A key challenge in maximizing the effectiveness of model-based design experiments for calibrating nonlinear process models is inaccurate prediction information that afforded by each new experiment. We present a novel methodology to exploit prior probability distributions model parameter estimates bi-objective optimization formulation, where conditional-value-at-risk criterion considered alongsi...

Motivated by the progress made towards incorporating robust optimization in framework of risk minimization, this work focuses on assessing practical usefulness approaches for minimization downside measures, such as Value-at-Risk (VaR) and Conditional (CVaR). Accordingly, we perform empirical analysis performance VaR CVaR models with respect to their counterparts, namely, Worst-Case CVaR, using ...

We propose a new one-parameter family of risk functions defined on portfolio return sample -paths, which is called conditional drawdown-at-risk (CDaR). These risk functions depend on the portfolio drawdown (underwater) curve considered in active portfolio management. For some value of the tolerance parameter α , the CDaR is defined as the mean of the worst % 100 ) 1 ( ∗ − α drawdowns. The CDaR ...

  Background: The incidence of ulcerative colitis (UC) is rising in populations with western-style diet, rich in fat and protein, and low in fruits and vegetables. In the present study, we aimed to evaluate the association between dietary protein intakes and the risk of developing incident UC.   Methods : Sixty two cases of UC and 124 controls were studied using country-specific food frequency ...

We compare capital requirements derived by tail conditional expectation (TCE) with those derived by tail conditional median (TCM) and find that there is no clear-cut relationship between these two measures in empirical data. Our results highlight the relevance of TCM as a robust alternative to TCE, especially for regulatory control. JEL Classification: G10, G11, G23, G29

The importance of proper tail risk management is a crucial component the investment process and conditional Value at Risk (CVaR) often used as measure. CVaR asymmetric measure that controls manages downside portfolio while symmetric measures such variance consider both upside risk. In fact, minimum promising alternative to traditional mean-variance optimization. However, there are three major c...

From the mathematical perspective considered in this tutorial, risk management is a procedure for shaping a risk distribution. Popular functions managing risk are valueat-risk (VaR) and conditional value-at-risk (CVaR). The problem of choice between VaR and CVaR, especially in financial risk management, has been quite popular in academic literature. Reasons affecting the choice between VaR and ...

Real-time coordination of distributed energy resources (DERs) is crucial for regulating the voltage profile in distribution grids. By capitalizing on a scalable neural network (NN) architecture, one can attain decentralized DER decisions to address lack real-time communications. This paper develops an advanced learning-enabled scheme by accounting potential risks associated with reactive power ...

We study robust notions of good-deal hedging and valuation under combined uncertainty about the drifts and volatilities of asset prices. Good-deal bounds are determined by a subset of risk-neutral pricing measures such that not only opportunities for arbitrage are excluded but also deals that are too good, by restricting instantaneous Sharpe ratios. A non-dominated multiple priors approach to m...