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Credit Risk
  • CVA and Wrong Way Risk models This paper proposes a simple model for incorporating wrong-way and right-way risk into CVA (credit value adjustment) calculations. These are the calculations made by a dealer to determine the reduction in the value of its derivatives portfolio arising from the possibility of a counterparty default. The model relates the hazard rate of the counterparty to the value of the transactions outstanding between the dealer and the counterparty. Numerical results for portfolios of 25 instruments dependent on five underlying market variables are presented. The paper finds that wrong-way and right-way risk have a significant effect on the Greek letters of CVA as well as on CVA itself. It also finds that the impact of wrong-way and right-way risk depend on the collateral arrangements. , J.Hull (2011)  
  • Bilateral counterparty risk valuation for interest-rate products: impact of volatilities and correlations models The purpose of this paper is introducing rigorous methods and formulas for bilateral counterparty risk credit valuation adjustments (CVA?s) on interest-rate portfolios. In doing so, we summarize the general arbitrage-free valuation framework for counterparty risk adjustments in presence of bilateral default risk, as developed more in detail in Brigo and Capponi (2008), including the default of the investor. We illustrate the symmetry in the valuation and show that the adjustment involves a long position in a put option plus a short position in a call option, both with zero strike and written on the residual net present value of the contract at the relevant default times. We allow for correlation between the default times of the investor and counterparty, and for correlation of each with the underlying risk factor, namely interest rates. We also analyze the often neglected impact of credit spread volatility. We include Netting in our examples, although other agreements such as Margining and Collateral are left for future work. , D.Brigo, A.Pallavicini, V.Papatheodorou (2009)
  • The Risk of Tranches Created from Residential Mortgages models This paper examines the risk in the tranches of ABSs and ABS CDOs that were created from residential mortgages between 2000 and 2007. Using the criteria of the rating agencies, it tests how wide the AAA tranches can be under different assumptions about the correlation model and recovery rates. It concludes that the AAA ratings assigned to the senior tranches of ABSs were not unreasonable. However, the AAA ratings assigned to tranches of Mezz ABS CDOs cannot be justified. The risk of a Mezz ABS CDO tranche depends critically on the correlation between mortgage pools as well as on the correlation model and the thickness of the underlying BBB tranches. The BBB tranches of ABSs cannot be considered equivalent to BBB bonds for the purposes of subsequent securitizations. , J.Hull, A.White (2009)
  • Burnout from pools to loans: Modeling refinancing prepayments as a self-selection process models In this paper we present compelling evidence from a detailed analysis of historical prepayment data to demonstrate that a mortgage cohort remem- bers the level of the previous mortgage rate troughs experienced by the co- hort. This is a general property, observed ubiquitously, that inescapably leads to refinancing models with a continuous distribution of refinancing incentive thresholds (elbows). We present such a new refinancing model, derived from the rst principle, based on a single assumption that each loan has an in- centive threshold above which its borrower will refinance. In this model, the refinancing prepayment of a cohort is a dynamic self-selection process that evolves by itself according to the encountered mortgage rate environment with the cohort concurrently acquiring its memory along the way. , Junwu Gan (2009)
  • Up And Down Credit Risk models , T.Bielicki, S.Crepey, M.Jeanblanc (2008)
  • Mortality Fluctuations Modelling with a Shared Frailty Approach models , J.P.Laurent, S.Fulla (2008)
  • The Credit Crunch of 2007: What Went Wrong? Why? What Lessons Can Be Learned? models , J.C.Hull (2008)
  • Credit Risk Models models , J.P.Laurent (2008)
  • Credit Risk Models models , M.Jeanblanc, T.R.Bielecki, M.Rutkowski (2007)
  • Reduced form modelling for credit risk models , M.Jeanblanc, Y.Le Cam (2007)
  • Credit Risk models , M.Jeanblanc (2006)
  • Merton?s Model, Credit Risk, and Volatility Skews models , J.Hull, A.White, I.Nelken (2004)
  • A Comparative Analysis of Current Credit Risk Models models , M.Crouhy, D.Galai, R.Mark (2000)
  • Pricing Credit Risk Derivatives models , P. J. Sch?nbucher (1998)





















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