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.
Develops a novel fast bootstrap for dependent data with higher-order accuracy.
Real moment-angle manifolds of combinatorially equivalent simple polytopes are equivariantly diffeomorphic.
A new method for generating samples without training, using smoothed score matching.
Stiefel-Whitney classes of moment-angle manifolds are trivial.
Paper proposes a new Taylor moment expansion for non-linear Gaussian filtering and smoothing.
We define a moment map associated to a smooth torus action on a smooth manifold, without a two-form. We define cobordisms of such structures, allowing non compact manifolds as long as the moment maps are proper. We prove that a compact manifold with a torus action and a moment map is cobordant to the disjoint union of …
Derives moments of PL networks for robust DNNs.
Kähler-Einstein metrics found on special types of symmetric varieties.
Let Phi : M --> g^* be a proper moment map associated to an action of a compact connected Lie group, G, on a connected symplectic manifold, (M,ω). A collective function is a pullback via Φof a smooth function on g^*. In this paper we present four new results about the relationship between the collective functions and t…
The paper improves generalization bounds for domain adaptation.
New SGMM algorithm for efficient estimation of moment restriction models.
Sharp inequalities in unit ball with constraints on moments.
The paper introduces new equations in Kähler geometry and proves their solutions and convexity.
Motivated by the sampling problems and heterogeneity issues common in high- dimensional big datasets, we consider a class of discordant additive index models. We propose method of moments based procedures for estimating the indices of such discordant additive index models in both low and high-dimensional settings. Our …
The paper trivializes moment maps for various geometric structures.
We investigate the probability distribution of the return intervals between successive 1-min volatilities of two Chinese indices exceeding a certain threshold . The Kolmogorov-Smirnov (KS) tests show that the two indices exhibit multiscaling behavior in the distribution of , which follows a stretched exponent…
Study on rational projective planes with small index singularities.
New method for adaptive estimation and inference in econometric models without knowing smoothness.
MOMENT selects and estimates mixed-effects models using moment identities.
Graph spectra have been successfully used to classify network types, compute the similarity between graphs, and determine the number of communities in a network. For large graphs, where an eigen-decomposition is infeasible, iterative moment matched approximations to the spectra and kernel smoothing are typically used. …
We define an equivariant index of Spin-Dirac operators on possibly noncompact manifolds, acted on by compact, connected Lie groups. The main result in this paper is that the index decomposes into irreducible representations according to the quantisation commutes with reduction principle.
New method approximates diffusion process posteriors using moment functions.
Paper provides Edgeworth expansions for network moments, improving accuracy of sampling distributions.
Post-estimation smoothing improves prediction accuracy with structural indices.
Optimizes graph spectral density learning for large networks.
Let G be a complex reductive group and K a maximal compact subgroup. If X is a smooth projective G-variety, with a fixed (not necessarily integral) K-invariant Kaehler form, then the K-action is Hamiltonian. Let M be the zero fiber of the corresponding moment map. It is well known that the quotient M/K is a complex spa…
The paper proves that Gaussian field critical points have finite moments.
In this paper we shall illustrate that each polytopal moment-angle complex can be understood as the intersection of the minima of corresponding Siegel leaves and the unit sphere, with respect to the maximum norm. Consequently, an alternative proof of a rigidity theorem of Bosio and Meersseman is obtained; as piecewise …
Dynamic Boltzmann Machine (DyBM) has been shown highly efficient to predict time-series data. Gaussian DyBM is a DyBM that assumes the predicted data is generated by a Gaussian distribution whose first-order moment (mean) dynamically changes over time but its second-order moment (variance) is fixed. However, in many fi…
For nearly every major stock market there exist equity and implied volatility indices. These play important roles within finance: be it as a benchmark, a measure of general uncertainty or a way of investing or hedging. It is well known in the academic literature, that correlations and higher moments between different i…
New real algebraic maps with prescribed images and compositions are constructed locally like moment maps.
We propose moment-based variational inference as a flexible framework for approximate smoothing of latent Markov jump processes. The main ingredient of our approach is to partition the set of all transitions of the latent process into classes. This allows to express the Kullback-Leibler divergence between the approxima…
Study nearly parallel G2-structures with torus symmetry using multi-moment maps.
The author studies regions foliated by 1D families of functions and their applications.
We propose a new indicator for technical analysis. The indicator emphasizes maximums and minimums in price series with inherent smoothing and has a potential to be useful in both mechanical trading rules and chart pattern analysis.
We present a general probabilistic perspective on Gaussian filtering and smoothing. This allows us to show that common approaches to Gaussian filtering/smoothing can be distinguished solely by their methods of computing/approximating the means and covariances of joint probabilities. This implies that novel filters and …
Realized moments of higher order computed from intraday returns are introduced in recent years. The literature indicates that realized skewness is an important factor in explaining future asset returns. However, the literature mainly focuses on the whole market and on the monthly or weekly scale. In this paper, we cond…
Paper analyzes convergence of stochastic methods under heavy-tailed noise.
We describe the basic cohomology ring of the canonical holomorphic foliation on a moment-angle manifold, LVMB-manifold or any complex manifold with a maximal holomorphic torus action. Namely, we show that the basic cohomology has a description similar to the cohomology ring of a complete simplicial toric variety due to…
Paper explores ML for UV spectra, showing transferability in chemical space.
Study the geometry of twistor spaces with rotating circle action.
Proves functions can have two indices differing by two.
Ricean channel model is widely used in wireless communications to characterize the channels with a line-of-sight path. The Ricean K factor, defined as the ratio of direct path and scattered paths, provides a good indication of the link quality. Most existing works estimate K factor based on either maximum-likelihood cr…
In this paper two portfolio choice models are studied: a purely possibilistic model, in which the return of a risky asset is a fuzzy number, and a mixed model in which a probabilistic background risk is added. For the two models an approximate formula of the optimal allocation is computed, with respect to the possibili…
A moment constraint that limits the number of dividends in the optimal dividend problem is suggested. This leads to a new type of time-inconsistent stochastic impulse control problem. First, the optimal solution in the precommitment sense is derived. Second, the problem is formulated as an intrapersonal sequential dyna…
New SQ lower bound shows complexity nearly matches known upper bound for smoothed agnostic learning.
We present a novel framework for kernel learning with sequential data of any kind, such as time series, sequences of graphs, or strings. Our approach is based on signature features which can be seen as an ordered variant of sample (cross-)moments; it allows to obtain a "sequentialized" version of any static kernel. The…
Smoothness of collapsed regions in soap films is proven, indicating wetted singularities.