assumptions alone in measuring risk. Cushioning against risk has always created a plethora of complexities and challenges; hence …, this paper attempts to analyse statistical properties of various risk measures in a not normal distribution and provide a … financial blueprint on how to manage risk. It is assumed that using old assumptions of normality alone in a distribution is not …

This paper investigates the dynamic evolution of tail risk interdependence among U.S. banks, financial services and …. The tail risk interdependence measurement framework relies on the multivariate Student-t Markov switching (MS) model and … the multiple-conditional value-at-risk (CoVaR) (conditional expected shortfall (CoES)) risk measures introduced in …

In this paper, we study the skewness risk and its return predictability in the energy market. Skewness risk is often …-sectional average realized skewness) estimated from underlying stock returns and risk-neutral skewness evaluated from the options market …

Systemic risk, in a complex system with several interrelated variables, such as a financial market, is quantifiable … distribution function can provide a full quantification of risk and stress propagation in the system. However, multivariate … distributions, discussing their estimation from data and proposing novel measures for stress impact and systemic risk in systems …

Several market and macro-level variables influence the evolution of equity risk in addition to the well …-known volatility persistence. However, the impact of those covariates might change depending on the risk level, being different between … low and high volatility states. By combining equity risk estimates, obtained from the Realized Range Volatility, corrected …

applications in Risk Management, Finance, Economics, Science, and many other areas. This paper develops the theory on both density …

distributed risk factors. Our results aim to correct inaccuracies that originate in Kamdem (2005) and are present also in at least … degrees of freedom. As such, the resulting economic impact in financial risk management applications could be significant. We …

The statistical distribution of financial returns plays a key role in evaluating Value-at-Risk using parametric methods …. Traditionally, when evaluating parametric Value-at-Risk, the statistical distribution of the financial returns is assumed to be … the observed financial returns. This article focuses on the evaluation of the South African equity markets in a Value-at-Risk …