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We consider a number of generalizations of the $\beta$-extended MacMahon Master Theorem for a matrix. The generalizations are based on replacing permutations on multisets formed from matrix indices by partial permutations or derangements…

Combinatorics · Mathematics 2014-01-22 Michael P. Tuite

We study the Hull-White model for the term structure of interest rates in the presence of volatility uncertainty. The uncertainty about the volatility is represented by a set of beliefs, which naturally leads to a sublinear expectation and…

Pricing of Securities · Quantitative Finance 2021-01-28 Julian Hölzermann

We consider a generalization of the Heath Jarrow Morton model for the term structure of interest rates where the forward rate is driven by Paretian fluctuations. We derive a generalization of It\^{o}'s lemma for the calculation of a…

Other Condensed Matter · Physics 2008-12-02 Przemyslaw Repetowicz , Brian Lucey , Peter Richmond

The recent financial crisis has led to so-called multi-curve models for the term structure. Here we study a multi-curve extension of short rate models where, in addition to the short rate itself, we introduce short rate spreads. In…

Pricing of Securities · Quantitative Finance 2016-06-06 Zorana Grbac , Laura Meneghello , Wolfgang J. Runggaldier

Reduced-rank decompositions provide descriptions of the variation among the elements of a matrix or array. In such decompositions, the elements of an array are expressed as products of low-dimensional latent factors. This article presents a…

Methodology · Statistics 2010-06-01 Peter Hoff

A linear multi-factor model is one of the most important tools in equity portfolio management. The linear multi-factor models are widely used because they can be easily interpreted. However, financial markets are not linear and their…

Machine Learning · Computer Science 2019-02-01 Kei Nakagawa , Tomoki Ito , Masaya Abe , Kiyoshi Izumi

For single input single output systems, we give a refinement of the generalized chordal metric. Our metric is given in terms of coprime factorizations, but it coincides with the extension of Vinnicombe's nu-metric given in earlier work by…

Optimization and Control · Mathematics 2014-02-03 Amol Sasane

We present a list of (1+1)-dimensional second-order evolution equations all connected via a proposed generalised hodograph transformation, resulting in a tree of equations transformable to the linear second-order autonomous evolution…

Exactly Solvable and Integrable Systems · Physics 2016-09-21 Norbert Euler , Marianna Euler

The paper investigates properties of generalized Hermite-type processes that arise in non-central limit theorems for integral functionals of long-range dependent random fields. The case of increasing multidimensional domain asymptotics is…

Probability · Mathematics 2020-10-06 Illia Donhauzer , Andriy Olenko

Several fundamental and closely interconnected issues related to factor models are reviewed and discussed: dynamic versus static loadings, rate-strong versus rate-weak factors, the concept of weakly common component recently introduced by…

Econometrics · Economics 2025-05-06 Matteo Barigozzi , Marc Hallin

Hermite subdivision schemes act on vector valued data that is not only considered as functions values in $\mathbb{R}^r$, but as consecutive derivatives, which leads to a mild form of level dependence of the scheme. Previously, we have…

Numerical Analysis · Mathematics 2018-03-15 Jean-Louis Merrien , Tomas Sauer

We derive necessary and sufficient conditions for an Ore extension of a Hopf algebra to have a Hopf algebra structure of a certain type. This construction generalizes the notion of Hopf-Ore extension, called a generalized Hopf-Ore…

Rings and Algebras · Mathematics 2018-01-03 Lan You , Zhen Wang , Huixiang Chen

This paper offers a new class of models of the term structure of interest rates. We allow each instantaneous forward rate to be driven by a different stochastic shock, constrained in such a way as to keep the forward rate curve continuous.…

Statistical Mechanics · Physics 2008-12-02 P. Santa-Clara , D. Sornette

We propose a multivariate generative model to capture the complex dependence structure often encountered in business and financial data. Our model features heterogeneous and asymmetric tail dependence between all pairs of individual…

Machine Learning · Computer Science 2025-12-10 Xiangqian Sun , Xing Yan , Qi Wu

A cohomology theory, associated to a $n$-Lie algebra and a representation space of it, is introduced. It is observed that this cohomology theory is qualified to encode the generalized derivation extensions, and that it coincides, for $n=3$,…

Rings and Algebras · Mathematics 2021-04-20 B. Ateşli , O. Esen , S. Sütlü

This paper introduces Hom-type analogues of affine algebraic structures, termed Hom-affgebras. Extending Brzezi\'nski's theory of affgebras and the Hom-algebra framework developed by Hartwig-Larsson-Silvestrov, we define and study…

Rings and Algebras · Mathematics 2025-11-06 Tarik Anowar , Ripan Saha

The infrared problem of the effective action in 2D is discussed in the framework of the Covariant Perturbation Theory. The divergences are regularised by a mass and the leading term is evaluated up to the third order of perturbation theory.…

General Relativity and Quantum Cosmology · Physics 2009-01-07 D. Hofmann , W. Kummer

We extend the now classic structural credit modeling approach of Black and Cox to a class of "two-factor" models that unify equity securities such as options written on the stock price, and credit products like bonds and credit default…

Pricing of Securities · Quantitative Finance 2011-10-27 Thomas R. Hurd , Zhuowei Zhou

This paper proposes a class of parametric multiple-index time series models that involve linear combinations of time trends, stationary variables and unit root processes as regressors. The inclusion of the three different types of time…

Econometrics · Economics 2021-11-04 Chaohua Dong , Jiti Gao , Bin Peng , Yundong Tu

Approximate Bayesian inference for neural networks is considered a robust alternative to standard training, often providing good performance on out-of-distribution data. However, Bayesian neural networks (BNNs) with high-fidelity…

Machine Learning · Computer Science 2021-12-07 Pavel Izmailov , Patrick Nicholson , Sanae Lotfi , Andrew Gordon Wilson
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