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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.

169,291 papers · 148 categories

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92185277369 · Jun 202019922001200920182026
48 results for weak order

Study on fourth order Lamm-Riviere system for biharmonic mappings in 4D.

problem Higher order regularity and sharp Holder continuity of weak solutions.
method Optimal higher order regularity and sharp Holder continuity through analysis of the Lamm-Riviere system.
result Derive weak compactness for sequences of weak solutions with uniformly bounded energy.

In this paper we discuss the possibility of using multilevel Monte Carlo (MLMC) methods for weak approximation schemes. It turns out that by means of a simple coupling between consecutive time discretisation levels, one can achieve the same complexity gain as under the presence of a strong convergence. We exemplify thi…

2014-06-10abs ↗pdf ↗

Let (W,S) be a finite rank Coxeter system with W infinite. We prove that the limit weak order on the blocks of infinite reduced words of W is encoded by the topology of the Tits boundary of the Davis complex X of W. We consider many special cases, including W word hyperbolic, and X with isolated flats. We establish tha…

2013-01-05abs ↗pdf ↗

Paper investigates conditions for independence of weak gradients on metric spaces.

problem Dependence of weak gradients on pp in arbitrary metric measure spaces.
method Investigates the Bounded Interpolation Property to ensure independence of weak gradients.
result Bounded Interpolation Property guarantees independence of weak gradients.

Study improves weak error estimates for rough volatility models.

problem Efficient numerical schemes for non-Markovian stochastic processes with rough volatility.
method Analyzes weak rates for a class of stochastic processes with rough stochastic volatility.
result Weak rate is of order min{3H+0.5, 1} for a large class of test functions.

This paper studies the Glosten Milgrom model whose risky asset value admits an arbitrary discrete distribution. Contrast to existing results on insider's models, the insider's optimal strategy in this model, if exists, is not of feedback type. Therefore a weak formulation of equilibrium is proposed. In this weak formul…

2013-10-18abs ↗pdf ↗

A new method for averaging probability distributions based on optimal weak mass transport.

problem Averaging probability distributions in a geometric way.
method Weak barycenters based on optimal weak mass transport.
result Extracts common geometric information shared by all input distributions.

Introduces weak (p,k)(p,k)-Dirac structures in geometric settings.

problem Defining and analyzing new geometric structures.
method Introducing and studying weak (p,k)(p,k)-Dirac structures in TMΛpTMTM \oplus \Lambda^pT^*M.
result Weak (p,k)(p,k)-Dirac structures contain more information than (p,k)(p,k)-Lagrangian structures.

Paper explores weak solutions' regularity in critical dimensions without conservation law.

problem Regularity of weak solutions to higher order elliptic systems in critical dimensions.
method Elementary and unified treatment, without conservation law.
result Interior Hölder continuity for solutions in critical dimensions.

Establishes a microstructural foundation for a rough log-normal volatility model.

problem Developing a robust model for financial volatility under microstructural effects.
method Introduced a sequence of order-driven financial market models with Poisson process arrivals and analyzed their convergence to a log-normal rough volatility model.
result Weak convergence of price-volatility process to a log-normal rough volatility model with established weak error rates.

Removes singularity order for Willmore immersions, reducing bubbling scenarios.

problem Understanding the singularity order of weak limits of Willmore immersions.
method Obtains removability result on singularity order, reducing bubbling scenarios.
result Only three out of twelve non-planar minimal surfaces may occur as bubbles of Willmore immersions.

Snorkel DryBell uses weak supervision to speed up machine learning model development.

problem Costly label data in machine learning applications.
method Flexible ingestion of organizational knowledge, cross-feature production serving, scalable execution.
result Comparable quality to hand-labeled models, 52% performance improvement on average.

Study on error rates for approximating rough volatility models.

problem Simulation of rough volatility models with fractional Brownian motion.
method Analysis of weak error rates for numerical schemes, focusing on fBm and cubic test functions.
result Convergence rates for approximations are (3H+12)1(3H+ \frac{1}{2}) \wedge 1 for exact left-point discretization and H+12H+\frac{1}{2} for hybrid schemes.

Following an approach of the second author for conformally invariant variational problems in two dimensions, we show in four dimensions the existence of a conservation law for fourth order systems, which includes both intrinsic and extrinsic biharmonic maps. With the help of this conservation law we prove the continuit…

2006-07-20abs ↗pdf ↗

This paper investigates higher order generalizations of well known results for Lie algebroids and bialgebroids. It is proved that nn-Lie algebroid structures correspond to nn-ary generalization of Gerstenhaber algebras and are implied by nn-ary generalization of linear Poisson structures on the dual bundle. A Nambu-…

2015-02-19abs ↗pdf ↗

Study rough volatility models using path-dependent PDEs and fractional Brownian motions.

problem Modeling and analyzing rough volatility in financial markets.
method Showed conditional expectations are unique classical solutions to path-dependent PDEs derived from functional Itô formula. Leverage these to study weak rates of convergence for discretized stochastic integrals.
result Obtained optimal weak error rates for approximating log-stock prices in rough volatility models.

