract
- It is beneficial for both investors and companies to avoid the detrimental consequences of overpricing during an initial public offering (IPO). Prospectuses are an important source of information for potential investors. Through Latent Dirichlet Allocation (LDA) we extract topics from the summary section of prospectuses S-1 for companies holding an IPO in the U.S. in 2019-2020. We represent the uniqueness of the companies through the topic proportions each document is composed of and use them, together with the initial offering price, to predict the outcome of the IPO. For the best performing model, we obtain an AUC of 0.80. In line with signalling theory, we argue that prospectuses may indeed send signals able to influence potential... (More)
- It is beneficial for both investors and companies to avoid the detrimental consequences of overpricing during an initial public offering (IPO). Prospectuses are an important source of information for potential investors. Through Latent Dirichlet Allocation (LDA) we extract topics from the summary section of prospectuses S-1 for companies holding an IPO in the U.S. in 2019-2020. We represent the uniqueness of the companies through the topic proportions each document is composed of and use them, together with the initial offering price, to predict the outcome of the IPO. For the best performing model, we obtain an AUC of 0.80. In line with signalling theory, we argue that prospectuses may indeed send signals able to influence potential investors. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9083567
- author
- Emidi, Christian LU and Galan, Sebastian LU
- supervisor
- organization
- course
- DABN01 20221
- year
- 2022
- type
- H1 - Master's Degree (One Year)
- subject
- keywords
- initial public offering, overpricing, signalling theory, topic model
- language
- English
- id
- 9083567
- date added to LUP
- 2022-06-08 12:50:49
- date last changed
- 2022-10-10 15:59:18
@misc{9083567, abstract = {{It is beneficial for both investors and companies to avoid the detrimental consequences of overpricing during an initial public offering (IPO). Prospectuses are an important source of information for potential investors. Through Latent Dirichlet Allocation (LDA) we extract topics from the summary section of prospectuses S-1 for companies holding an IPO in the U.S. in 2019-2020. We represent the uniqueness of the companies through the topic proportions each document is composed of and use them, together with the initial offering price, to predict the outcome of the IPO. For the best performing model, we obtain an AUC of 0.80. In line with signalling theory, we argue that prospectuses may indeed send signals able to influence potential investors.}}, author = {{Emidi, Christian and Galan, Sebastian}}, language = {{eng}}, note = {{Student Paper}}, title = {{Prospectus Content as Predictor of IPO Outcome: A topic model approach}}, year = {{2022}}, }