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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.

169,051 papers · 148 categories

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131263394525 · Jun 202019922001200920182026
48 results for Finite Discrete Measure

Proves finite measure implies product structure for certain discrete subgroups.

problem Classifying discrete subgroups with finite Bowen-Margulis-Sullivan measure.
method Product structure of leafwise measures and high entropy method.
result Proves virtually a product structure for certain subgroups.

The paper studies market viability and completeness in discrete markets.

problem Characterizing the set of equivalent martingale measures in finite markets.
method Characterization as convex combinations of martingale measures, algorithm for finding these measures.
result Limitations of using discrete-time models to understand continuous-time models.

This work relaxes OT problems with marginal moments constraints, achieving finite discrete measures.

problem Solving Optimal Transport problems with marginal moments constraints.
method Relaxation of OT problems using moment constraints and Tchakaloff's theorem.
result The Moment Constrained Optimal Transport problem (MCOT) is achieved by a finite discrete measure.

The paper constructs discrete Hessian and divdiv complexes on triangulations and proves their cohomology isomorphic to continuous versions.

problem Discrete construction of Hessian and divdiv complexes on triangulations.
method Construction of discrete Hessian and divdiv complexes using finite elements and Dirac measures on triangulations.
result The cohomology of the constructed complexes is isomorphic to the continuous de Rham cohomology.

Study shows kk-NN classifier is not universally consistent on (0,1)(0,1) but consistent on discrete and specific measure spaces.

problem Consistency of kk-NN classifier under Wasserstein distance on measure spaces.
method Analysis of kk-NN classifier properties under Wasserstein distance, use of σσ-finite metric dimension, geodesic structures of Wasserstein spaces.
result Consistency of kk-NN classifier on specific measure spaces (discrete, Gaussian, wavelet series) but not on (0,1)(0,1).

We show that the mapping class group of a compact orientable surface with higher complexity has the following extreme rigidity in the sense of measure equivalence: if the mapping class group is measure equivalent to a discrete group, then they are commensurable up to finite kernel. Moreover, we describe all lattice emb…

2006-07-24abs ↗pdf ↗

Study loop ensembles on graphs, linking group theory and topology.

problem Understanding loop homotopy classes and homologies on graphs.
method Determined distributions of loop homotopy classes and homologies using the lower central series of the fundamental group.
result Distributions of loop homotopy classes and homologies defined by the lower central series of the fundamental group.

We study time-consistency questions for processes of monetary risk measures that depend on bounded discrete-time processes describing the evolution of financial values. The time horizon can be finite or infinite. We call a process of monetary risk measures time-consistent if it assigns to a process of financial values …

2004-10-21abs ↗pdf ↗

Develops non-standard analysis for coherent risk estimation.

problem Estimating coherent risk measures in financial contexts.
method Non-standard analysis, hyperfinite representations, discrete Kusuoka formulae, plug-in asymptotics.
result Uniform almost sure consistency and asymptotic normality of spectral plug-in estimators.

The new notion of maturity-independent risk measures is introduced and contrasted with the existing risk measurement concepts. It is shown, by means of two examples, one set on a finite probability space and the other in a diffusion framework, that, surprisingly, some of the widely utilized risk measures cannot be used…

2007-10-20abs ↗pdf ↗

Defines speculative bubbles in discrete-time models based on discounted stock price losing mass.

problem Characterizing speculative bubbles in discrete-time models.
method Introduces a new definition based on discounted stock price behavior and provides probabilistic characterizations.
result Speculative bubbles in discrete time are linked to solutions of a linear Volterra integral equation.

Study shows singularity of stationary measure on Furstenberg boundary for certain random walks.

problem Singularity of stationary measure on Furstenberg boundary for random walks.
method Analysis of random walks on semisimple Lie groups with specific properties.
result Stationary measure is singular to Lebesgue measure in certain cases.

Let K be an irreducible and reversible Markov kernel on a finite set X. We construct a metric W on the set of probability measures on X and show that with respect to this metric, the law of the continuous time Markov chain evolves as the gradient flow of the entropy. This result is a discrete counterpart of the Wassers…

2011-02-25abs ↗pdf ↗

Develops unbiased estimation method using underdamped Langevin dynamics.

problem Estimating expectations of non-negative Lebesgue density probability measures.
method Underdamped Langevin dynamics, time-discretized versions, doubly randomized estimation.
result Proves finite variance and expected/finite cost of the proposed estimator.

