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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.

168,657 papers · 148 categories

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48 results for Measurement

Study invariant measures on measured laminations for subgroups of mapping class group.

problem Classify invariant Radon measures on space of measured laminations for subgroups of mapping class group.
method Geometric approach, focusing on recurrent measured laminations, explicitly constructing ergodic measures.
result Show uniquely ergodic for divergence-type subgroups, generalize results for full mapping class group.

New set-valued star-shaped risk measures introduced for better risk assessment.

problem Improving risk assessment in financial contexts.
method Developed new set-valued star-shaped risk measures and proved their representation theorems.
result Set-valued star-shaped risk measures can be represented as unions of set-valued convex risk measures.

Bayesian approach to robust risk measures under model uncertainty.

problem Representing robust risk measures as a single probability measure.
method Introducing two types of risk measures and analyzing their relation to robust risk measures.
result Robust risk measures can be represented by a mixture probability measure, a Bayesian approach.

The paper studies dynamic star-shaped risk measures and their representation.

problem Representing dynamic star-shaped risk measures and their properties.
method Representation theorems for dynamic monetary and star-shaped risk measures.
result Dynamic star-shaped risk measures can be represented as the lower envelope of a family of dynamic convex risk measures.

Transformers can interpolate between arbitrary measures.

problem Understanding the expressive power of Transformers as measure-to-measure maps.
method Provided an explicit choice of parameters for a single Transformer to match N arbitrary input measures to N arbitrary target measures.
result A single Transformer can interpolate between arbitrary measures.

Submodularity is studied for convex risk measures, including Expected Shortfall.

problem Characterizing submodularity in convex risk measures.
method Analyzing submodularity properties of law-invariant coherent risk measures, including Expected Shortfall and Value-at-Risk.
result AES is submodular only when it reduces to ES, and empirical analysis shows AES violations are less frequent than VaR and ES violations.

The paper explores non-convex risk measures and their characterizations.

problem Characterizing non-convex risk measures without convexity or weak convexity.
method Characterizes monetary risk measures as lower envelopes of families of convex or coherent risk measures, considering law-invariance and SSD-consistency.
result Unified representation theorems for law-invariant risk measures, including VaR.

One often finds in the literature connections between measures of fairness and measures of feature importance employed to interpret trained classifiers. However, there seems to be no study that compares fairness measures and feature importance measures. In this paper we propose ways to evaluate and compare such measure…

2019-10-12abs ↗pdf ↗

Dual representations for robust risk measures and uncertainty sets.

problem Characterizing continuity of robust risk measures and their uncertainty sets.
method Develop dual representations for robust risk measures and uncertainty sets based on distinct geometric assumptions.
result Two dual frameworks for consolidated uncertainty sets are complementary, not interchangeable.

A scalable approach to learning from probability measures using quantization.

problem Efficiently comparing and manipulating large sets of probability measures.
method Quantization of probability measures to a fixed support, followed by optimal transport computations.
result Consistency and convergence guarantees for quantized measures in various OT-based tasks.

Risk measures for multivariate financial positions are studied in a utility-based framework. Under a certain incomplete preference relation, shortfall and divergence risk measures are defined as the optimal values of specific set minimization problems. The dual relationship between these two classes of multivariate ris…

2014-05-19abs ↗pdf ↗

The Cannon-Thurston map's pushed measures on the circle are singular with respect to sphere measures.

problem Understanding the behavior of geodesics and measures on fibered hyperbolic 3-manifolds.
method Properties of geodesics and measures on the circle and sphere are analyzed to prove singularity.
result Natural measures on the circle become singular with respect to measures on the sphere.

New weighted surface area measures for convex bodies with applications.

problem Generalizing surface area measures to weighted Borel measures.
method Formulating and analyzing weighted surface area measures, proving integral formula and Bézout-type inequality.
result New integral formula for mixed measure of three bodies, generalizing Bézout-type inequality.

Standardized fairness measures for continuous risk scores using Wasserstein distance.

problem Quantifying and interpreting group disparities in continuous risk scores.
method Proposes standardized fairness measures based on Wasserstein distance for continuous scores.
result Proposed measures outperform ROC-based fairness measures by being more explicit and quantifying significant biases.

We study generalizations of Reifenberg's Theorem for measures in Rn\mathbb R^n under assumptions on the Jones' ββ-numbers, which appropriately measure how close the support is to being contained in a subspace. Our main results, which holds for general measures without density assumptions, give effective measure bounds…

2016-12-23abs ↗pdf ↗

The study evaluates AI model performance measures for medical use.

problem Selecting appropriate performance measures for AI models in medical practice.
method Assessed 32 performance measures across five domains for binary outcomes.
result 17 measures are both proper and reflect decision-analytic performance.

