1 citations · 2 across the 6 of their papers we have counts for
8 papers
Divergence Based Quadrangle and Applications
Anton Malandii, Siddhartha Gupte, Cheng Peng +1
This paper introduces a novel framework for assessing risk and decision-making in the presence of uncertainty, the \emph{-Divergence Quadrangle}. This approach expands upon the…
Expectile Quadrangle and Applications
Viktor Kuzmenko, Anton Malandii, Stan Uryasev
The paper explores the concept of the \emph{expectile risk measure} within the framework of the Fundamental Risk Quadrangle (FRQ) theory. According to the FRQ theory, a quadrangle…
Mixture Quantiles Estimated by Constrained Linear Regression
Cheng Peng, Yizhou Li, Stan Uryasev
We study the problem of modeling univariate distributions via their quantile functions. We introduce a flexible family of distributions whose quantile function is a linear combinat…
Factor Model of Mixtures
Cheng Peng, Stanislav Uryasev
This paper proposes a new approach to estimating the distribution of a response variable conditioned on observing some factors. The proposed approach possesses desirable properties…
Support Vector Regression: Risk Quadrangle Framework
Anton Malandii, Stan Uryasev
This paper investigates Support Vector Regression (SVR) within the framework of the Risk Quadrangle (RQ) theory. Every RQ includes four stochastic functionals -- error, regret, ris…
Portfolio Optimization with Expectile and Omega Functions
Alexander Wagner, Stan Uryasev
This paper proves equivalences of portfolio optimization problems with negative expectile and omega ratio. We derive subgradients for the negative expectile as a function of the po…
Calculating CVaR and bPOE for Common Probability Distributions With Application to Portfolio Optimization and Density Estimation
Matthew Norton, Valentyn Khokhlov, Stan Uryasev
Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR), also called the superquantile and quantile, are frequently used to characterize the tails of probability distribution's an…
Yet Another Convex Sets Subtraction with Application in Nondifferentiable Optimization
Evgeni Nurminski, Stan Uryasev
This paper introduces a new subtraction operation for convex sets, which defines their difference as a collection of inclusion-minimal convex sets with appropriate definitions of l…