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Complex risk is a critical factor for both intelligent systems and risk management. In this paper, we consider a special class of risk statistics, named complex risk statistics. Our result provides a new approach for addressing complex…

Risk Management · Quantitative Finance 2020-12-01 Fei Sun , Yichuan Dong

Multivariate regular variation plays a role assessing tail risk in diverse applications such as finance, telecommunications, insurance and environmental science. The classical theory, being based on an asymptotic model, sometimes leads to…

Probability · Mathematics 2011-08-31 Bikramjit Das , Abhimanyu Mitra , Sidney Resnick

This paper is concerned with cost optimization of an insurance company. The surplus of the insurance company is modeled by a controlled regime switching diffusion, where the regime switching mechanism provides the fluctuations of the random…

Optimization and Control · Mathematics 2016-08-02 Chao Zhu

Diversification of an investment into independently fluctuating assets reduces its risk. In reality, movement of assets are are mutually correlated and therefore knowledge of cross--correlations among asset price movements are of great…

Statistical Mechanics · Physics 2009-11-07 B. Rosenow , V. Plerou , P. Gopikrishnan , H. E. Stanley

Regulatory requirements dictate that financial institutions must calculate risk capital (funds that must be retained to cover future losses) at least annually. Procedures for doing this have been well-established for many years, but recent…

Computational Finance · Quantitative Finance 2017-05-22 Peter Mitic

Consider an investor trading dynamically to maximize expected utility from terminal wealth. Our aim is to study the dependence between her risk aversion and the distribution of the optimal terminal payoff. Economic intuition suggests that…

General Finance · Quantitative Finance 2011-09-15 Mathias Beiglboeck , Johannes Muhle-Karbe , Johannes Temme

Hidden regular variation is a sub-model of multivariate regular variation and facilitates accurate estimation of joint tail probabilities. We generalize the model of hidden regular variation to what we call hidden domain of attraction. We…

Probability · Mathematics 2011-10-05 Abhimanyu Mitra , Sidney I. Resnick

The paper is devoted to the study of the twice epi-differentiablity of extended-real-valued functions, with an emphasis on functions satisfying a certain composite representation. This will be conducted under the parabolic regularity, a…

Optimization and Control · Mathematics 2020-04-15 Ashkan Mohammadi , M. Ebrahim Sarabi

We develop a cutting-plane methodology that adjusts solutions to optimization problems so as to reduce features that bring about exposure to risk, such as concentration of assets or resources. The methodology is agnostic to the…

Optimization and Control · Mathematics 2026-05-28 Daniel Bienstock , Blake Sisson

Distributional regression aims at estimating the conditional distribution of a targetvariable given explanatory co-variates. It is a crucial tool for forecasting whena precise uncertainty quantification is required. A popular methodology…

Statistics Theory · Mathematics 2024-11-22 Clément Dombry , Ahmed Zaoui

We expose a theoretical hedging optimization framework with variational preferences under convex risk measures. We explore a general dual representation for the composition between risk measures and utilities. We study the properties of the…

Mathematical Finance · Quantitative Finance 2024-10-11 Marcelo Righi

A new framework for portfolio diversification is introduced which goes beyond the classical mean-variance approach and portfolio allocation strategies such as risk parity. It is based on a novel concept called portfolio dimensionality that…

Portfolio Management · Quantitative Finance 2019-09-23 Mathias Barkhagen , Brian Fleming , Sergio Garcia Quiles , Jacek Gondzio , Joerg Kalcsics , Jens Kroeske , Sotirios Sabanis , Arne Staal

The paper is devoted to a comprehensive study of composite models in variational analysis and optimization the importance of which for numerous theoretical, algorithmic, and applied issues of operations research is difficult to overstate.…

Optimization and Control · Mathematics 2019-12-10 Ashkan Mohammadi , Boris S. Mordukhovich , M. Ebrahim Sarabi

Many physical phenomena, governed by partial differential equations (PDEs), are second order in nature. This makes sense to pose the control on the second order derivatives of the field solution, in addition to zero and first order ones, to…

Optimization and Control · Mathematics 2010-10-11 Rouhollah Tavakoli

Most classification methods provide either a prediction of class membership or an assessment of class membership probability. In the case of two-group classification the predicted probability can be described as "risk" of belonging to a…

Machine Learning · Statistics 2011-10-28 Yizhar Toren

We study combinations of risk measures under no restrictive assumption on the set of alternatives. We develop and discuss results regarding the preservation of properties and acceptance sets for the combinations of risk measures. One of the…

Mathematical Finance · Quantitative Finance 2023-05-09 Marcelo Brutti Righi

Variational convexity, together with ist strong counterpart, of extended-real-valued functions has been recently introduced by Rockafellar. In this paper we present second-order characterizations of these properties, i.e., conditions using…

Optimization and Control · Mathematics 2025-02-04 Helmut Gfrerer

In recent years, the economic policy of privatization, which is defined as the transfer of property or responsibility from public sector to private sector, is one of the global phenomenon that increases use of markets to allocate resources.…

General Finance · Quantitative Finance 2008-12-02 M. Vahabi , G. R. Jafari

A first-order model for a stock market assigns to each stock a return parameter and a variance parameter that depend only on the rank of the stock. A second-order model assigns these parameters based on both the rank and the name of the…

Statistical Finance · Quantitative Finance 2013-02-18 Robert Fernholz , Tomoyuki Ichiba , Ioannis Karatzas

Conditional risk minimization arises in high-stakes decisions where risk must be assessed in light of side information, such as stressed economic conditions, specific customer profiles, or other contextual covariates. Constructing reliable…

Machine Learning · Statistics 2025-09-30 Xinqiao Xie , Jonathan Yu-Meng Li