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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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48 results for graded skew

Classifies objects in graded skew-gentle algebras using geometric models.

problem Classifying indecomposable objects in the derived category of graded skew-gentle algebras.
method Introduces new geometric models (punctured marked surfaces and binary surfaces) to classify objects.
result Integrates geometric models to classify objects in the derived category of graded skew-gentle algebras.

We construct the full linearisation functor which takes a graded bundle of degree kk (a particular kind of graded manifold) and produces a kk-fold vector bundle. We fully characterise the image of the full linearisation functor and show that we obtain a subcategory of kk-fold vector bundles consisting of symmetric $…

2015-12-08abs ↗pdf ↗

It is shown that the new Poisson brackets proposed in Part I of this work (J. Math. Phys. 34, 5747(hep-th/9305133)) arise naturally in an extension of the formal variational calculus incorporating divergences. The linear spaces of local functionals, evolutionary vector fields, functional forms, multi-vectors and differ…

1995-01-13abs ↗pdf ↗

In this paper we use Kuperberg's sl3\mathfrak{sl}_3-webs and Khovanov's sl3\mathfrak{sl}_3-foams to define a new algebra KSK^S, which we call the sl3\mathfrak{sl}_3-web algebra. It is the sl3\mathfrak{sl}_3 analogue of Khovanov's arc algebra. We prove that KSK^S is a graded symmetric Frobenius algebra. Furthermore, we cate…

2012-06-11abs ↗pdf ↗

Let SS be a spinor bundle of a pseudo-Euclidean vector bundle (E,g)(E,\mathrm{g}) of even rank. We introduce a new filtration on the algebra D(M,S)\mathcal{D}(M,S) of differential operators on SS. As main property, the associated graded algebra grD(M,S)\mathrm{gr}\mathcal{D}(M,S) is isomorphic to the algebra $\mathcal{O}(\mathcal…

2014-10-13abs ↗pdf ↗

A manifold is multisymplectic, or more specifically n-plectic, if it is equipped with a closed nondegenerate differential form of degree n+1. In our previous work with Baez and Hoffnung, we described how the `higher analogs' of the algebraic and geometric structures found in symplectic geometry should naturally arise i…

2010-05-13abs ↗pdf ↗

The paper defines MTCov for skewed elliptical distributions.

problem No specific problem stated, but dealing with skewed elliptical distributions.
method Defined MTCov for generalized skew-elliptical distributions and compared with skewed and non-skewed normal distributions.
result Special formula for MTCov of generalized skew-elliptical distributions.

The paper analyzes skewness and kurtosis measures for skew-elliptical distributions.

problem Examining skewness and kurtosis measures for skew-elliptical distributions.
method Deriving exact expressions for skewness and kurtosis measures for skew-elliptical distributions, constructing test statistics, and comparing measures through simulations and real data analysis.
result Exact expressions and test statistics for skewness and kurtosis measures for various skew-elliptical distributions.

The paper calculates moments and conditional risks for skewed elliptical distributions.

problem Estimating moments and tail conditional risks for skewed elliptical distributions.
method Derives explicit expressions for multivariate doubly truncated moments and conditional risks for generalized skew-elliptical distributions.
result Explicit formulas for multivariate doubly truncated moments and conditional risks are derived for various skewed elliptical distributions.

We elaborate on the recent observation that evolution for twist knots simplifies when described in terms of triangular evolution matrix B{\cal B}, not just its eigenvalues ΛΛ, and provide a universal formula for B{\cal B}, applicable to arbitrary rectangular representation R=[rs]R=[r^s]. This expression is in terms of s…

2019-02-11abs ↗pdf ↗

Proposes a method to identify elements in a skewness matrix for multivariate skew-elliptical distributions.

problem Label switching issue in Bayesian estimation of skewness matrix.
method Imposes a positive lower-triangular constraint and uses Bayesian sparse estimation with horseshoe prior.
result Successfully estimates the true structure of skewness dependency.

Study the geometry and dynamics of skew evolutes and involutes, related to bicycle kinematics.

problem Understanding the geometry and dynamics of skew evolutes and involutes.
method Investigate the skew evolute and involute maps, comparing them to bicycle kinematics.
result The skew evolute and involute maps have properties analogous to bicycle kinematics.

Study on simplicity of Lie skew braces, proving new results for compact cases.

problem Simplicity of Lie skew braces, focusing on compact connected cases.
method Reviewing correspondence, investigating ideals and rigidity, proving main result for compact Lie skew braces.
result Compact connected simple Lie skew braces are either trivial or have simple underlying Lie groups.

