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Real | CumulantGeneratingCond (const std::vector< Real > &invUncondProbs, Real lossFraction, const std::vector< Real > &mktFactor) const |
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Real | CumGen1stDerivativeCond (const std::vector< Real > &invUncondProbs, Real saddle, const std::vector< Real > &mktFactor) const |
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Real | CumGen2ndDerivativeCond (const std::vector< Real > &invUncondProbs, Real saddle, const std::vector< Real > &mktFactor) const |
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Real | CumGen3rdDerivativeCond (const std::vector< Real > &invUncondProbs, Real saddle, const std::vector< Real > &mktFactor) const |
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Real | CumGen4thDerivativeCond (const std::vector< Real > &invUncondProbs, Real saddle, const std::vector< Real > &mktFactor) const |
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boost::tuples::tuple< Real, Real, Real, Real > | CumGen0234DerivCond (const std::vector< Real > &invUncondProbs, Real saddle, const std::vector< Real > &mktFactor) const |
| DISPOSABLE???? More...
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boost::tuples::tuple< Real, Real > | CumGen02DerivCond (const std::vector< Real > &invUncondProbs, Real saddle, const std::vector< Real > &mktFactor) const |
| DISPOSABLE????
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Real | CumulantGenerating (const Date &date, Real s) const |
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Real | CumGen1stDerivative (const Date &date, Real s) const |
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Real | CumGen2ndDerivative (const Date &date, Real s) const |
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Real | CumGen3rdDerivative (const Date &date, Real s) const |
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Real | CumGen4thDerivative (const Date &date, Real s) const |
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Real | findSaddle (const std::vector< Real > &invUncondProbs, Real lossLevel, const std::vector< Real > &mktFactor, Real accuracy=1.0e-3, Natural maxEvaluations=50) const |
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Probability | probOverLossCond (const std::vector< Real > &invUncondProbs, Real trancheLossFract, const std::vector< Real > &mktFactor) const |
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Probability | probOverLossPortfCond1stOrder (const std::vector< Real > &invUncondProbs, Real loss, const std::vector< Real > &mktFactor) const |
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Probability | probOverLossPortfCond (const std::vector< Real > &invUncondProbs, Real loss, const std::vector< Real > &mktFactor) const |
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Probability | probDensityCond (const std::vector< Real > &invUncondProbs, Real loss, const std::vector< Real > &mktFactor) const |
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Disposable< std::vector< Real > > | splitLossCond (const std::vector< Real > &invUncondProbs, Real loss, std::vector< Real > mktFactor) const |
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Real | expectedShortfallFullPortfolioCond (const std::vector< Real > &invUncondProbs, Real lossPerc, const std::vector< Real > &mktFactor) const |
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Real | expectedShortfallTrancheCond (const std::vector< Real > &invUncondProbs, Real lossPerc, Probability percentile, const std::vector< Real > &mktFactor) const |
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Disposable< std::vector< Real > > | expectedShortfallSplitCond (const std::vector< Real > &invUncondProbs, Real lossPerc, const std::vector< Real > &mktFactor) const |
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Real | conditionalExpectedLoss (const std::vector< Real > &invUncondProbs, const std::vector< Real > &mktFactor) const |
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Real | conditionalExpectedTrancheLoss (const std::vector< Real > &invUncondProbs, const std::vector< Real > &mktFactor) const |
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void | resetModel () |
| Concrete models do now any updates/inits they need on basket reset.
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virtual Disposable< std::vector< Real > > | splitESFLevel (const Date &d, Real loss) const |
| Associated ESF fraction to each counterparty.
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virtual Real | densityTrancheLoss (const Date &d, Real lossFraction) const |
| Probability density of a given loss fraction of the basket notional.
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virtual Disposable< std::vector< Probability > > | probsBeingNthEvent (Size n, const Date &d) const |
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virtual Real | defaultCorrelation (const Date &d, Size iName, Size jName) const |
| Pearsons' default probability correlation.
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virtual Probability | probAtLeastNEvents (Size n, const Date &d) const |
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virtual Real | expectedRecovery (const Date &, Size iName, const DefaultProbKey &) const |
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template<class CP>
class QuantLib::SaddlePointLossModel< CP >
Saddle point portfolio credit default loss model.
- Default Loss model implementing the Saddle point expansion integrations on several default risk metrics. Codepence is dealt through a latent model making the integrals conditional to the latent model factor. Latent variables are integrated indirectly.
- See:
- Taking to the saddle by R.Martin, K.Thompson and C.Browne; RISK JUNE 2001; p.91
- The saddlepoint method and portfolio optionalities R.Martin in Risk December 2006
- VAR: who contributes and how much? R.Martin, K.Thompson and C.Browne RISK AUGUST 2001
- Shortfall: Who contributes and how much? R. J. Martin, Credit Suisse January 3, 2007
- Don’t Fall from the Saddle: the Importance of Higher Moments of Credit Loss Distributions J.Annaert, C.Garcia Joao Batista, J.Lamoot, G.Lanine February 2006, Gent University
- Analytical techniques for synthetic CDOs and credit default risk measures A. Antonov, S. Mechkovy, and T. Misirpashaevz; NumeriX May 23, 2005
- Computation of VaR and VaR contribution in the Vasicek portfolio credit loss model: a comparative study X.Huang, C.W.Oosterlee, M.Mesters Journal of Credit Risk (75–96) Volume 3/ Number 3, Fall 2007
- Higher-order saddlepoint approximations in the Vasicek portfolio credit loss model X.Huang, C.W.Oosterlee, M.Mesters Journal of Computational Finance (93–113) Volume 11/Number 1, Fall 2007
- While more expensive, a high order expansion is used here; see the paper by Antonov et al for the terms retained.
- For a discussion of an alternative to fix the error at low loss levels (more relevant to pricing than risk metrics) see:
- The hybrid saddlepoint method for credit portfolios by A.Owen, A.McLeod and K.Thompson; in Risk, August 2009. This is not implemented here though (yet?...)
- For the more general context mathematical theory see: Saddlepoint approximations with applications by R.W. Butler, Cambridge series in statistical and probabilistic mathematics. 2007