Showing 1 - 6 of 6
Under the new Basel III banking regulation banks should include wrong-way risk (WWR) into the calculation of the credit valuation adjustment (CVA) of the OTC derivatives. WWR takes place when the exposure to a counterparty is adversely correlated with the credit quality of that counterparty....
Persistent link: https://www.econbiz.de/10013023673
We are comparing two approaches for stochastic volatility and jumps estimation in the EUR/USD time series - the non-parametric power-variation approach using high-frequency returns, and the parametric Bayesian approach (MCMC estimation of SVJD models) using daily returns. We find that both of...
Persistent link: https://www.econbiz.de/10013030080
Methodology is proposed of how to utilize high-frequency power-variation estimators in the Bayesian estimation of Stochastic-Volatility Jump-Diffusion (SVJD) models. Realized variance is used as an additional source of information for the estimation of stochastic variances, while the Z-Estimator...
Persistent link: https://www.econbiz.de/10012914862
The aim of this paper is to propose and test a novel PF method called Sequential Gibbs Particle Filter allowing to estimate complex latent state variable models with unknown parameters. The framework is applied to a stochastic volatility model with independent jumps in returns and volatility....
Persistent link: https://www.econbiz.de/10012916933
We formulate a bivariate stochastic volatility jump-diffusion model with correlated jumps and volatilities. An MCMC Metropolis-Hastings sampling algorithm is proposed to estimate the model's parameters and latent state variables (jumps and stochastic volatilities) given observed returns. The...
Persistent link: https://www.econbiz.de/10013121407
In this paper, Extreme value theory (EVT) is applied in estimating low quantiles of P/L distribution and the results are compared to common VaR methodologies. The fundamental theory behind EVT is built, and peaks-over-threshold method is used for modeling the tail of the distribution of losses...
Persistent link: https://www.econbiz.de/10013129257