A convex projective surface is the quotient of a properly convex open ΩΩ of P(R)\mathbb{P}(\R) by a discret subgroup ΓΓ of SL3(R)\mathrm{SL}_3(\R). We give some caracterisations of the fact that a convex projective surface is of finite volume for the Busemann's measure. We deduce of this that if ΩΩ is not a triangle then …

2009-02-18abs ↗pdf ↗

We study a new notion of Ricci curvature that applies to Markov chains on discrete spaces. This notion relies on geodesic convexity of the entropy and is analogous to the one introduced by Lott, Sturm, and Villani for geodesic measure spaces. In order to apply to the discrete setting, the role of the Wasserstein metric…

2011-11-11abs ↗pdf ↗

New discrete-time model shows insider trading dynamics.

problem Modeling insider trading with discrete time and noise traders.
method Formulated as a game with three types of traders, including an insider, noise traders, and a market maker. Proved existence of sequential Kyle equilibrium for various distributions and information flows.
result Equilibria exist in mixed strategies but not in pure strategies, unlike in Kyle's original model.

We introduce Network Maximal Correlation (NMC) as a multivariate measure of nonlinear association among random variables. NMC is defined via an optimization that infers transformations of variables by maximizing aggregate inner products between transformed variables. For finite discrete and jointly Gaussian random vari…

2016-06-15abs ↗pdf ↗

We introduce the notion of volume of the representation variety of a finitely presented discrete group in a compact Lie group using the push-forward measure associated to a map defined by a presentation of the discrete group. We show that the volume thus defined is invariant under the Andrews-Curtis moves of the genera…

2002-12-01abs ↗pdf ↗

A new method uses normalizing flows to approximate optimal transport between empirical distributions.

problem Learning an optimal transport map between two empirical distributions.
method Relaxing the Monge formulation of optimal transport, using normalizing flows to approximate the solution.
result The method provides a good approximation of the true optimal transport.

The paper analyzes Laplace learning for Gaussian measure data in infinite dimensions, proving convergence.

problem Analyzing Laplace learning for infinite-dimensional Gaussian measure data.
method Minimizes Dirichlet energy on a graph constructed from the full dataset.
result Proves pointwise convergence of the graph Dirichlet energy for Gaussian measure data.

Recently, Ross showed that it is possible to recover an objective measure from a risk-neutral measure. His model assumes that there is a finite-state Markov process X that drives the economy in discrete time. Many authors extended his model to a continuous-time setting with a Markov diffusion process X with state space…

2014-10-08abs ↗pdf ↗

Study stationary measures and orbit closures for non-abelian actions on surfaces.

problem Classify stationary measures and orbit closures for non-abelian action on a surface.
method Use a finite verifiable average growth condition and results from Brown and Rodriguez Hertz.
result Show that under certain conditions, the only nonatomic stationary measure is the given smooth invariant measure, and every orbit closure is either finite or dense.

Estimates discontinuous optimal transport maps between a discrete and continuous distribution.

problem Estimating discontinuous optimal transport maps between a discrete and continuous distribution.
method Entropic optimal transport estimator, computationally efficient.
result The estimator converges at the minimax-optimal rate n1/2n^{-1/2} in the semi-discrete setting.

Framework for robust control under model uncertainty, improving financial derivatives hedging.

problem Model uncertainty in financial derivatives hedging.
method Dynamic programming principle for solving one-step optimization problems.
result Robust hedging strategy outperforms model-based strategies during adverse scenarios.

The article presents a general discrete time dividend valuation model when the dividend growth rate is a general continuous variable. The main assumption is that the dividend growth rate follows a discrete time semi-Markov chain with measurable space. The paper furnishes sufficient conditions that assure finiteness of …

2016-05-09abs ↗pdf ↗

A method for vectorizing persistence diagrams simplifies topological data analysis.

problem Challenges in integrating persistence diagrams into machine learning pipelines.
method Quantized Persistence and Integral transforms of Diagrams (Qupid) using binning and discrete transforms.
result Qupid preserves highly competitive performances compared to state-of-the-art methods across various classification tasks.

The paper analyzes rates for a modified gradient descent method using Stein variational gradients.

problem Improving the accuracy of gradient descent methods for complex target distributions.
method Derives finite-particle rates for regularized Stein variational gradient descent (R-SVGD).
result Establishes explicit non-asymptotic bounds for time-averaged empirical measures.

In this paper a finite discrete time market with an arbitrary state space and bid-ask spreads is considered. The notion of an equivalent bid-ask martingale measure (EBAMM) is introduced and the fundamental theorem of asset pricing is proved using (EBAMM) as an equivalent condition for no-arbitrage. The Cox-Ross-Rubinst…

2014-07-12abs ↗pdf ↗

In this paper it is shown that the space of tight geodesic segments connecting any two vertices in a complex of cycles has finite, uniformly bounded dimension. The dimension is defined in terms of a discrete analogue of Jacobi fields, which are explicitly constructed and shown to give a complete description of the enti…

2013-02-01abs ↗pdf ↗