In this work, we explore the application of machine learning models (MLM) to the analysis of firms’ performance. To such aim, we consider a bunch of financial indicators on firms operating in the Information and Communication Technology (ICT) sector, with attention to enterprises providing ICT related-services. The rationale is to highlight the potential of MLM to exploit the complexity of financial data, and to offer a handy way to visualize the related information. In fact, instead of performing classical analysis, we discuss how to apply to those indicators Self-Organizing Maps-SOMs—that are well suited to manage high dimensional and complex datasets to extract their relevant features. It emerges that SOMs are useful in clustering companies depending on multi-dimensional criteria and in analysing hidden relations in companies’ performances.
|Titolo:||Mapping Financial Performances in Italian ICT-related firms via Self-Organizing Maps|
|Data di pubblicazione:||2018|
|Appare nelle tipologie:||02.01 - Contributo in volume (Capitolo o saggio)|
File in questo prodotto:
|Resta2018_Chapter_MappingFinancialPerformancesIn.pdf||Documento in versione editoriale||Administrator Richiedi una copia|