The geometry of graded principal bundles is discussed in the framework of graded manifold theory of Kostant-Berezin-Leites. In particular, we prove that a graded principal bundle is globally trivial if and only if it admits a global graded section and, further, that the sheaf of vertical derivations on such a bundle co…

1996-05-16abs ↗pdf ↗

A skew loop is a closed curve without parallel tangent lines. We prove: The only complete surfaces in euclidean 3-space with a point of positive curvature and no skew loops are the quadrics. In particular, ellipsoids are the only closed surfaces without skew loops. We also prove results about skew loops on cylinders an…

2002-05-21abs ↗pdf ↗

Skewness dispersion predicts future stock market returns, especially in months with monetary policy announcements.

problem Predicting future stock market returns using skewness dispersion.
method Cross-sectional analysis of firm-level realized skewness and stock market returns.
result Skewness dispersion is a significant predictor of future stock market returns, robust to various estimation methods.

We investigate aspects of Kauffman bracket skein algebras of surfaces and modules of 3-manifolds using quantum torus methods. These methods come in two flavors: embedding the skein algebra into a quantum torus related to quantum Teichmuller space, or filtering the algebra and obtaining an associated graded algebra that…

2019-10-03abs ↗pdf ↗

A skew brane is an immersed codimension 2 submanifold in affine space, free from pairs of parallel tangent spaces. Using Morse theory, we prove that a skew brane cannot lie on a quadratic hypersurface. We also prove that there are no skew loops on embedded ruled developable discs in 3-space. The paper extends recent wo…

2003-02-21abs ↗pdf ↗

This paper classifies 4D spin manifolds with skew Killing spinors.

problem Classifying 4D Riemannian spin manifolds with skew Killing spinors.
method Analyzing skew Killing spinors with skew-symmetric endomorphisms A, considering both degenerate and non-degenerate cases.
result In the degenerate case, the manifold is locally isometric to R x N with N having a skew Killing spinor.

Complete classification of quaternionic skew-Hermitian symmetric spaces found.

problem Classifying quaternionic skew-Hermitian symmetric spaces.
method Proving the existence of a torsion-free mSO(2n)mSp(1){ m SO}^{*}(2n){ m Sp}(1)-structure and showing that any homogeneous space is symmetric.
result A complete classification of quaternionic skew-Hermitian symmetric spaces for arbitrary n>1n>1.

Following recent work by Ghomi, Solomon and Tabachnikov, we study geometry and topology of skew branes. A skew brane is a codimension 2 submanifold in affine space such that the tangent spaces at any pair of distinct points are not parallel. We prove that if an oriented closed manifold has a non-zero Euler characterist…

2005-04-23abs ↗pdf ↗

A parsimonious model reduces over-parameterization in skewed matrix variate mixtures.

problem Over-parameterization in skewed matrix variate mixtures.
method Parsimonious family of 256 models using bilinear factor analyzers constrained over clusters, with AECM algorithm for estimation.
result Extensive simulations and real-world datasets (MNIST, Olivetti faces) demonstrate the method's effectiveness.

We review the concept of a graded bundle as a natural generalisation of a vector bundle. Such geometries are particularly nice examples of more general graded manifolds. With hindsight there are many examples of graded bundles that appear in the existing literature. We start with a discussion of graded spaces, passing …

2016-05-11abs ↗pdf ↗

This paper develops a theory of graded manifolds in differential geometry.

problem Defining consistent global descriptions of graded manifolds with mixed graded coordinates.
method Using sheaves of graded commutative associative algebras on topological spaces.
result Resolved known issues in the definition of graded manifolds, especially those involving mixed graded coordinates.

Optimizes option portfolios for skewed-t returns using VaR and variance measures.

problem Optimizing portfolios for skewed-t returns with heavy tails and skewness.
method Uses variance and VaR measures, departing from normal returns, and provides explicit portfolio weights.
result Optimal portfolio weights differ significantly from variance optimal weights due to skewness.

Graded Transformers embed algebraic structure in neural networks through graded transformations.

problem Efficiently modeling hierarchical and structured data in neural networks.
method Introduces Linearly Graded Transformer (LGT) and Exponentially Graded Transformer (EGT) with graded scaling operators.
result Establishes rigorous guarantees and improved efficiency for structured data.

The paper improves asset allocation using a skew-normal distribution in the Black-Litterman model.

problem Improving asset allocation under skewed return distributions.
method Using the Black-Litterman model with hidden truncation skew-normal distribution and Simaan's three-moment risk model.
result Optimal portfolios have less risk and higher skewness compared to classical BL model.

This paper aims at setting out the basics of Z\mathbb{Z}-graded manifolds theory. We introduce Z\mathbb{Z}-graded manifolds from local models and give some of their properties. The requirement to work with a completed graded symmetric algebra to define functions is made clear. Moreover, we define vector fields and ex…

2015-12-09abs ↗pdf ↗

A new clustering method for functional data using skewed distributions.

problem Clustering functional data with skewed distributions.
method Mixtures of functional linear regression models and three skewed multivariate distributions (variance-gamma, skew-t, normal-inverse Gaussian).
result The proposed method funWeightClustSkew performs well on simulated and real data.