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arXiv research

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.

168,695 papers · 148 categories

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48 results for width of bands

The Rosenberg index vanishes if a manifold admits a wide Riemannian band or cube-like domain.

problem Proving the Rosenberg index does not vanish for certain manifolds.
method Analyzing isometric immersions of wide Riemannian bands and cube-like domains on spin manifolds.
result Closed spin manifolds with infinite KO\mathcal{KO}-width have non-vanishing Rosenberg index.

Inspired by Gromov's work on 'Metric inequalities with scalar curvature' we establish band width inequalities for Riemannian bands of the form (V=M×[0,1],g)(V=M\times[0,1],g), where Mn1M^{n-1} is a closed manifold. We introduce a new class of orientable manifolds we call filling enlargeable and prove: If MM is filling enlargeable…

2019-11-29abs ↗pdf ↗

Develops connections between operator K-theory and positive scalar curvature.

problem Positive scalar curvature on closed spin manifolds and Gromov's band width conjecture.
method Quantitative index theory and related techniques.
result The propagation of the index of the Dirac operator is inversely related to the curvature lower bound.

The paper proves rigidity for certain product spaces and bounds for band widths.

problem Proving rigidity for product spaces and bounds for band widths.
method Combining stable weighted slicing with a spectral Dirac operator argument.
result Closed spin (Mn,g)(M^n,g) is isometrically covered by SnmimesRmS^{n-m} imes\mathbb{R}^m under certain conditions.

Extends spectral torus band inequalities for compact manifolds with scalar curvature bounds.

problem Proving upper bounds for the width of compact manifolds with boundary.
method Utilizes spacetime harmonic functions, μ-bubbles, and spinorial Callias operators.
result Generalizes Schoen-Yau black hole existence theorem to higher dimensions.

The study explores positive scalar curvature metrics on non-orientable manifolds and their covers.

problem Existence of positive scalar curvature metrics on non-orientable manifolds and their covers.
method Extends Schoen-Yau inductive descent approach to non-orientable manifolds.
result Examples of non-orientable manifolds with positive scalar curvature metrics on their orientation double covers but not on homotopy equivalent manifolds.

The paper explores rigidity theorems for spectral curvature bounds in 3-manifolds.

problem Classical rigidity results in scalar curvature geometry are extended to the spectral setting.
method Warped μμ-bubble method is systematically employed to classify stable weighted minimal hypersurfaces and establish band width estimates.
result Classification theorems and band width estimates for spectral Ricci and scalar curvatures are proven.

Develops a robust hedging valuation adjustment measure for dynamic hedging under liquidity-demand stress.

problem Dynamic hedging under liquidity-demand stress
method Define robust HVA as the worst-case expected loss over a relative-entropy neighborhood of the loss distribution generated by simulated rebalancing and maturity-unwind trades.
result Distinguishes fixed-radius convention from fixed benchmark-stress convention and shows wider no-trade bands lower rebalancing costs but raise hedge-error risk.

Paper develops a robust HVA measure for dynamic hedging under liquidity stress.

problem Valuation of dynamic hedging under liquidity stress.
method Defines robust HVA as worst-case expected loss over a relative-entropy neighborhood of loss distributions for no-trade bands.
result Wider no-trade bands lower rebalancing costs but increase hedge-error risk.

This work uses sampling theory to analyze smoothness and error bounds of finite neural networks.

problem Analyzing the function space of finite neural networks and providing error bounds.
method Applying sampling theory to finite neural networks with non-expansive activation functions, considering both deterministic and random sampling.
result Novel error bounds for univariate neural networks under band-limited input assumption, highlighting the advantage of deterministic uniform sampling.

The paper constructs optimal confidence bands for kernel gradient flow estimators.

problem Estimating generalization error and constructing confidence bands for kernel gradient flows.
method Established convergence rates and constructed optimal confidence bands under capacity-source condition.
result Optimal confidence bands for kernel gradient flows have shrinkage rates close to minimax optimal rates.

Define mass invariant for asymptotically hyperbolic 3-manifolds with toroidal infinity.

problem Define mass invariant for asymptotically hyperbolic 3-manifolds with toroidal infinity.
method Define mass invariant for asymptotically hyperbolic 3-manifolds with toroidal infinity.
result Define mass invariant for asymptotically hyperbolic 3-manifolds with toroidal infinity.

UTOPIA aggregates multiple prediction intervals efficiently.

problem Constructing optimal prediction intervals for various real-world data problems.
method UTOPIA is a universally trainable strategy using linear or convex programming.
result UTOPIA constructs prediction intervals with small average width and high coverage probability.

