Results 1 to 10 of about 838 (122)
Credit Valuation Adjustment Compression by Genetic Optimization [PDF]
Risks, 2019 Since the 2008−2009 financial crisis, banks have introduced a family of X-valuation adjustments (XVAs) to quantify the cost of counterparty risk and of its capital and funding implications.
Marc Chataigner, Stéphane Crépey
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Quantum algorithm for credit valuation adjustments
New Journal of Physics, 2022 Quantum mechanics is well known to accelerate statistical sampling processes over classical techniques. In quantitative finance, statistical samplings arise broadly in many use cases.
Javier Alcazar +6 more
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Interactions of Logistic Distribution to Credit Valuation Adjustment: A Study on the Associated Expected Exposure and the Conditional Value at Risk [PDF]
Mathematics, 2022 In Basel III, the credit valuation adjustment (CVA) was given, and it was discussed that a bank covers mark-to-market losses for expected counterparty risk with a CVA capital charge. The purpose of this study is threefold. Using the logistic distribution,
Yanlai Song +3 more
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Credit Valuation Adjustment with Replacement Closeout: Theory and Algorithms [PDF]
SSRN Electronic Journal, 2022 The replacement closeout convention has drawn more and more attention since the 2008 financial crisis. Compared with the conventional risk-free closeout, the replacement closeout convention incorporates the creditworthiness of the counterparty and thus providing a more accurate estimate of the Mark-to-market value of a financial claim.
Chaofan Sun, Ken Seng Tan, Wei Wei
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Impact of Multiple-Curve Dynamics in Credit Valuation Adjustments [PDF]
, 2016 We present a detailed analysis of interest rate derivatives valuation under credit risk and collateral modeling. We show how the credit and collateral extended valuation framework in Pallavicini et al. (2011) can be helpful in defining the key market rates underlying the multiple interest rate curves that characterize current interest rate markets.
Giacomo Bormetti +3 more
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Bilateral Defaultable Financial Derivatives Pricing and Credit Valuation Adjustment [PDF]
SSRN Electronic Journal, 2019 The one-side defaultable financial derivatives valuation problems have been studied extensively, but the valuation of bilateral derivatives with asymmetric credit qualities is still lacking convincing mechanism. This paper presents an analytical model for valuing derivatives subject to default by both counterparties. The default-free interest rates are
Tim Xiao
+10 more sources
A computational approach to hedging Credit Valuation Adjustment in a jump-diffusion setting [PDF]
Applied Mathematics and Computation, 2020 This study contributes to understanding Valuation Adjustments (xVA) by focussing on the dynamic hedging of Credit Valuation Adjustment (CVA), corresponding Profit & Loss (P&L) and the P&L explain. This is done in a Monte Carlo simulation setting, based on a theoretical hedging framework discussed in existing literature.
T. van der Zwaard +2 more
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Credit Valuation Adjustment Study
, 2019 This paper presents a model for calculating credit value adjustment (CVA) by taking wrong way risk into account. Many people believe that the cash flows of a defaultable financial contract can be priced independently and then be summed up to give the final risky price of the contract. We emphasize here that this conclusion is only true of the financial
Tim Xiao
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Credit Valuation Adjustment in Credit Risk with Simultaneous Defaults Possibility [PDF]
, 2020 In a series of recent papers, Damiano Brigo, Andrea Pallavicini, and co-authors have shown that the value of a contract in a Credit Valuation Adjustment (CVA) setting, being the sum of the cash flows, can be represented as a solution of a decoupled forward-backward stochastic differential equation (FBSDE).
Aditi Dandapani, Philip Protter
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Bilateral Credit Valuation Adjustment for Large Credit Derivatives Portfolios [PDF]
Finance and Stochastics, 2013 We obtain an explicit formula for the bilateral counterparty valuation adjustment of a credit default swaps portfolio referencing an asymptotically large number of entities. We perform the analysis under a doubly stochastic intensity framework, allowing for default correlation through a common jump process.
Lijun Bo, Agostino Capponi
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