Monthly Archives: May 2015

Andrea Pallavicini, “Arbitrage-Free Pricing with Funding Costs and Collateralization”

Friday May 29  2015
9.30 – 13.00
Scuola Normale Superiore
Aula Fermi

Andrea Pallavicini
Banca IMI, Milano and Imperial College, London

Arbitrage-Free Pricing with Funding Costs and Collateralization

Abstract
The financial crisis started in 2007 has shown that any pricing framework must include from the very beginning the possibility of default of any market player. As a consequence derivative valuation and risk analysis have moved from exotic derivatives managed on simple single-asset classes to simple derivatives embedding credit risk and new, or previously neglected, types of complex and interconnected non-linear effects. Derivative valuation is adjusted to include counterparty credit risk and contagion effects along with funding costs due to collateral posting, treasury policies, and regulatory constraints. A second level of complexity is produced by moving from a single trade to the whole bank portfolio. Aggregation-dependent valuation processes, and theirs operational challenges, arising from non-linearities are discussed both from a mathematical and practical point of view.

Download slides here.

All interested people are kindly invited.

Corsi, F., Lillo, F. and Pirino, D. (2015). Measuring Flight-to-Quality with Granger-Causality Tail Risk Networks.

Abstract
We introduce an econometric method to detect and analyze events of flight-to-quality by financial institutions. Specifically, using the recently proposed test for the detection of Granger causality in risk (Hong et al. 2009), we construct a bipartite network of systemically important banks and sovereign bonds, where the presence of a link between two nodes indicates the existence of a tail causal relation. This means that tail events in the equity variation of a bank helps in forecasting a tail event in the price variation of a bond. Inspired by a simple theoretical model of flight-to-quality, we interpret links of the bipartite networks as distressed trading of banks directed toward the sovereign debt market and we use them for defining indicators of flight-to-quality episodes. Based on the quality of the involved bonds, we distinguish different patterns of flight-to-quality in the 2006-2014 period. In particular, we document that, during the recent Eurozone crisis, banks with a considerable systemic importance have significantly impacted the sovereign debt market chasing the top-quality government bonds. Finally, an out of sample analysis shows that connectedness and centrality network metrics have a significant cross-sectional forecasting power of bond quality measures.
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2576078

Agliari, E., Sartori, F., Cattivelli, L. and Cassi, D., 2015. Hitting and trapping times on branched structures. Physical Review E, 91(5), p.052132.

In this work we consider a simple random walk embedded in a generic branched structure and we find a close-form formula to calculate the hitting time H(i,f) between two arbitrary nodes i and j. We then use this formula to obtain the set of hitting times {H(i,f)} for combs and their expectation values, namely, the mean first-passage time, where the average is performed over the initial node while the final node f is given, and the global mean first-passage time, where the average is performed over both the initial and the final node. Finally, we discuss applications in the context of reaction-diffusion problems.

http://dx.doi.org/10.1103/PhysRevE.91.052132

Massimiliano Caporin, “The impact of network connectivity on factor exposures, asset pricing and portfolio diversification”

Wednesday May 6 2015
13:00
Scuola Normale Superiore
Aula Bianchi

Massimiliano Caporin
Department of Economics and Management “Marco Fanno” – Università di Padova

Abstract
The need for understanding the propagation mechanisms behind the recent financial crises lead the increased interest for works associated with asset interconnections. In this framework, network-based methods have been used to infer from data the linkages between institutions. In this paper, we elaborate on this and make a step forward by introducing network linkages into linear factor models. Networks are used to infer the exogenous and contemporaneous links across assets, and impacts on several dimensions: network exposures act as in inflating factor for systematic exposure to common factors with implications for pricing; the power of diversication is reduced by the presence of network connections; in the presence of network links a misspecied traditional linear factor model provides residuals that are correlated and heteroskedastic. We support our claims with an extensive simulation experiment. Joint work with Monica Billio, Roberto Panzica, and Loriana Pelizzon.