can be used in risk measurement and forecasting. Value at risk (VaR) is a widely used measure of financial risk, which … 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 …

This paper investigates the predictability of variance and value at-risk (VaR) measures in international stock markets … determine the persistency of these risk measures. We find that for all G7 countries considered in the paper persistency in …

This paper investigates the prediction of Value-at-Risk (VaR) using option-implied information obtained by the maximum … entropy method. The maximum entropy method provides an estimate of the risk-neutral distribution based on option prices …. Besides commonly used implied volatility, we obtain implied skewness, kurtosis and quantile from the estimated risk …

, practitioners and researchers. However, little attention has been paid to the predictability of their risk measures. In this paper …, we compare the predictability of the one-step-ahead volatility and Value-at-Risk of Bitcoin using several volatility … models. We also include procedures that take into account the presence of outliers and estimate the volatility and Value-at-Risk …

In this study we consider the risk estimation as a stochastic process based on the Sample Quantile Process (SQP …) - which is a generalization of the Value-at-Risk calculated on a rolling sample. Using SQP's, we are able to show and quantify … the pro-cyclicality of the current way financial institutions measure their risk. Analysing 11 stock indices, we show that …