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Efficient algorithms for calculating risk measures and risk contributions in copula credit risk models

Huang, Zhenzhen; Kwok, Yue-Kuen; Xu, Ziqing - In: Insurance : mathematics and economics 115 (2024), pp. 132-150

Persistent link: https://www.econbiz.de/10015066737

A general importance sampling algorithm for estimating portfolio loss probabilities in linear factor models

Scott, Alexandre; Metzler, Adam - In: Insurance / Mathematics & economics 64 (2015), pp. 279-293

Persistent link: https://www.econbiz.de/10011398073

Estimating multifactor portfolio credit risk : a variance reduction approach

Hsieh, Ming-Hua; Lee, Yi-Hsi; Shyu, So-De; Chiu, Yu-Fen - In: Pacific-Basin finance journal 57 (2019), pp. 1-17

Persistent link: https://www.econbiz.de/10012170623

A TVM-Copula-MIDAS-GARCH model with applications to VaR-based portfolio selection

Jiang, Cuixia; Ding, Xiaoyi; Xu, Qifa; Tong, Yongbo - In: The North American journal of economics and finance : a … 51 (2020), pp. 1-11

Persistent link: https://www.econbiz.de/10012659611

A g-and-h Copula Approach to Risk Measurement in Multivariate Financial Models

Huggenberger, Markus - 2010

considered and fast random sampling is of importance. To illustrate our methodology, we fit copula GARCH models with g …

Persistent link: https://www.econbiz.de/10013138164

Dynamic Correlation Hedging in Copula Models for Portfolio Selection

Stefanova, Denitsa - 2009

In this paper we address the issue of modeling extreme asset co-movements and their implications for the hedging demands of a dynamic portfolio. We propose a model that is able to accommodate an extremal dependence structure through the stationary distribution of the state variables underlying...

Persistent link: https://www.econbiz.de/10013155303

Forecasting the Risk of Speculative Assets by Means of Copula Distributions

Beckers, Benjamin - 2013

The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of financial returns and portfolio risk. In this paper, we propose an adjustment of GARCH implied conditional value-at-risk and expected shortfall forecasts that exploits the...

Persistent link: https://www.econbiz.de/10013084434

Forecasting the risk of speculative assets by means of copula distributions

Beckers, Benjamin; Herwartz, Helmut; Seidel, Moritz - 2013

The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of financial returns and port-folio risk. In this paper, we propose an adjustment of GARCH implied conditional value-at-risk and expected shortfall forecasts that exploits the...

Persistent link: https://www.econbiz.de/10009723920

Modeling dependencies in finance using copulae

Härdle, Wolfgang (contributor); Okhrin, Ostap (contributor) - 2008

In this paper we provide a review of copula theory with applications to finance. We illustrate the idea on the …

Persistent link: https://www.econbiz.de/10003727552

Bayesian inference for latent factor copulas and application to financial risk forecasting

Schamberger, Benedikt; Gruber, Lutz F.; Czado, Claudia - In: Econometrics : open access journal 5 (2017) 2, pp. 1-23

couple the variables with the latent factor. We use adaptive rejection Metropolis sampling (ARMS) within Gibbs sampling for … posterior simulation: Gibbs sampling enables application to Bayesian problems, while ARMS is an adaptive strategy that replaces … of our proposed approach both in terms of sampling efficiency and accuracy. We provide an extensive application example …

Persistent link: https://www.econbiz.de/10011654443