Two main axiomatically based risk measures are the coherent risk measure, which assumes subadditivity for random variables, and the insurance risk measure, which assumes additivity for comonotonic random variables. We propose a new, data based, risk measure, called natural risk statistic, that is characterized by a new set of axioms. The new axioms only require subadditivity for comonotonic ran...

Risk analysis and management currently have a strong presence in financial institutions, where high performance and energy efficiency are key requirements for acceleration systems, especially when it comes to intraday analysis. In this regard, we approach the estimation of the widely-employed portfolio risk metrics value-at-risk (VaR) and conditional value-at-risk (cVaR) by means of nested Mont...

We study the optimal portfolio allocation problem from a Bayesian perspective using value at risk (VaR) and conditional (CVaR) as measures. By applying posterior predictive distribution for future return, we derive relevant quantities needed in computations of VaR CVaR, express weights terms observed data only. This is contrast to conventional method where solution based on unobserved which are...

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 ...

Abstract To examine the familiar tradeoff between risk and return in financial investments, we use a rolling two-stage stochastic program to compare mean-risk optimization models with time series momentum strategies. In backtest of allocating investment market index risk-free asset, generate scenarios future according momentum-based process model. A new hybrid approach, strategy controlling dow...

This article studies a model for risk aversion when designing flexible capacity expansion plan multi-facility system. In this setting, the decision maker can dynamically expand of each facility given observations uncertain demand. We situation as multi-stage stochastic programming problem, and we express through Conditional Value-at-Risk (CVaR) mean-CVaR objective. optimize problem over tractab...

Several polyhedral risk measures have been recently introduced leading to Linear Programming (LP) models for portfolio optimization. In this paper we study LP solvable portfolio optimization models based on the tail Gini’s mean difference risk measurement. We use combinations of the Conditional Value at Risk (CVaR) measures to get some approximations to the tail Gini’s mean difference with the ...

On the condition that both futures and options exist in the markets for hedging, this paper examines the optimal hedging strategy under price risk and background risk. Compared with the previous research, which has studied options hedging against basis risk and production risk being extended to options and futures hedging against price risk and background risk, we proposed a model and have take...