Let MM be a closed connected spin manifold such that its spinor Dirac operator has non-vanishing (Rosenberg) index. We prove that for any Riemannian metric on V=M×[1,1]V = M \times [-1,1] with scalar curvature bounded below by σ>0σ> 0, the distance between the boundary components of VV is at most Cn/σC_n/\sqrtσ, where $C_n = \…

2019-05-21abs ↗pdf ↗

A new pricing controller handles resource constraints to infer target prices effectively.

problem Resource constraints prevent fixed-price inference, leading to support exclusion.
method Formalizes support-exclusion failure, designs a target-aware controller, and uses a realized information clock.
result The controller can certify feasible target bands and log continuous local densities, leading to polynomial rates of inference.

The study refines known counterexamples in 4D to satisfy certain inequalities.

problem Addressing counterexamples in Gromov's and Rosenberg's conjectures.
method Analyzing simply connected and non-simply connected four manifolds up to homeomorphism.
result Gromov's and Rosenberg's conjectures hold for simply connected four manifolds up to homeomorphism.

Every link is shown to be presentable as a boundary of an unknotted flat banded surface. A (flat) banded link is defined as a boundary of an unknotted (flat) banded surface. A link's (flat) band index is defined as the minimum number of bands required to present the link as boundaries of an unknotted (flat) banded surf…

2011-04-30abs ↗pdf ↗

Consider the problem of a central bank that wants to manage the exchange rate between its domestic currency and a foreign one. The central bank can purchase and sell the foreign currency, and each intervention on the exchange market leads to a proportional cost whose instantaneous marginal value depends on the current …

2017-12-06abs ↗pdf ↗

Proves a quantitative index theorem for positive scalar curvature metrics.

problem Studying conjectures and open questions on positive scalar curvature.
method Quantitative relative index theorem and λλ-Lipschitz rigidity theorem.
result Positive answers to Gromov's open questions on scalar curvature.

The goal of this study is to explain and examine the statistical underpinnings of the Bollinger Band methodology. We start off by elucidating the rolling regression time series model and deriving its explicit relationship to Bollinger Bands. Next we illustrate the use of Bollinger Bands in pairs trading and prove the e…

2012-12-20abs ↗pdf ↗

In cellular systems, the user equipment (UE) can request a change in the frequency band when its rate drops below a threshold on the current band. The UE is then instructed by the base station (BS) to measure the quality of candidate bands, which requires a measurement gap in the data transmission, thus lowering the da…

2019-10-02abs ↗pdf ↗

We consider the problem of estimating a large rank-one tensor uk(Rn)k{\boldsymbol u}^{\otimes k}\in({\mathbb R}^{n})^{\otimes k}, k3k\ge 3 in Gaussian noise. Earlier work characterized a critical signal-to-noise ratio λBayes=O(1)λ_{Bayes}= O(1) above which an ideal estimator achieves strictly positive correlation with the unknown ve…

2017-11-15abs ↗pdf ↗

We give a short proof that if a non-trivial band sum of two knots results in a tight fibered knot, then the band sum is a connected sum. In particular, this means that any prime knot obtained by a non-trivial band sum is not tight fibered. Since a positive L-space knot is tight fibered, a non-trivial band sum never yie…

2015-09-01abs ↗pdf ↗

The paper creates nonparametric confidence bands for band-limited functions.

problem Estimating confidence bands for band-limited functions with finite samples and unknown noise.
method Uses Paley-Wiener reproducing kernel Hilbert spaces and gradient-perturbation methods.
result Non-asymptotic guarantees for confidence regions without assuming a parametric model.

New method finds arbitrage opportunities in fluctuating asset bands.

problem Finding arbitrage opportunities in fluctuating asset bands.
method Formulate as maximizing volatility within a price band, using convex-concave optimization.
result Approximately solves non-convex optimization problem for moving-band arbitrage.

Every classical knot is band-pass equivalent to the unknot or the trefoil. The band-pass class of a knot is a concordance invariant. Every ribbon knot, for example, is band-pass equivalent to the unknot. Here we introduce the long virtual knot concordance group VC\mathscr{VC}. It is shown that for every concordance cla…

2016-03-01abs ↗pdf ↗

The paper improves nonparametric confidence bands for band-limited functions.

problem Constructing nonparametric simultaneous confidence bands with nonasymptotic and distribition-free guarantees.
method Based on Paley-Wiener reproducing kernel Hilbert spaces, the paper relaxes assumptions, improves noise estimation, and tightens constraints.
result Enhanced confidence bands with improved efficiency and tighter constraints.

We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which tapers the sample covariance matrix by a Toeplitz, sparsely-banded…

2014-05-23abs ↗pdf ↗