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Counterparty risk valuation for Energy-Commodities swaps: Impact of volatilities and correlation


  • Damiano Brigo
  • Kyriakos Chourdakis
  • Imane Bakkar


It is commonly accepted that Commodities futures and forward prices, in principle, agree under some simplifying assumptions. One of the most relevant assumptions is the absence of counterparty risk. Indeed, due to margining, futures have practically no counterparty risk. Forwards, instead, may bear the full risk of default for the counterparty when traded with brokers or outside clearing houses, or when embedded in other contracts such as swaps. In this paper we focus on energy commodities and on Oil in particular. We use a hybrid commodities-credit model to asses impact of counterparty risk in pricing formulas, both in the gross effect of default probabilities and on the subtler effects of credit spread volatility, commodities volatility and credit-commodities correlation. We illustrate our general approach with a case study based on an oil swap, showing that an accurate valuation of counterparty risk depends on volatilities and correlation and cannot be accounted for precisely through a pre-defined multiplier.

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  • Damiano Brigo & Kyriakos Chourdakis & Imane Bakkar, 2009. "Counterparty risk valuation for Energy-Commodities swaps: Impact of volatilities and correlation," Papers 0901.1099,
  • Handle: RePEc:arx:papers:0901.1099

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    References listed on IDEAS

    1. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    2. Damiano Brigo, 2008. "Constant Maturity Credit Default Swap Pricing with Market Models," Papers 0812.4159,
    3. Damiano Brigo & Naoufel El-Bachir, 2007. "An exact formula for default swaptions’ pricing in the SSRJD stochastic intensity model," ICMA Centre Discussion Papers in Finance icma-dp2007-14, Henley Business School, Reading University.
    4. Damiano Brigo & Aurélien Alfonsi, 2005. "Credit default swap calibration and derivatives pricing with the SSRD stochastic intensity model," Finance and Stochastics, Springer, vol. 9(1), pages 29-42, January.
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