We introduce a weak notion of barycenter of a probability measure μμ on a metric measure space (X,d,m)(X, d, {\bf m}), with the metric dd and reference measure m{\bf m}. Under the assumption that optimal transport plans are given by mappings, we prove that our barycenter B(μ)B(μ) is well defined; it is a probability measur…

2017-03-28abs ↗pdf ↗

Study on convergence of Narasimhan-Simha measures on degenerating families of Riemann surfaces.

problem Analyzing the convergence of measures on degenerating families of Riemann surfaces.
method Hybrid space approach, using metrized curve complex and Hermitian pairing.
result Convergence of measures on hybrid space, extending to singular curves.

Stationary measures on hyperbolic surfaces with cusps are singular and stable under quasi-symmetries.

problem Understanding stationary measures on hyperbolic surfaces with cusps.
method Analyzing exponential decay of cusp excursions and proving quasi-symmetry stability.
result Stationary measures on hyperbolic surfaces with cusps are quasi-symmetrically stable and singular.

The study shows finite measure-preserving isometry groups for certain metric measure spaces.

problem Understanding the structure of isometry groups in metric measure spaces.
method Analyzing synthetic negative Ricci curvature and Bakry-Émery Ricci curvature.
result The measure-preserving isometry group is finite for compact metric measure spaces with specific curvature conditions.

The paper establishes a connection between different risk measures and their risk contributions.

problem Understanding the relationship between conditional coherent and deviation risk measures.
method Axiomatic framework and continuous-time risk contribution analysis.
result Risk contributions of time-consistent risk measures are also time-consistent.

Investigates set-valued risk measures for processes and vectors, proving equivalence and providing new dual representations.

problem Investigates set-valued risk measures for processes and vectors.
method Utilizes equivalence of risk measures for processes and vectors and their penalty function formulations.
result Provides new dual representation for risk measures for processes in the set-valued framework.

Starting from the requirement that risk measures of financial portfolios should be based on their losses, not their gains, we define the notion of loss-based risk measure and study the properties of this class of risk measures. We characterize loss-based risk measures by a representation theorem and give examples of su…

2011-10-07abs ↗pdf ↗

This paper introduces a new systemic risk measure, JMES, and its associated contribution measures.

problem Measuring systemic risk and its contributions among entities.
method Proposes JMES and associated contribution measures, studies their properties, and compares them with existing measures.
result Established sufficient conditions for comparing JMES and other measures under different copula structures and stress levels.

We describe a construction of ordered algebraic structures (ordered abelian semigroups, ordered commutative semirings, etc.) and describe applications to codimension-1 laminations. For a suitable ordered semi- algebraic structure L\mathbb L and measurable space XX we define L\mathbb L-measures νν on XX. If LL is …

2014-07-25abs ↗pdf ↗

Measuring conditional dependencies among the variables of a network is of great interest to many disciplines. This paper studies some shortcomings of the existing dependency measures in detecting direct causal influences or their lack of ability for group selection to capture strong dependencies and accordingly introdu…

2017-03-31abs ↗pdf ↗

New risk measures assess cryptocurrency market vulnerabilities during financial distress.

problem Capturing systemic risk in cryptocurrency markets during financial distress.
method Introducing Vulnerability Conditional Risk Measures (VCoES) and related measures.
result Validated theoretical insights and demonstrated practical relevance in cryptocurrency market.

New stability measures for similar features improve feature selection accuracy.

problem Existing stability measures fail to distinguish similar features in highly correlated datasets.
method Introduce new adjusted stability measures that consider feature similarities.
result One new stability measure considers highly similar features as interchangeable.

We simplify information measure computation using learned features.

problem Computing information measures from raw data is computationally expensive.
method Developed a separable design for computing information measures from learned feature representations.
result A variety of information measures can be computed efficiently through learned feature representations.

The paper analyzes skewness and kurtosis measures for skew-elliptical distributions.

problem Examining skewness and kurtosis measures for skew-elliptical distributions.
method Deriving exact expressions for skewness and kurtosis measures for skew-elliptical distributions, constructing test statistics, and comparing measures through simulations and real data analysis.
result Exact expressions and test statistics for skewness and kurtosis measures for various skew-elliptical distributions.