Predicting post-IPO financial performance: a hybrid approach using logistic regression and decision trees
Pornpawee Supsermpol & Van Nam Huynh & Suttipong Thajchayapong & Nathridee Suppakitjarak & Navee Chiadamrong
DOI: https://doi.org/10.1108/JABES-06-2024-0292
Abstract
Purpose
This study enhances the financial modelling of companies undergoing an Initial Public Offering (IPO) by focusing on internal capability determinants and IPO proceeds.
Design/methodology/approach
A hybrid logistic regression and shallow-depth decision tree approach are employed to predict the initial three-year post-IPO performance of companies listed on the Stock Exchange of Thailand (SET) using data from 2002 to 2021.
Findings
The results demonstrate that these models not only perform competitively against complex machine learning algorithms but also surpass them in terms of interpretability, an essential feature in financial modelling. The proposed approach effectively captures the effects of each determinant, offering valuable insights into strategic resource allocation and investment decision-making during transition years.
Originality/value
This study introduces a novel application that integrates logistic regression with decision trees to predict multiclass financial performance, filling the gap between complex machine learning techniques and interpretable financial models. It offers practical tools for companies and investors to make informed decisions in challenging post-IPO environments.
2022, Journal of Asian Business and Economic Studies
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Abstract
Purpose
The purpose of this paper is to extend the literature on the spillovers across economic policy uncertainty (EPU) and cryptocurrency uncertainty indices.
Design/methodology/approach
This paper uses cross-country economic policy uncertainty indices and the novel data measuring the cryptocurrency price uncertainties over the period 2013–2021 to construct a sample of 946 observations and applies the time-varying parameter vector autoregression (TVP-VAR) model to do an empirical study.
Findings
The findings suggest that there are cross-country spillovers of economic policy uncertainty. In addition, the total uncertainty spillover between economic policies and cryptocurrency peaked in 2015 before gradually decreasing in the following periods. Concomitantly, the cryptocurrency uncertainty has acted as the “receiver.” More importantly, the authors found the predictive power of economic policy uncertainty to predict the cryptocurrency uncertainty index. This paper’s results hold robust when using alternative measurement of cryptocurrency policy uncertainty.
Originality/value
This study is the first research that deeply investigates the association between two uncertainty indicators, namely economic policy uncertainty and the cryptocurrency uncertainty index. We provide fresh evidence about the dynamic connectedness between country-level economic policy uncertainty and the cryptocurrency index. Our work contributes a new channel driving the variants of uncertainties in the cryptocurrency market.
