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Conferences

Session III-1 Banking & Insurance (17/12/2009 à 14h30)

C. Refait-Alexandre

Financial Crisis: Estimating the Risk of Assets in Balance

Auteurs : Giovanni Barone-Adesi (Swiss Finance Insitute, University of Lugano); Giuseppe Corvasce (Swiss Finance Insitute, University of Lugano)

!!Email!! : giovanni.baroneadesi@usi.ch

Intervenants : Giovanni Barone-Adesi (Swiss Finance Insitute, University of Lugano)

Rapporteurs : Markus Fischer

We propose a model able to estimate the risk of assets in balance from aggregate data by introducing a prudential measure called Filtered Historical Spectral Asset Measure (FH - SAM). Our measure combines a model based method to simulate the evolution of volatility with model free method of distribution. It provides a robust methodology to simulate the evolution of risk. The paper extends the debate in the literature about the tools for estimating the risk of assets for a financial institution in case of distress and systemic risk (Stiglitz et al. 2002; Lucas and McDonald 2006).

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Bank Capital Ratios, Competition and Loan Spreads

Auteurs : Markus Fischer (Goethe University Frankfurt) - Fischer@finance.uni-frankfurt.deMarkus Fischer (Goethe University Frankfurt); Julian Mattes (Goethe University Frankfurt); Sascha Steffen (University of Mannheim)

!!Email!! : Fischer@finance.uni-frankfurt.de

Intervenants : Markus Fischer (Goethe University Frankfurt)

Rapporteurs : Carole Gresse

Bank Capital Ratios, Competition and Loan Spreads
This paper uses a dataset of all syndicated loans issued by U.S. borrowers during the 1993 to 2007 period and empirically investigates whether or not bank banks charge higher loan spreads for maintaining high capital ratios. We find convincing evidence that this is indeed the case. We further investigate whether this result can be explained by banks holding-up their borrowers. using various proxies for information asymmetry and competition, we cannot reject the hypotheses that all borrowers pay for banks having high capital ratios. In other words, this premium is not competed away even for the most transparent firms. Our findings have implications why borrowing costs are higher in the U.S. than in Europe.

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Risk Model Validation with Contaminated Data

Auteurs : Laurent FRÉSARD (HEC Paris); Christophe PÉRIGNON (HEC Paris); Anders Wilhelmsson (Lund University, Sweden)

!!Email!! : perignon@hec.fr

Intervenants : Christophe PÉRIGNON (HEC Paris)

Rapporteurs : Giovanni Barone-Adesi

A great challenge for both banks and regulators is to validate risk models. We show that a large fraction of US and international banks uses contaminated data when testing their risk models. In particular, most banks validate their market risk model using profit-and-loss data that include fees and commissions and/or intraday trading revenues. This practice is inconsistent with the definition of the employed market risk measure. Using both simulations and bank data, we find that data contamination has dramatic implications for backtesting and can lead to the acceptance of misspecified risk models. Interestingly, we show that the pernicious effect of data contamination has strengthened during the financial crisis.

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