The analysis and prediction of systemic financial risks in the US during COVID-19 pandemic is great significance to stability markets even world. This paper aims predict risk before by using copula–GJR–GARCH models with component expected shortfall (CES), also identify systemically important institutions (SIFIs) for two comparative periods. empirical results show that overall increased after ou...

The autoregressive conditional heteroskedasticity (ARCH) and generalized autoregressive conditional heteroskedasticity (GARCH) models take the dependency of the conditional second moments. The idea behind ARCH/GARCH model is quite intuitive. For ARCH models, past squared innovations describes the present squared volatility. For GARCH models, both squared innovations and the past squared volatil...

In this paper we discuss the problem on parametric and non parametric estimation of the distributions generated by the Marshall-Olkin copula. This copula comes from the Marshall-Olkin bivariate exponential distribution used in reliability analysis. Through this copula we can extend the Marshall-Olkin distribution in order to construct several bivariate survival functions. The cumulative distrib...

Nowadays many researchers use GARCH models to generate volatility forecasts. However, it is well known that volatility persistence, as indicated by the sum of the two parameters G1 and A1[1], in GARCH models is usually too high. Since volatility forecasts in GARCH models are based on these two parameters, this may lead to poor volatility forecasts. It has long been argued that this high persist...

The measure for expert dependence proposed by Jouini and Clemen (clemen) is implemented for expert judgement data gathered at the T.U. Delft. Experts show less dependence than might have been supposed, though more sensitive measures might reveal more. Clemen’s copula for aggregation is implemented and performance is compared with performance-based combinations for two illustrative cases.

Since ARCH and GARCH models are presented, more and more authors are interested in the study of volatilities in financial markets with GARCH models. Method for estimating the coefficients of GARCH models is mainly the maximum likelihood estimation. Now we consider another method—MCMC method to substitute for maximum likelihood estimation method. Then we compare three GARCH models based on it. M...

Any multivariate distribution can be uniquely decomposed into marginal (1-point) distributions, and a function called the copula, which contains all of the information on correlations between the distributions. The copula provides an important new methodology for analyzing the density field in large-scale structure. We derive the empirical 2-point copula for the evolved dark matter density fiel...

We discuss the general optimization problem of choosing a copula with minimum entropy relative to a specified copula and a computationally intensive procedure to solve its dual. These techniques are applied to constructing an empirical copula for CDO tranche pricing. The empirical copula is chosen to be as close as possible to the industry standard Gaussian copula while ensuring a close fit to ...

In this paper we use dynamic copulas method to price a CDO. We apply GOF test and binary segmentation procedure to detect the change of copula function. According to the result of the change point, we divide the time series into nine stages. In each stage, we use the best copula function to describe the default correlation. Our empirical results show that in different time period, the best copu...