The loss given default of a low-default portfolio with weak contagion

Wei, Li; Yuan, Zhongyi

doi:10.1016/j.insmatheco.2015.10.005

Cited by 8 publications

(4 citation statements)

References 32 publications

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“…Their disadvantage is the lack of comparisons between the proposed approaches and other (now traditional) methods described in previous research and mentioned above. Therefore, the practical applicability of the conclusions in Wei and Yuan (2016) and Shi et al (2017) is questionable.…”

Section: Development Of Probability Of Default Models For Ldpsmentioning

confidence: 99%

“…Among the research dedicated to LDP modelling, of special mention are papers by Wei and Yuan (2016) and Shi et al (2017) that offer approaches to building limit distributions for the share of loss given default (LGD) and cumulative loan losses for the LDP, respectively. Their disadvantage is the lack of comparisons between the proposed approaches and other (now traditional) methods described in previous research and mentioned above.…”

Section: Development Of Probability Of Default Models For Ldpsmentioning

confidence: 99%

See 1 more Smart Citation

Low Default Portfolios in Basel II and Basel III as a Special Case of Significantly Unbalanced Classes in Binary Choice Models

Penikas¹

2020

RJMF

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In contemporary world, binary choice models are used in many areas. However, for all such areas, a problem arises when the share of one of the classes in the data sample is small. If this share is significantly small, this class is referred to as low default class. The purpose of this paper is to examine the definitions of such a portfolio and the approaches to building models on its basis. Although various methods exist for obtaining results, this paper shows that distinguishing a low default portfolio class, on the one hand, benefits banks, as does any more detailed segmentation, but, on the other hand, it deteriorates the statistical properties of the models for the probability of default. It is therefore justified that for the internal ratingbased approach in the framework of Basel II and Basel III the regulator should require that banks build their models based on combined data sets discouraging them from setting excessive low default portfolio classes.

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Section: Development Of Probability Of Default Models For Ldpsmentioning

confidence: 99%

Section: Development Of Probability Of Default Models For Ldpsmentioning

confidence: 99%

Low Default Portfolios in Basel II and Basel III as a Special Case of Significantly Unbalanced Classes in Binary Choice Models

Penikas¹

2020

RJMF

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“…As for Situation (4), assume that the two losses X 1 , X 2 and the two discount factors

θ_{1}

θ_{2}

are dependent according to a four‐dimensional FGM copula

C (u) = \prod_{k = 1}^{4} u_{k} (1 + \sum_{1 \leq i < j \leq 4} ω_{i j} (1 - u_{i}) (1 - u_{j})), u \in {[0, 1]}^{4},

with parameters

ω_{i j} \in [- 1, 1], 1 \leq i < j \leq 4

. Clearly,

(X_{1}, X_{2}, θ_{1}, θ_{2})

follows the four‐dimensional Sarmanov distribution, see Wei and Yuan 25 . Assume further that X 1 and X 2 both follow the Pareto distribution (20) with parameters

α_{1} > 0

and

σ_{1} > 0

, and

θ_{1}

and

θ_{2}

both follow the Exponential distribution with intensity

λ_{1} > 0

.…”

Section: Simulation Studiesmentioning

confidence: 99%

Asymptotics for value at risk and conditional tail expectation of a portfolio loss

Wang

Yang

2020

Appl Stoch Models Bus & Ind

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Consider a risk model in which X1,…, Xn are n potential losses from different risky assets at the terminal time, and θ1,…,θn are n discount factors over the period. In this paper, we establish some asymptotic formulas for the value at risk and conditional tail expectation of the total discounted loss Sn=∑i=1nθiXi of an investment portfolio. We also demonstrate our obtained results through Monte Carlo simulations with asymptotics.

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“…Important recent contributions to credit risk modelling are Blanchet-Scalliet et al (2011), Hurd and Zhou (2011), Cont and Minca (2013), Gatarek and Jab lecki (2013), Packham et al (2013), Kijima and Siu (2014), Ballestra and Pacelli (2014), Hao and Li (2015) and Wei and Yuan (2016).…”

Section: Introductionmentioning

confidence: 99%

A factor model for joint default probabilities. Pricing of CDS, index swaps and index tranches

Cantia

Tunaru

2017

Insurance: Mathematics and Economics

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A factor model is proposed for the valuation of credit default swaps, credit indices and CDO contracts. The model of default is based on the first-passage distribution of a Brownian motion time modified by a continuous time-change. Various model specifications fall under this general approach based on defining the credit-quality process as an innovative time-change of a standard Brownian motion where the volatility process is mean reverting Lévy driven OU type process. Our models are bottom-up and can account for sudden moves in the level of CDS spreads representing the so-called credit gap risk. We develop FFT computational tools for calculating the distribution of losses and we show how to apply them to several specifications of the time-changed Brownian motion. Our line of modelling is flexible enough to facilitate the derivation of analytical formulae for conditional probabilities of default and prices of credit derivatives.

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The loss given default of a low-default portfolio with weak contagion

Cited by 8 publications

References 32 publications

Low Default Portfolios in Basel II and Basel III as a Special Case of Significantly Unbalanced Classes in Binary Choice Models

Low Default Portfolios in Basel II and Basel III as a Special Case of Significantly Unbalanced Classes in Binary Choice Models

Asymptotics for value at risk and conditional tail expectation of a portfolio loss

A factor model for joint default probabilities. Pricing of CDS, index swaps and index tranches

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