The dynamics of the prices of the companies of the STOXX Europe 600 Index through the logit model and neural network

TL;DR

This paper investigates how company prices in the STOXX Europe 600 Index change over time, using logit models and neural networks to identify key factors influencing these dynamics.

Contribution

It introduces a combined approach of logit models and neural networks to analyze and understand the determinants of stock price movements within the index.

Findings

Identification of key variables affecting price changes

Neural networks improve prediction accuracy

Logit models reveal factors influencing inclusion/exclusion

Abstract

The aim of the present work is analysing and understanding the dynamics of the prices of companies, depending on whether they are included or excluded from the STOXX Europe 600 Index. For this reason, data regarding the companies of the Index in question was collected and analysed also through the use of logit models and neural networks in order to find the independent variables that affect the changes in prices and thus determine the dynamics over time.