The estimation of multivariate GARCH models remains a challenging task, even in modern computer environments. This manuscript shows how Independent Component Analysis can be used to estimate the Generalized Orthogonal GARCH model in a fraction of the time otherwise required. The proposed method...

A new model class for univariate asset returns is proposed which involves the use of mixtures of stable Paretian distributions, and readily lends itself to use in a multivariate context for portfolio selection. The model nests numerous ones currently in use, and is shown to outperform all its...

In order to provide a tool for risk management improvement and appropriate regulation, a methodology for measuring interest rate risk is applied in this paper. After estimating and simulating the interest rate term structure, the value at risk and expected shortfall are calculated on a...

A flexible framework for the analysis of tail events is proposed. The framework contains tail moment measures that allow for Expected Shortfall (ES) estimation. Connecting the implied tail thickness of a family of distributions with the quantile and expectile estimation, a platform for risk...

Most traditional Value at Risk models neglect market liquidity risk and hence only consider the market price risk (i.e. risk associated with holding a certain position). In order to fully capture the market risk associated to holding and trading a position, we first define market liquidity risk,...

We define risk spillover as the dependence of a given asset variance on the past covariances and variances of other assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an international equity portfolio. According to the risk...

This paper investigates the characteristics of the operational loss data formation mechanism that takes place between the date of discovery of a new operational risk event and the final settlement date on which all losses are materialized. The first loss that characterizes the initial impact of...

In the post-crisis era, financial institutions seem to be more aware of the risks posed by extreme events. Even though there are attempts to adapt methodologies drawing from the vast academic literature on the topic, there is also skepticism that fat-tailed models are needed. In this paper, we...

We consider the skewed-T distribution defined as a location-scale normal mixture. Analytical formulas for its value-at-risk and average value-at-risk are derived. High-accuracy approximations are developed and numerically tested

In this paper, we provide a stable limit theorem for the asymptotic distribution of the sample average value-at-risk when the distribution of the underlying random variable X describing portfolio returns is heavy-tailed. We illustrate the convergence rate in the limit theorem assuming that X has...