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Kim, Kim, and Neggers (2019) defined probability functions on a poset, by listing some very natural conditions that a function \(\pi: P \times P \to [0,1]\) should satisfy in order to capture the intuition of "the likelihood that \(a\)…

Combinatorics · Mathematics 2025-02-05 Jan Snellman

We are studying here a family of probability density functions indexed by a real parameter, and constructed from homographic relations between associated Stieltjes transforms. From the analysis of orthogonal polynomials we deduce a family…

Classical Analysis and ODEs · Mathematics 2011-05-12 Roland Groux

Employing two models, we show that various counting functions of a random variable defined by restriction or contraction of a ranked set with multiplicity (e.g., classical and arithmetic matroids) have expectations given by the…

Combinatorics · Mathematics 2020-03-17 Tan Nhat Tran

Here we develop an option pricing method based on Legendre series expansion of the density function. The key insight, relying on the close relation of the characteristic function with the series coefficients, allows to recover the density…

Mathematical Finance · Quantitative Finance 2017-03-21 Julien Hok , Tat Lung Chan

A mode of a probability vector is a local maximum with respect to some vicinity structure on the set of elementary events. The mode inequalities cut out a polytope from the simplex of probability vectors. Related to this is the concept of…

Combinatorics · Mathematics 2015-03-03 Guido Montufar , Johannes Rauh

We propose a refinement of the random matrix model for a certain family of $L$-functions over $\mathbb F_q[u]$, using techniques that we hope will eventually apply to an arbitrary family of $L$-functions. This consists of a probability…

Number Theory · Mathematics 2024-09-05 Will Sawin

An unconstrained nonlinear binary optimization problem of selecting a maximum expected value subset of items is considered. Each item is associated with a profit and probability. Each of the items succeeds or fails independently with the…

Computational Complexity · Computer Science 2017-06-23 Noam Goldberg , Gabor Rudolf

The research problem in this work is the relaxation of maximizing non-negative submodular plus modular with the entire real number domain as its value range over a family of down-closed sets. We seek a feasible point $\mathbf{x}^*$ in the…

Data Structures and Algorithms · Computer Science 2022-04-13 Xin Sun , Chenchen Wu , Dachuan Xu , Yang Zhou

We consider the problem of approximation of density functions which is important in the theory of pricing of basket options. Our method is well adopted to the multidimensional case. Observe that implementations of polynomial and spline…

Statistics Theory · Mathematics 2014-04-08 Alexander Kushpel

Mathematical psychology has a long tradition of modeling probabilistic choice via distribution-free random utility models and associated random preference models. For such models, the predicted choice probabilities often form a bounded and…

Optimization and Control · Mathematics 2017-10-10 Clintin P. Davis-Stober , Jean-Paul Doignon , Samuel Fiorini , François Glineur , Michel Regenwetter

We construct a 2-parameter family of 4-dimensional polytopes with extreme combinatorial structure: In this family, the ``fatness'' of the f-vector gets arbitrarily close to 9, the ``complexity'' (given by the flag vector) gets arbitrarily…

Metric Geometry · Mathematics 2007-05-23 Günter M. Ziegler

We use the notions of reflexivity and of reflexive dimensions in order to introduce probability measures for lattice polytopes and initiate the investigation of their statistical properties. Examples of applications to discrete geometry…

Algebraic Geometry · Mathematics 2008-09-12 Maximilian Kreuzer

In this paper we consider an aggregation model f: X1 x ... x Xn --> Y for arbitrary sets X1, ..., Xn and a finite distributive lattice Y, factorizable as f(x1, ..., xn) = p(u1(x1), ..., un(xn)), where p is an n-variable lattice polynomial…

Rings and Algebras · Mathematics 2011-10-11 Miguel Couceiro , Tamás Waldhauser

Parameter estimation in HEP experiments often involves Monte-Carlo simulation to model the experimental response function. A typical application are forward-folding likelihood analyses with re-weighting, or time-consuming minimization…

Data Analysis, Statistics and Probability · Physics 2018-06-12 Thorsten Glüsenkamp

Motivated by numerical methods for solving parametric partial differential equations, this paper studies the approximation of multivariate analytic functions by algebraic polynomials. We introduce various anisotropic model classes based on…

Numerical Analysis · Mathematics 2020-01-17 Andrea Bonito , Ronald DeVore , Diane Guignard , Peter Jantsch , Guergana Petrova

A statistical decision problem is hidden in the core of option pricing. A simple form for the price C of a European call option is obtained via the minimum Bayes risk, R_B, of a 2-parameter estimation problem, thus justifying calling C…

Pricing of Securities · Quantitative Finance 2013-04-19 Yannis G. Yatracos

Set-membership estimation is usually formulated in the context of set-valued calculus and no probabilistic calculations are necessary. In this paper, we show that set-membership estimation can be equivalently formulated in the probabilistic…

Optimization and Control · Mathematics 2016-04-13 Alessio Benavoli , Dario Piga

In this paper we study the subset sum problem with real numbers. Starting from the given problem, we formulate a quadratic maximization problem over a polytope, P, which is eventually written as a distance maximization to a fixed point over…

Optimization and Control · Mathematics 2023-10-09 Marius Costandin

The true probability of a European call option to achieve positive return is investigated under the Black-Scholes model. It is found that the probability is determined by those market factors appearing in the BS formula, besides the growth…

Pricing of Securities · Quantitative Finance 2009-12-31 Guanghui Huang , Jianping Wan

Previously, we have introduced a very small number of examples of what we call Ouroboros functions. Using our already established theory of Ouroboros spaces and their functions, we will provide a set of families of Ouroboros functions that…

Functional Analysis · Mathematics 2021-06-10 Nathan Thomas Provost
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