Topics in climate change risk

Bortolan, Leonardo (2022) Topics in climate change risk, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Scienze statistiche, 34 Ciclo.
Documenti full-text disponibili:
[img] Documento PDF (English) - Accesso riservato fino a 19 Settembre 2024 - Richiede un lettore di PDF come Xpdf o Adobe Acrobat Reader
Disponibile con Licenza: Salvo eventuali più ampie autorizzazioni dell'autore, la tesi può essere liberamente consultata e può essere effettuato il salvataggio e la stampa di una copia per fini strettamente personali di studio, di ricerca e di insegnamento, con espresso divieto di qualunque utilizzo direttamente o indirettamente commerciale. Ogni altro diritto sul materiale è riservato.
Download (2MB) | Contatta l'autore


In this Thesis, we analyze how climate risk impacts economic players and its consequences on the financial markets. Essentially, literature unravels two main channels through which climate change poses risks to the status quo, namely physical and transitional risk, that we cover in three works. Firstly, the call for a global shift to a net-zero economy implicitly devalues assets that contribute to global warming that regulators are forcing to dismiss. On the other hand, abnormal changes in the temperatures as well as weather-related events challenge the environmental equilibrium and could directly affect operations as well as profitability. We start the analysis with the physical component, by presenting a statistical measure that generally represents shocks to the distribution of temperature anomalies. We oppose this statistic to classical physical measures and assess that it is the driver of the electricity consumption, in the weather derivatives market, and in the cross-section of equity returns. We find two transmission channels, namely investor attention, and firm operations. We then analyze the transition risk component, by associating a regulatory horizon characterization to fixed income valuation. We disentangle a risk driver for corporate bond overperformance that is tight to change in credit riskiness. After controlling a statistical learning algorithm to forecast excess returns, we include carbon emission metrics without clear evidence. Finally, we analyze the effects of change in carbon emission on a regulated market such as the EU ETS by selecting utility sector corporate bond and, after controlling for the possible risk factor, we document how a firm’s carbon profile differently affects the term structure of credit riskiness.

Tipologia del documento
Tesi di dottorato
Bortolan, Leonardo
Dottorato di ricerca
Settore disciplinare
Settore concorsuale
Parole chiave
Climate Change, Temperature extremes, Physical Risk, Transitional Risk, Fixed income, Carbon Emission
Data di discussione
15 Giugno 2022

Altri metadati

Gestione del documento: Visualizza la tesi