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Importance sampling in the presence of PD-LGD correlation

Metzler, Adam; Scott, Alexandre - In: Risks : open access journal 8 (2020) 1/25, pp. 1-36

to as PD-LGD correlation (here PD refers to probability of default, which is often used synonymously with default rate …). There is a large literature on modelling stochastic LGD and PD-LGD correlation, but there is a dearth of literature on using … deviation probabilities across a wide variety of PD-LGD correlation models that have been proposed in the literature. …

Persistent link: https://www.econbiz.de/10012203783

Risk model validation : an intraday VaR and ES approach using the multiplicative component GARCH

Summinga-Sonagadu, Ravi; Narsoo, Jason - In: Risks : open access journal 7 (2019) 1/10, pp. 1-23

In this paper, we employ 99% intraday value-at-risk (VaR) and intraday expected shortfall (ES) as risk metrics to assess the competency of the Multiplicative Component Generalised Autoregressive Heteroskedasticity (MC-GARCH) models based on the 1-min EUR/USD exchange rate returns. Five...

Persistent link: https://www.econbiz.de/10012018629

Tail dependence in financial markets : a dynamic copula approach

Cortese, Federico Pasquale - In: Risks : open access journal 7 (2019) 4/116, pp. 1-14

This article is concerned with the study of the tail correlation among equity indices by means of dynamic copula … Correlation (DCC) model. …

Persistent link: https://www.econbiz.de/10012127765

Markov Chain Monte Carlo methods for estimating systemic risk allocations

Koike, Takaaki; Hofert, Marius - In: Risks : open access journal 8 (2020) 1/6, pp. 1-33

In this paper, we propose a novel framework for estimating systemic risk measures and risk allocations based on Markov Chain Monte Carlo (MCMC) methods. We consider a class of allocations whose jth component can be written as some risk measure of the jth conditional marginal loss distribution...

Persistent link: https://www.econbiz.de/10012204312

Credit risk meets random matrices : coping with non-stationary asset correlations

Mühlbacher, Andreas; Guhr, Thomas - In: Risks : open access journal 6 (2018) 2, pp. 1-25

model for random correlation matrices to model non-stationary effects. We then use the Merton model in which default events … ensemble of random matrices that models the truly existing set of measured correlation matrices. As a most welcome side effect …

Persistent link: https://www.econbiz.de/10011866403

Direct and hierarchical models for aggregating spatially dependent catastrophe risks

Wójcik, Rafał; Liu, Charlie Wusuo; Guin, Jayanta - In: Risks : open access journal 7 (2019) 2/54, pp. 1-22

We present several fast algorithms for computing the distribution of a sum of spatially dependent, discrete random variables to aggregate catastrophe risk. The algorithms are based on direct and hierarchical copula trees. Computing speed comes from the fact that loss aggregation at branching...

Persistent link: https://www.econbiz.de/10012019121

A note on the impact of parameter uncertainty on barrier derivatives

Escobar, Marcos; Panz, Sven - In: Risks : open access journal 4 (2016) 4, pp. 1-25

This paper presents a comprehensive extension of pricing two-dimensional derivatives depending on two barrier constraints. We assume randomness on the covariance matrix as a way of generalizing. We analyse common barrier derivatives, enabling us to study parameter uncertainty and the risk...

Persistent link: https://www.econbiz.de/10011556565

L1 regularization for high-dimensional multivariate GARCH models

Yao, Sijie; Zou, Hui; Xing, Haipeng - In: Risks : open access journal 12 (2024) 2, pp. 1-29

The complexity of estimating multivariate GARCH models increases significantly with the increase in the number of asset series. To address this issue, we propose a general regularization framework for high-dimensional GARCH models with BEKK representations, and obtain a penalized quasi-maximum...

Persistent link: https://www.econbiz.de/10014497339

Multivariate analysis of energy commodities during the COVID-19 pandemic : evidence from a mixed-frequency approach

Andreani, Mila; Candila, Vincenzo; Morelli, Giacomo; … - In: Risks : open access journal 9 (2021) 8, pp. 1-20

COVID-19 low-frequency variable, namely the Dynamic EquiCorrelation (DECO) and corrected Dynamic Conditional Correlation …

Persistent link: https://www.econbiz.de/10012612379

Bivariate copula trees for gross loss aggregation with positively dependent risks

Wójcik, Rafał; Liu, Charlie Wusuo - In: Risks : open access journal 10 (2022) 8, pp. 1-24

We propose several numerical algorithms to compute the distribution of gross loss in a positively dependent catastrophe insurance portfolio. Hierarchical risk aggregation is performed using bivariate copula trees. Six common parametric copula families are studied. At every branching node, the...

Persistent link: https://www.econbiz.de/10013368496

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