One of the key components of financial risk management is risk measurement. This typically requires modeling … financial econometrics literature have developed several models based on Extreme Value Theory (EVT) to carry out these tasks …

This article reviews two leading measures of financial risk and an emerging alternative. Embraced by the Basel accords …, value-at-risk and expected shortfall are the leading measures of financial risk. Expectiles offset the weaknesses of value-at-risk … (VaR) and expected shortfall. Indeed, expectiles are the only elicitable law-invariant coherent risk measures. After …

investment returns and risk, provide an attractive and effective alternative to traditional guaranteed life annuity products …. While longevity risk sharing in pooled annuities has received recent attention, incorporating investment risk beyond fixed …, while reducing pooled annuity income volatility and downside risk, as well as an investment strategy that reduces exposure …

risky, motivating us to manage their risk. In this paper, we aimed to forecast the risk of Decentraland's MANA and Theta … combination with Bitcoin. To measure their risk, we proposed a modified aggregate risk measure (AggM) defined as a convex … combination of aggregate value-at-risk (AggVaR) and aggregate expected shortfall (AggES). To capture their dependence, we employed …

The present study aims at modelling market risk for four commodities, namely West Texas Intermediate (WTI) crude oil …, natural gas, gold and corn for the period 2007-2017. To this purpose, we use Extreme Value Theory (EVT) together with a set of … Conditional Auto-Regressive Logit (CARL) models to predict risk measures for the futures return series of the considered …

We introduce a neural network approach for assessing the risk of a portfolio of assets and liabilities over a given … value-at-risk and expected shortfall, but the approach also works for other risk measures. …

and risk prevention as this trend continues. In this paper, we convert natural disaster losses to the year 2016 dollars … outperforms the other two composite distributions in modeling natural disaster losses. Important risk measures for natural …

risk model CreditRisk+. This allows exact risk aggregation via an efficient numerically stable Panjer recursion algorithm …. Furthermore, the model allows exact (without Monte Carlo simulation error) calculation of risk measures and their sensitivities … with respect to model parameters for P&L distributions such as value-at-risk and expected shortfall. Numerous examples …

opportunities while also introducing new risks. The aim of this study is to investigate the relationship between risk and return in … any dynamic link between risk and return in the Indian fintech market. The variance-based Mean-GARCH (GARCH-M) model was … used to determine whether there is a dynamic link between risk and return in the Indian fintech market. The findings …