Pricing Swap Default Risk

Sorensen, Eric H.; Bollier, Thierry F.

doi:10.2469/faj.v50.n3.23

Cited by 172 publications

(110 citation statements)

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“…Earlier works examining the pricing of counterparty credit risk invarious asset classes include, for example, (Sorenson, 1994), who show that the counterparty credit risk on a swap can be expressed as a function of swaptions with various exercise dates and (Brigo, 2005), who calculate the Credit Valuation Adjustment (CVA) assuming unilateral counterparty credit risk. Earlier works treating the commodity asset classes include, for example, (Canabarro, 2005), who analyze the topic from a capital adequacy and risk management perspective.…”

Section: Literature Reviewmentioning

confidence: 99%

CSA Discounting: Impacts on Pricing and Risk of Commodity Derivatives

Abbate¹

2014

JFRM

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The global financial crisis of 2007-2008 caused market practitioners to reassess the way in which financial derivative contracts had been priced during the preceding thirty years. The purpose of this paper is to examine the evolving practice of pricing and hedging commodity derivative contracts according to the terms of the Credit Support Annex (CSA). Using a series of case studies, we price crude oil swaps and Asian options in the pre-crisis, peak-crisis, post-crisis and recent market environments under two different frameworks: LIBOR discounting and CSA discounting (also referred to in a less general form as "OIS discounting", which incorporates nearly risk-free interest rates). We also compute the widely used first-order and second-order Greek sensitivities. In each market environment, we shift the forward prices and implied volatilities crude oil and re-compute the trades' valuation and Greek sensitivities at each incremental increase or decrease in price or implied volatility. Under each discounting framework, we quantify the change in trade valuation and Greek sensitivities that results from switching from LIBOR discounting to CSA discounting. The impact on the valuation and Greek sensitivities of a swap and an Asian option as the result of adopting CSA discounting can be significant under certain market conditions. There is likely to be larger impact on directional portfolios containing transactions that hedge either consumption or production (e.g. end users). Ceteris paribus, the impact on portfolio valuation and risk is likely to be limited for market participants (e.g. banks) with hedged portfolios that contain a large number of offsetting positions. Even though we focus our analysis on crude oil derivative contracts, the results easily extend to other asset classes such as natural gas, refined products, agriculture, metals, etc.

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Section: Literature Reviewmentioning

confidence: 99%

CSA Discounting: Impacts on Pricing and Risk of Commodity Derivatives

Abbate¹

2014

JFRM

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“…Journal of Futures Markets DOI: 10.1002/fut fixed and long an option to pay (receive) floating cash flows, with the counterparty simultaneously owning the opposite pair of options, Sorensen and Bollier (1994) argue that the value of a swap depends on the value of the option to default. The value of the option to default, in turn, depends on a number of factors including the swap parties' default probabilities, the shape of the yield curve, and interest rate volatility.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The interest rate volatility generated by a GARCH model and the slope of the term structure of interest rates are also included in our empirical model because these two variables determine the value of the option to default in the Sorensen and Bollier's (1994) model. Because increasing interest rate volatility is often associated with economic uncertainty, as such, it is expected to positively influence swap spreads.…”

Section: Data and Variablesmentioning

confidence: 99%

“…Theoretically, the impact of the slope of the term structure on swap spreads could be either positive or negative. For instance, according to Sorensen and Bollier (1994), when the yield curve is upward sloping, the fixed payer (floating receiver) is exposed to higher counterparty risk due to higher default risk exposure associated with the higher future floating payments. A lower fixed swap rate will compensate for this increased risk.…”

Section: Data and Variablesmentioning

confidence: 99%

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Determinants of Japanese Yen interest rate swap spreads: Evidence from a smooth transition vector autoregressive model

Huang

Chen

Camacho

2007

Journal of Futures Markets

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This study investigates the determinants of variations in the yield spreads between Japanese yen interest rate swaps and Japan government bonds for a period from 1997 to 2005. A smooth transition vector autoregressive (STVAR) model and generalized impulse response functions are used to analyze the impact of various economic shocks on swap spreads. The volatility based on a GARCH (generalized autoregressive conditional heteroskedasticity) model of the government bond rate is identified as the transition variable that controls the smooth transition from a high volatility regime to a low volatility regime. The break We thank two anonymous reviewers and the editor, Bob Webb, for helpful comments. The views in this paper are those of the authors and do not represent the views of the Bank of Spain or the Eurosystem. point of the regime shift occurs around the end of the Japanese banking crisis. The impact of economic shocks on swap spreads varies across the maturity of swap spreads as well as regimes. Overall, swap spreads are more responsive to the economic shocks in the high volatility regime. Moreover, a volatility shock has profound effects on shorter maturity spreads, whereas the term structure shock plays an important role in impacting longer maturity spreads. Results of this study also show noticeable differences between the nonlinear and linear impulse response functions.

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“…Hull et al [3] while the volatility of the credit spread is neglected (the hazard rate is assumed to be a constant). In other studies, volatility of the credit spread is included but the interest rate of the underlying asset is assumed to be a constant as in Brigo et al [4] and Sorensen [5]. In more recent work Brigo et al [6][7][8], both stochastic interest rate and hazard rate models are used.…”

Section: Introductionmentioning

confidence: 99%

Credit contingent interest rate swap pricing

Huang

Wang

et al. 2017

Mathematics-in-Industry Case Studies

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Credit value adjustment (CVA) is an adjustment to an existing trading price based on the counterparty-risk premium. Currently, CVA is computed with an implicit assumption that the replacement contract is default-free after the original counterparty defaults, with the assumption that those trades will not re-assigned. In the actual counterparty default settlement, it is the norm that trades will be re-assigned, especially on the buy side. Since the counterparty of the replacement contract could also default within the lifetime of an existing contract, ignoring the possibility of counterparty defaults of replacement contracts will either under or over estimate the cost of the risk. An important practical question is, therefore, how to estimate under/over pricing of CVA under current practice. In this paper, we considered the pricing of credit contingent interest rate swap (CCIRS) or credit contingent default swap (CCDS), which is considered the CVA hedge for interest rate swaps (IRS). We derived partial differential Eqs. (PDEs) satisfied by the approximated CVA with the assumption that the replacement contracts do not default. For comparison purposes, we also derived the PDEs for the cost of CVA by relaxing the assumption of default-free replacement contracts with a finite number of counterparty defaults. It shows that the no-default and two default cases can be derived within the same analytical solution framework, similar to the Funding Valuation Adjustment (FVA) problem where continuous funding is a reasonable assumption. The finite number of default case is non-trivial. The PDE for the two default case is derived in this paper. We calibrate our model based on market data and carry out extensive computations for the purpose of comparing these three CVAs. Our basic finding is that the values of the two CVAs are close for top rated counterparties. On the other hand, for counterparties with lower credit ratings, the difference among the two CVAs can be significant.

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Pricing Swap Default Risk

Cited by 172 publications

References 0 publications

CSA Discounting: Impacts on Pricing and Risk of Commodity Derivatives

CSA Discounting: Impacts on Pricing and Risk of Commodity Derivatives

Determinants of Japanese Yen interest rate swap spreads: Evidence from a smooth transition vector autoregressive model

Credit contingent interest rate swap pricing

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