The impact of multinationality on firm value: A comparative analysis of machine learning techniques

详细信息    查看全文

• 作者：Cemil Kuzey^a ; ^{ckuzey@fatih.edu.tr" class="auth_mail}Author Vitae ; Ali Uyar^a ; ^{auyar@fatih.edu.tr" class="auth_mail}Author Vitae ; Dursun Delen^b ; ^{dursun.delen@okstate.edu" class="auth_mail}Author Vitae
• 关键词：Machine learning ; Predictive analytics ; Decision trees ; Artificial neural networks ; Sensitivity analysis ; Firm value ; Multinationality
• 刊名：Decision Support Systems
• 出版年：March, 2014
• 年：2014
• 卷：59
• 期：Complete
• 页码：127-142
• 全文大小：1181 K

文摘

In this study, the impact of multinationality (as measured by foreign sales ratio) and fourteen other financial indicators on firm value (characterized by market capitalization and market-to-book ratio) for the period of 1997-2011 was investigated using two popular machine learning techniques: decision trees and artificial neural networks. We divided the time period of 1997-2011 into two periods; 1997-2004 and 2005-2011 to investigate the robustness of results pre- and post-IFRS implementation. To determine the relative importance of factors as the predictors of firm value, first, a number of classification models are developed; then, the information fusion based sensitivity analysis is applied to these classification models to identify the ranked order of the independent variables. Among the independent variables, multinationality was found to determine firm value only moderately. In addition to multinationality, other financial characteristics such as firm size (as measured by natural logarithm of assets), leverage, liquidity, and profitability were consistently found to be affecting firm value.