The thesis collects five papers, each of them, except the last one, treats a different topics related to the asset interconnections and asset pricing. The first paper extends the classic factor-based asset pricing model by including network linkages, leading to a network-augmented linear factor models. The contribution of the paper is to show that the network presence affects the exposure on the common factor, the power of the diversification and the expected returns. The second paper generalizes the model used in the first work by allowing the number of network greater than one. This work has two contributions: how to use a linear factor model as a device for estimating a combination of several networks that monitor the links across variables from different viewpoints; and to demonstrate that Granger causality should be combined with quantile-based causality when the focus is on risk propagation. The third paper investigates on the determinants of the idiosyncratic volatility puzzle by allowing the contemporaneous linkages across asset returns. The first contribution is to show that the puzzle found by ang et al 2006, where stocks with high (low)idiosyncratic volatility relative to the FamaFrench1993 model have low (high) average returns, falls if the idiosyncratic volatility is filtered out from the impact coming from the network. The purpose of the fourth paper is to assert the different informative content between quantile based network measures and quantile based loss measures such as ΔCoVaR. Globally Systemically Important Banks and Insurers and several Hedge Fund indices are considered. The contribution of the paper is to show that quantile regression based on network measures capture the indirect effect of risk spillovers that is instead ignored by quantile based loss measures. Finally, the comparison between quantile based network measures and quantile based losses measures highlights the predicting power of the former during the global systemic crisis of 2007/2008. The fifth paper is a not network related topic, it analyses which are the causes to make a contract eligible to be cleared, by using probit analysis.
Network connectivity, systematic and systemic risk / Panzica, Roberto Calogero. - (2018 Mar 01).
Network connectivity, systematic and systemic risk
Panzica, Roberto Calogero
2018-03-01
Abstract
The thesis collects five papers, each of them, except the last one, treats a different topics related to the asset interconnections and asset pricing. The first paper extends the classic factor-based asset pricing model by including network linkages, leading to a network-augmented linear factor models. The contribution of the paper is to show that the network presence affects the exposure on the common factor, the power of the diversification and the expected returns. The second paper generalizes the model used in the first work by allowing the number of network greater than one. This work has two contributions: how to use a linear factor model as a device for estimating a combination of several networks that monitor the links across variables from different viewpoints; and to demonstrate that Granger causality should be combined with quantile-based causality when the focus is on risk propagation. The third paper investigates on the determinants of the idiosyncratic volatility puzzle by allowing the contemporaneous linkages across asset returns. The first contribution is to show that the puzzle found by ang et al 2006, where stocks with high (low)idiosyncratic volatility relative to the FamaFrench1993 model have low (high) average returns, falls if the idiosyncratic volatility is filtered out from the impact coming from the network. The purpose of the fourth paper is to assert the different informative content between quantile based network measures and quantile based loss measures such as ΔCoVaR. Globally Systemically Important Banks and Insurers and several Hedge Fund indices are considered. The contribution of the paper is to show that quantile regression based on network measures capture the indirect effect of risk spillovers that is instead ignored by quantile based loss measures. Finally, the comparison between quantile based network measures and quantile based losses measures highlights the predicting power of the former during the global systemic crisis of 2007/2008. The fifth paper is a not network related topic, it analyses which are the causes to make a contract eligible to be cleared, by using probit analysis.File | Dimensione | Formato | |
---|---|---|---|
963322-1218856-Panzica Roberto.pdf
accesso aperto
Tipologia:
Tesi di dottorato
Dimensione
3.43 MB
Formato
Adobe PDF
|
3.43 MB | Adobe PDF | Visualizza/Apri |
I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.