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Fuzzy modeling has many advantages over the non-fuzzy methods, such as robustness against uncertainties and less sensitivity to the varying dynamics of nonlinear systems. Data-driven fuzzy modeling needs to extract fuzzy rules from the…

Systems and Control · Computer Science 2018-06-08 Erick de la Rosa , Wen Yu

In a data matrix, we may distinguish between cases, each represented by a row vector for a statistical unit, and cells, which correspond to single entries of the data matrix. Recent developments in Robust Statistics have introduced the…

This paper shows that the fuzzy temporal logic can model figures of thought to describe decision-making behaviors. In order to exemplify, some economic behaviors observed experimentally were modeled from problems of choice containing time,…

Artificial Intelligence · Computer Science 2019-02-18 José Cláudio do Nascimento

A common problem in formulating models for the relative risk and risk difference is the variation dependence between these parameters and the baseline risk, which is a nuisance model. We address this problem by proposing the conditional log…

Methodology · Statistics 2016-11-21 Thomas S. Richardson , James M. Robins , Linbo Wang

This paper proposes two mixed models to study a consumer's optimal saving in the presence of two types of risk.

General Finance · Quantitative Finance 2017-06-26 Irina Georgescu , Adolfo Cristóbal Campoamor , Ana Maria Lucia Casademunt

We study an optimal investment problem under default risk where related information such as loss or recovery at default is considered as an exogenous random mark added at default time. Two types of agents who have different levels of…

Pricing of Securities · Quantitative Finance 2017-03-02 Ying Jiao , Idris Kharroubi

We introduce a general theory of epistemic random fuzzy sets for reasoning with fuzzy or crisp evidence. This framework generalizes both the Dempster-Shafer theory of belief functions, and possibility theory. Independent epistemic random…

Artificial Intelligence · Computer Science 2024-05-08 Thierry Denoeux

Possibility and probability theories are alternative and complementary ways to deal with uncertainty, which has motivated over the last years an interest for the study of ways to transform probability distributions into possibility…

Other Statistics · Statistics 2020-01-03 Esteve del Acebo , Yousef Alizadeh-Q , Sayyed Ali Hossayni

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

In this paper, we consider a risk-based optimal investment problem of an insurer in a regime-switching jump diffusion model with noisy memory. Using the model uncertainty modeling, we formulate the investment problem as a zero-sum,…

Portfolio Management · Quantitative Finance 2019-03-25 Rodwell Kufakunesu , Calisto Guambe , Lesedi Mabitsela

We give a geometrically motivated measure of skewness, define a mean value triangle number, and dispersion (in that order) of a fuzzy number without reference or seeking analogy to the namesake but parallel concepts in probability theory.…

Other Statistics · Statistics 2020-11-03 Jan Schneider

We show that under plausible levels of background risk, no theory of choice under risk -- such as expected utility theory, prospect theory, or rank dependent utility -- can simultaneously satisfy the following three economic postulates: (i)…

Theoretical Economics · Economics 2021-03-09 Xiaosheng Mu , Luciano Pomatto , Philipp Strack , Omer Tamuz

The optimal allocation of assets has been widely discussed with the theoretical analysis of risk measures, and pessimism is one of the most attractive approaches beyond the conventional optimal portfolio model. The $\alpha$-risk plays a…

Portfolio Management · Quantitative Finance 2024-05-20 Sungchul Hong , Jong-June Jeon

This paper proposes two kinds of fuzzy abductive inference in the framework of fuzzy rule base. The abductive inference processes described here depend on the semantic of the rule. We distinguish two classes of interpretation of a fuzzy…

Artificial Intelligence · Computer Science 2007-05-23 Nedra Mellouli , Bernadette Bouchon-Meunier

Statistical jump models have been recently introduced to detect persistent regimes by clustering temporal features and discouraging frequent regime changes. However, they are limited to hard clustering and thereby do not account for…

Methodology · Statistics 2025-10-01 Federico P. Cortese , Antonio Pievatolo , Elisa Maria Alessi

The research interest of this paper is focused on the efficient clustering task for an arbitrary color data. In order to tackle this problem, we have tried to model the inherent uncertainty and vagueness of color data using fuzzy color…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Dae-Won Kim , Kwang H. Lee

In this paper, we revisit the portfolio optimization problems of the minimization/maximization of investment risk under constraints of budget and investment concentration (primal problem) and the maximization/minimization of investment…

Portfolio Management · Quantitative Finance 2018-01-17 Daichi Tada , Hisashi Yamamoto , Takashi Shinzato

In this paper, we discuss the ambiguous chance constrained based portfolio optimization problems, in which the perturbations associated with the input parameters are stochastic in nature, but their distributions are not known precisely. We…

Optimization and Control · Mathematics 2023-11-09 Pulak Swain , Akshay Kumar Ojha

Portfolio selection involves optimizing simultaneously financial goals such as risk, return and Sharpe ratio. This problem holds considerable importance in economics. However, little has been studied related to the nonconvexity of the…

Optimization and Control · Mathematics 2023-05-02 Vuong D. Nguyen , Nguyen Kim Duyen , Nguyen Minh Hai , Bui Khuong Duy

The expected utility operators introduced in a previous paper, offer a framework for a general risk aversion theory, in which risk is modelled by a fuzzy number $A$. In this paper we formulate a coinsurance problem in the possibilistic…

Mathematical Finance · Quantitative Finance 2019-08-20 Irina Georgescu