Swissquote Conference on Interest Rate and Credit Risk: Program

s (in alphabetic order of speakers) Tomas Björk, Stockholm School of Economics Title: Good Deal Bound Pricing, with Applications to Credit Risk Abstract: We consider an incomplete market in the form of a multidimensional Markovian factor model, driven by a general marked point process (representing discrete jump events) as well as by a standard multidimensional Wiener process. Within this framework we give an overview of the theory of arbitrage free good deal pricing bounds for derivative assets and present some recent applications to credit risk and regime switching models. Giovanni Cesari, UBS Title: Modelling Counterparty Exposure and Credit Valuation Adjustment Abstract: The credit crisis that started in 2007, with the collapse of well-established financial institutions and the bankruptcy of many public corporations, has clearly shown the importance for any company entering in the derivative business of Modelling, Pricing, and Hedging Counterparty Credit Exposure. Building an accurate representation of firm-wide credit exposure, for both risk and trading activities, is a significant challenge from a technical as well as a practical point of view. In this talk we consider several aspects of finding solutions to the problem of computing counterparty risk exposure and CVA for large books of both vanilla and exotic derivatives usually traded by large Investment Banks. The main challenges faced when computing future value distributions for diverse portfolios of financial products are the following:  Scenario consistency. When tackling a pricing problem, different transactions can be priced in isolation and the resulting value summed up to give the portfolio value. In a portfolio view, however, the behaviour of a portfolio in future scenarios cannot be estimated correctly unless all constituent trades are analyzed in the same set of common scenarios. This means that both the simulation and the pricing methodology has to be able to deal with all types of products in a consistent way.  Accuracy. When dealing with hedging and pricing counterparty exposure (CVA) accuracy is key. The approach, often used in the industry, of generating scenarios and using analytical formulas for pricing has strong limitations. To deal with exotic types of transactions we suggest using American Monte Carlo (AMC) techniques. AMC allows the definition of a generic mathematical framework, which can be applied to all types of transactions in a consistent way. Swissquote Conference on Interest Rate and Credit Risk: Program  Different financial products representations. In general large Investment Banks have different desks with their own way of representing and pricing trades, so that the trades in any counterparty's portfolio might be a collection of different trade types that are booked, priced, and represented differently. If we are to apply a common simulation and pricing methodology to all trade types, an essential step is to convert all trade representations to a common representation that lends itself well to the framework we have chosen. The common representation we have come up with is the Portfolio Aggregation Language (PAL). In light of these challenges, the main points we will consider in this talk are  Computing CVA and counterparty risk for both vanilla and exotic products.  Defining a generic mathematical and computational framework.  We will give several practical examples of exposure computations across all asset classes  We will show how to include right way / wrong way risk  And finally we will show the impact of collateral Pierre Collin-Dufresne, Columbia University Title: On the Relative Pricing of long Maturity S&P 500 Index Options and CDX Tranches Abstract: We investigate a structural model of market and firm-level dynamics in order to jointly price long-dated S&P 500 options and tranche spreads on the five-year CDX index. We demonstrate the importance of calibrating the model to match the entire term structure of CDX index spreads because it contains pertinent information regarding the timing of expected defaults and the specification of idiosyncratic dynamics. Our model matches the time series of tranche spreads well, both before and during the financial crisis, thus offering a resolution to the puzzle reported by Coval, Jurek and Stafford (2009). Rama Cont, CNRS-Université de Paris VI and Columbia University Title: Default Contagion and Systemic Risk in Financial Networks Abstract: A banking system may be modeled as a network of counterparties, where nodes represent financial institutions and (weighted) links represent the exposures of institutions to each other. Using a unique data set of interbank exposures and capital levels of Brazilian financial institutions, we show Swissquote Conference on Interest Rate and Credit Risk: Program that such banking networks may be modeled as directed scale-free networks with regularly-varying degree and exposure distributions. In such networks, the failure of a node may generate contagion via domino effects and default cascades. We define two indicators of default contagion the Default Impact and the Contagion Indexwhich measure the extent of systemic risk generated by the failure of an institution. We use these indicators to investigate the magnitude and nature of systemic risk in the Brazilian financial system. We find that default contagion, whose importance had been minimized in several previous studies, can be a major source of systemic risk if its magnitude is measured properly. Our study also reveals some interesting connections between network properties and the magnitude of systemic risk in the network and points to quantities which could serve as efficient tools for monitoring and regulating systemic risk. For large networks, we perform an asymptotic analysis of the size of default cascades and obtain an analytical criterion for the stability of the network with respect to the default of a given node. Our asymptotic results are shown to be in good agreement with numerical simulation of large networks and provide a theoretical framework for stress testing the resilience to contagion of a large counterparty networks.