Tesi etd-11042019-115433
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Tipo di tesi
Corsi integrativi di II livello
Autore
COLUCCIA, DAVIDE MARIA
URN
etd-11042019-115433
Titolo
Value-at-Risk and Credit Cycles: an ABM perspective
Struttura
Cl. Sc. Sociali - Scienze Economiche
Corso di studi
SCIENZE ECONOMICHE E MANAGERIALI - Economics (DM 270)
Relatori
Tutor Prof. NUVOLARI, ALESSANDRO
Relatore Prof. ROVENTINI, ANDREA
Relatore Prof. ROVENTINI, ANDREA
Parole chiave
- Agent-Based Computational Economics
- Financial Cycles
- Leverage
- Mark-to-Market
- Value-at-Risk.
Data inizio appello
09/12/2019;
Disponibilità
completa
Riassunto analitico
This essay studies an Agent-Based model that allows to disentangle the complex links between the real and
the financial sides of an economy. We model a financial sector consisting of equity funds and banks. The
former trade in bank equity, while the latter hold marked-to-market balance sheets and undertake Valueat-Risk leverage management. We show that these features convey a strong feedback and transmission
mechanism to the real side of the economy. We are in particular able to conclude that the amplification
dynamics stemming from the pro-cyclical behavior of bank leverage that emerges are related to more volatile
business cycles, and harsher recessions. Furthermore, we show that our model is able to succesfully
replicate a wide array of empirically well-known stylized facts, ranging from macro business cycle facts to
relevant firm dyamics regularities.
the financial sides of an economy. We model a financial sector consisting of equity funds and banks. The
former trade in bank equity, while the latter hold marked-to-market balance sheets and undertake Valueat-Risk leverage management. We show that these features convey a strong feedback and transmission
mechanism to the real side of the economy. We are in particular able to conclude that the amplification
dynamics stemming from the pro-cyclical behavior of bank leverage that emerges are related to more volatile
business cycles, and harsher recessions. Furthermore, we show that our model is able to succesfully
replicate a wide array of empirically well-known stylized facts, ranging from macro business cycle facts to
relevant firm dyamics regularities.
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