Study introduces weak elastic energy for curves on Riemannian surfaces.

problem Detecting curvature of curves on Riemannian surfaces.
method Relaxation starting from inscribed geodesic polygonals, defined in normalized isothermal coordinates.
result Relaxed energy detects intrinsic second-order Sobolev regularity and agrees with geodesic curvature.

Improved accuracy in quantization methods for financial derivatives.

problem Efficient numerical methods for evaluating functionals of stochastic differential equations.
method Recursive Marginal Quantization of higher-order schemes (Euler, Milstein, simplified weak order 2.0).
result Higher-order schemes provide improved weak order convergence and accurate marginal distributions.

The paper defines weak lower scalar curvature bounds for C0C^0 metrics and shows their stability under Ricci flow.

problem Defining and proving stability of weak lower scalar curvature bounds for metrics with low regularity.
method Proposes local definitions of weak lower scalar curvature bounds for C0C^0 metrics, shows stability under perturbation, and defines a Ricci flow for C0C^0 initial data.
result Weak lower scalar curvature bounds are preserved under Ricci flow from C0C^0 initial data.

New algorithm for duelling bandits with weak regret in adversarial settings.

problem Improving performance in duelling bandits with weak regret.
method Developed an algorithm for duelling bandits in adversarial environments, considering the Borda winner.
result Algorithm provides theoretical guarantees in both utility-based and unrestricted settings.

Develops Poisson structures on weak Sobolev loop spaces for integrable systems.

problem Analyzing integrable systems on low regularity loop spaces.
method Extending Mokhov's constructions to weak Sobolev spaces, constructing presymplectic and Poisson structures.
result Valid Poisson structures and deformations for weak Sobolev loops, extending Hamiltonian formalisms.

Weak correlations explain linear dynamics in deep learning models.

problem Understanding the linear structure in gradient-based learning algorithms.
method Characterization of weak correlations between derivatives and parameters.
result Weak correlations are the underlying principle for linearization in deep learning models.

Study on Kähler manifolds proves weak decompositions and relates harmonic forms.

problem Analyzing harmonic forms on Kähler manifolds.
method Proves weak W1,2W^{1,2} Bott-Chern and Dolbeault decompositions.
result Strict relation between W1,2W^{1,2} Bott-Chern harmonic forms and the W1,2W^{1,2} Bott-Chern decomposition.

Characterizes preferences for decision-making under uncertainty using a leader-follower game model.

problem Decision-making under uncertainty and ambiguity aversion.
method Characterizes niveloidal preferences through a leader-follower game model, satisfying specific axioms.
result The leader's strategy space can serve as an ambiguity aversion index.

A new machine learning method solves high-dimensional Kolmogorov PDEs efficiently.

problem Solving high-dimensional Kolmogorov PDEs and SDEs.
method Stochastic weighted minimization and stochastic gradient descent with Malliavin weights.
result Accurate approximation of high-dimensional Kolmogorov PDEs and SDEs without curse of dimensionality.

The Lebesgue property (order-continuity) of a monotone convex function on a solid vector space of measurable functions is characterized in terms of (1) the weak inf-compactness of the conjugate function on the order-continuous dual space, (2) the attainment of the supremum in the dual representation by order-continuous…

2013-05-10abs ↗pdf ↗

We consider spaces of smooth immersed plane curves (modulo translations and/or rotations), equipped with reparameterization invariant weak Riemannian metrics involving second derivatives. This includes the full H2H^2-metric without zero order terms. We find isometries (called RR-transforms) from some of these spaces i…

2013-11-14abs ↗pdf ↗

Efficient simulation scheme for rough Heston model reduces computational cost.

problem Accurate and efficient simulation of the rough Heston model for option pricing.
method Weak simulation scheme based on Markovian approximations of the rough Heston process.
result The new scheme exhibits second order weak convergence with linear computational cost.

In usual stochastic volatility models, the process driving the volatility of the asset price evolves according to an autonomous one-dimensional stochastic differential equation. We assume that the coefficients of this equation are smooth. Using Itô's formula, we get rid, in the asset price dynamics, of the stochastic i…

2009-08-13abs ↗pdf ↗

Self-test loss functions improve data-driven modeling of weak-form operators and gradient flows.

problem Challenges in selecting test functions for data-driven modeling involving weak-form operators and gradient flows.
method Introducing self-test loss functions that depend on unknown parameters and are quadratic.
result Self-test loss functions conserve energy for gradient flows and coincide with log-likelihood ratios for stochastic differential equations.

Managing a portfolio to a risk model can tilt the portfolio toward weaknesses of the model. As a result, the optimized portfolio acquires downside exposure to uncertainty in the model itself, what we call "second order risk." We propose a risk measure that accounts for this bias. Studies of real portfolios, in asset-by…

2009-08-17abs ↗pdf ↗