New method models portfolios with leptokurtic risk factors using Gram-Charlier expansions.
arXiv research
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The study of pseudo-Anosov maps with minimum expansion factor using train tracks.
Random walks on free groups reveal asymmetric expansion factors.
Factorization of DE coefficients is violated in antiparallel triple pretzels, but described elegantly.
Geodesic flows on compact manifolds without conjugate points are shown to have a unique measure of maximal entropy.
In this paper we are interested in term structure models for pricing zero coupon bonds under rapidly oscillating stochastic volatility. We analyze solutions to the generalized Cox-Ingersoll-Ross two factors model describing clustering of interest rate volatilities. The main goal is to derive an asymptotic expansion of …
Analyzes the differential expansion of knot polynomials, focusing on its applicability and modifications.
Density expansions for hypoelliptic diffusions are revisited. In particular, we are interested in density expansions of the projection , at time , with . Global conditions are found which replace the well-known "not-in-cutlocus" condition known from heat-kernel asymptot…
Geodesic flows on certain surfaces are shown to be semi-conjugate to expansive flows.
New method recovers signals from compressed measurements using generative networks with contractive layers.
New formulas derived for lattice crossing coefficients, improving computation efficiency.
Improved MUSE boosts performance and reduces error in Bayesian inference.
Factorization of the differential expansion coefficients for HOMFLY-PT polynomials of double braids, discovered in arXiv:1606.06015 in the case of rectangular representations , is extended to the first non-rectangular representations and . This increases chances that such factorization will take p…
The Weil-Petersson and Takhtajan-Zograf metrics on the Riemann moduli spaces of complex structures for an -fold punctured oriented surface of genus in the stable range are shown here to have complete asymptotic expansions in terms of Fenchel-Nielsen coordinates at the exceptional divisors of the Knuds…
The article calculates a multiplying factor to convert rational Vassiliev invariants to integer-valued ones.
A new Lagrangian formulation of the Raychaudhuri equation in non-Riemannian geometry.
The Magnus expansion is a universal finite type invariant of pure braids with values in the space of horizontal chord diagrams. The Conway polynomial composed with the short circuit map from braids to knots gives rise to a series of finite type invariants of pure braids and thus factors through the Magnus map. We descr…
Unified theory explains housing cycle across metros, showing credit expansion impacts.
We elaborate on the recent observation that evolution for twist knots simplifies when described in terms of triangular evolution matrix , not just its eigenvalues , and provide a universal formula for , applicable to arbitrary rectangular representation . This expression is in terms of s…
Existing nonnegative matrix factorization methods focus on learning global structure of the data to construct basis and coefficient matrices, which ignores the local structure that commonly exists among data. In this paper, we propose a new type of nonnegative matrix factorization method, which learns local similarity …
In this paper, we establish a framework for the analysis of linear parabolic equations on conical surfaces and use them to study the conical Ricci flow. In particular, we prove the long time existence of the conical Ricci flow for general cone angle and show that this solution has the optimal regularity, namely, the ti…
New tests for identifying the number of latent factors in short panels with small time dimensions.
Study on future stability of FLRW spacetime solutions with decelerated expansion.
In this paper we derive a refined asymptotic expansion, near an isolated singularity, for conformally flat metrics with constant positive Q-curvature and positive scalar curvature. The condition that the metric has constant Q-curvature forces the conformal factor to satisfy a fourth order nonlinear partial differential…
Optimizes trading strategies with price impact, predictable returns, and stochastic volatility.
Continuing the quest for exclusive Racah matrices, which are needed for evaluation of colored arborescent-knot polynomials in Chern-Simons theory, we suggest to extract them from a new kind of a double-evolution -- that of the antiparallel double-braids, which is a simple two-parametric family of two-bridge knots, gene…
We consider a general one-factor short rate model, in which the instantaneous interest rate is driven by a univariate diffusion with time independent drift and volatility. We construct recursive formula for the coefficients of the Taylor expansion of the bond price and its logarithm around , where is time to m…
Paper develops a new kernel expansion method using entropic optimal features for sparse and efficient kernel approximation.
We show that, when considering the scaling factor as an affine variable, the coefficients of the asymptotic expansion of the spectral action on a (Euclidean) Robertson-Walker spacetime are periods of mixed Tate motives, involving relative motives of complements of unions of hyperplanes and quadric hypersurfaces and div…
New insights into contrastive learning reveal how projectors affect downstream performance.
We consider the problem of computing the Credit Value Adjustment ({CVA}) of a European option in presence of the Wrong Way Risk ({WWR}) in a default intensity setting. Namely we model the asset price evolution as solution to a linear equation that might depend on different stochastic factors and we provide an approxima…
Paper introduces a new method for efficient portfolio risk quantification.
Improved electricity price forecasting with NBEATSx model.
Unsupervised estimation of latent variable models is a fundamental problem central to numerous applications of machine learning and statistics. This work presents a principled approach for estimating broad classes of such models, including probabilistic topic models and latent linear Bayesian networks, using only secon…
ML models predict stock prices poorly during recessions.
Complexity helps identify sparse risk factors in asset pricing.
We propose a fast algorithm for computing the expected tranche loss in the Gaussian factor model. We test it on portfolios ranging in size from 25 (the size of DJ iTraxx Australia) to 100 (the size of DJCDX.NA.HY) with a single factor Gaussian model and show that the algorithm gives accurate results. The algorithm prop…
Paper provides Edgeworth expansions for network moments, improving accuracy of sampling distributions.
We show that, when considering the anisotropic scaling factors and their derivatives as affine variables, the coefficients of the heat kernel expansion of the Dirac-Laplacian on Bianchi IX metrics are algebro-geometric periods of motives of complements in affine spaces of unions of quadrics and hyperplanes. We …
We prove that the marginal densities of a global probability mass function in a primal normal factor graph and the corresponding marginal densities in the dual normal factor graph are related via local mappings. The mapping depends on the Fourier transform of the local factors of the models. Details of the mapping, inc…
SPIDER uses deep neural networks for streaming tensor factorization.
A Bayesian nonparametric approach for continual learning using neural networks.
We rewrite the recently proposed differential expansion formula for HOMFLY polynomials of the knot in arbitrary rectangular representation as a sum over all Young sub-diagrams of with extraordinary simple coefficients in front of the -factors. Somewhat miraculously…
We study the algebraic property of the representation of the mapping class group of a closed oriented surface of genus 2 constructed by VFR Jones [Annals of Math. 126 (1987) 335-388]. It arises from the Iwahori-Hecke algebra representations of Artin's braid group of 6 strings, and is defined over integral Laurent polyn…
We propose an affine extension of the Linear Gaussian term structure Model (LGM) such that the instantaneous covariation of the factors is given by an affine process on semidefinite positive matrices. First, we set up the model and present some important properties concerning the Laplace transform of the factors and th…
Rescaling expansiveness proven for k*-expansive vector fields.
Proposes efficient model for continual learning that grows model over task-specific parameters.
DSM on manifolds removes singularities and computes small-noise expansions.