Drivers of Corporate Turnaround: An Analysis of Italian Companies in the period 2016-2022

This master thesis explores the dynamics of turnaround investing in Italy over the period 2016 to 2022, a time characterized by significant economic fluctuations and challenges for businesses across various sectors. At the heart of this investigation is an analysis of the drivers behind successful turnaround strategies, providing insights into the mechanisms that enable distressed companies to achieve sustainable recovery and growth. Turnaround investing refers to the process of identifying, investing in, and revitalizing companies that are experiencing financial distress or operational difficulties. This investment strategy is predicated on the belief that, with the right interventions in management, operational efficiencies, financial restructuring, or strategic reorientation, these companies can recover and generate substantial value for their stakeholders. The target of turnaround investments is distressed companies, by definition, those facing liquidity constraints, declining sales, loss of market share, or challenges that threaten their ongoing viability. The allure of turnaround investing lies in the potential for high returns; however, it also involves substantial risk, given the precarious position of the target companies. Understanding the drivers behind successful turnarounds is essential for investors, managers, and policymakers aiming to support distressed companies. This thesis categorizes these drivers into four macro areas: operational efficiency improvements, financial restructuring, managerial changes, and assets restructuring. Through empirical analysis, the research identifies patterns and practices that have led to successful turnarounds in the Italian context, offering an overview of the Italian turnaround market in the period from 2016 to 2022. The primary objective of this thesis is to understand the significance of the drivers and to understand if they have a positive or negative contribution. This will be done by using a regression model structured by setting as a dependent (explicative) variable the Equity. By analyzing the output of such model it’ll be possible to determine if the drivers, identified during the literature review, are significant or not. This thesis is articulated in two macro areas. The first part aims to establish a strong theoretical foundation by analyzing existing literature to provide an overview of theories and past research that have paved the way in this field. The initial part focuses on discussing financial distress, describing the typical target company for turnaround investing, and delving into the most renowned predictive models of financial distress. This leads to the framing of turnaround investment, the true core of this research, where not only is turnaround investment defined, but also the models and strategies frequently employed for such investments are examined. The second major area concentrates on empirical analysis, with the goal of identifying the significance of drivers that have facilitated a shift in performance. This empirical analysis will be conducted using financial data collected from the AIDA database, as well as web research that has provided insights into the strategies used for individual turnaround operations (e.g., press releases from the players, official communications from the company undergoing the turnaround process). The second part will focus on the Italian market, sector that will be mapped during this thesis by analyzing both the current state of the turnaround investing sector in Italy, exam