DUBECQ Simon

A bank that lends on the unsecured market requires compensations for facing the default risk of the borrowing bank (credit risk) and the risk associated to its own future funding needs (liquidity risk). In this paper, we propose a quadratic term-structure model of the spreads between unsecured and risk free interbank rates. Our no-arbitrage econometric framework allows us to decompose the term structure of spreads into credit and liquidity components and to identify risk premia associated with each of these two risks. Our results suggest that, over the period 2012-2013, most of the reduction in interbank spreads comes from a decrease in liquidity-related risk components.

We construct a model where risk shifting can be moderated by capital requirements. Imperfect information about the level of capital per unit of risk, however, introduces uncertainty about the risk exposure of intermediaries. Over-estimation of the capital held by financial intermediaries, or the extent of regulatory arbitrage, may induce households to wrongly infer from higher asset prices that the fundamentals of risky assets have improved. This mechanism can notably explain the low risk premia paid by U.S. financial intermediaries between 2000 and 2007 in spite of their increased exposure to risk through higher leverage. Moreover, the lower the level of the risk-free interest rate, the more risk is under-estimated.

This paper analyses how an external adverse shock will impact the financial situations of banks and insurance companies and how it will diffuse among these companies. In particular we explain how to disentangle the direct and indirect (contagion) effects of such a shock, how to exhibit the contagion network and how to detect the ”superspreaders”, i.e. the most important firms involved in the contagion process. This method is applied to a network of 8 large European banks in order to analyze whether the revealed interconnections within these banks differ depending on the underlying measure of banks’ financial positions, namely their market capitalization, the price of the CDS contract written on their default and their book value.

This paper analyses how an external adverse shock will impact the financial situations of banks and insurance companies and how it will diffuse among these companies. In particular we explain how to disentangle the direct and indirect (contagion) effects of such a shock, how to exhibit the contagion network and how to detect the ”superspreaders”, i.e. the most important firms involved in the contagion process. This method is applied to a network of 8 large European banks in order to analyze whether the revealed interconnections within these banks differ depending on the underlying measure of banks’ financial positions, namely their market capitalization, the price of the CDS contract written on their default and their book value.

In the first part of this thesis, we introduce a new methodology for stress-test exercises. Our approach allows to consider richer stress-test exercises, which assess the impact of a modification of the whole distribution of asset prices’ factors, rather than focusing as the common practices on a single realization of these factors, and take into account the potential reaction to the shock of the portfolio manager. The second part of the thesis is devoted to the pricing of bonds with very long-term time-to-maturity (more than ten years). Modeling the volatility of very long-term rates is a challenge, due to the constraints put by no-arbitrage assumption. As a consequence, most of the no-arbitrage term structure models assume a constant limiting rate (of infinite maturity). The second chapter investigates the compatibility of the so-called "level" factor, whose variations have a uniform impact on the modeled yield curve, with the no-arbitrage assumptions. We introduce in the third chapter a new class of arbitrage-free term structure factor models, which allows the limiting rate to be stochastic, and present its empirical properties on a dataset of US T-Bonds.

The first part of this thesis introduces a new methodology for conducting stress-testing exercises. Our approach allows to consider much richer stress scenarios than in practice, which evaluate the impact of a change in the statistical distribution of factors influencing asset prices, not only the consequences of a particular realization of these factors, and take into account the reaction of the portfolio manager to the shock. The second part of the thesis is devoted to the valuation of bonds with very long maturities (over 10 years). Modeling the volatility of very long term rates is a challenge, especially because of the constraints posed by the absence of arbitrage opportunities, and most models of interest rates in the absence of arbitrage opportunities imply a constant (infinite maturity) rate limit. The second chapter studies the compatibility of the "level" factor, whose variations have a uniform impact on all the rates modeled, especially the longest ones, with the absence of arbitrage opportunities. In the third chapter, we introduce a new class of interest rate model, without arbitrage opportunities, where the limit rate is stochastic, and we present its empirical properties on a database of US Treasury bond prices.