This paper adopts a copula approach at assessing the dependence structure of the U.S. equity market. Seven types of copulas are considered: Gaussian, Student t, Clayton, rotated Clayton, Gumbel, rotated Gumbel and BB4. By adopting a twenty-two year sample of daily returns on the seventeen Fama...

Die klassische, von Markowitz entwickelte, Portfoliotheorie basiert auf spezifischen Risikomaßen, der Renditevarianz bzw. der Renditestandardabweichung. Diese Risikomaße messen primär die Volatilität der Renditeentwicklung...

In this paper we propose a maximum entropy estimator for the asymptotic distribution of the hedging error for options. Perfect replication of financial derivatives is not possible, due to market incompleteness and discrete-time hedging. We derive the asymptotic hedging error for options under a...

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...

In the aftermath of the Global Financial Crisis, some risk management practitioners have advocated wider adoption of Bayesian inference to replace Value- at-Risk (VaR) models in order to minimize risk failures. Despite its limitations, the Bayesian methodology has significant advantages. Just...

We study the intra-horizon value at risk (iVaR) in a general jump diffusion setup and propose a new model of asset returns called displaced mixed-exponential model, which can arbitrarily closely approximate finite-activity jump-diffusions and completely monotone Levy processes. We derive...

In this work, we propose an ARMA(1,1)-GARCH(1,1) model with standard classical tempered stable (CTS) innovations for historical daily returns of 29 selected stocks. The non-Gaussian nature of the innovations captures the fat-tail property observed in data. The dependency between different assets...

Value-at-risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a simple approach to forecasting of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting the...

This study introduces a multivariate entropic Value at Risk (mEVaR) risk measure, broadening the conventional Value at Risk scope to a multi-asset scenario. The mEVaR is coherent and encapsulates the integrated risk of various assets in a portfolio. In addition, a new theoretical result...