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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.

168,742 papers · 148 categories

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48 results for skewed confidence

Improves binary classification from positive data with skewed confidence.

problem Skewed confidence in positive data affects the performance of Pconf classifiers.
method Parameterized model of skewed confidence and hyperparameter selection.
result Proposed method effectively cancels out the negative impact of skewed confidence.

SkewPNN uses probabilistic neural networks with skew-normal kernels to improve classification of imbalanced data.

problem Imbalanced data distribution leading to biased predictions for minority classes.
method Probabilistic neural networks with skew-normal kernel function and Bat optimization algorithm for hyperparameter tuning.
result SkewPNN and BA-SkewPNN outperform other methods in both balanced and imbalanced datasets.

LLMs overestimate stock returns and are less accurate at predicting extreme outcomes.

problem Behavioral biases in LLMs' stock return forecasts.
method Comparison of LLM forecasts with crowd-sourced estimates and historical data.
result LLMs overestimate stock returns and are less accurate at predicting extreme outcomes.

Develops a novel fast bootstrap for dependent data with higher-order accuracy.

problem Estimation of parametric and semi-parametric models for dependent data.
method i.i.d. resampling of smoothed moment indicators, asymptotic refinements under mild assumptions.
result Higher-order correct asymptotic confidence distributions and confidence intervals.

New method improves confidence intervals for adaptive experiment results.

problem Adaptive experiments complicate statistical inference, especially when estimating sub-optimal treatments.
method Adaptive reweighting of inverse propensity weighting terms to control variance and ensure correct coverage.
result The method prevents heavy-tailed estimates and increases hypothesis testing power.

The paper defines MTCov for skewed elliptical distributions.

problem No specific problem stated, but dealing with skewed elliptical distributions.
method Defined MTCov for generalized skew-elliptical distributions and compared with skewed and non-skewed normal distributions.
result Special formula for MTCov of generalized skew-elliptical distributions.

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.

GINNs combine deep learning with PGMs for physics-based multiscale systems.

problem Intrinsic computational bottlenecks and lack of sufficient data for QoI estimation.
method Hybrid approach combining deep learning with probabilistic graphical models, informed by structured priors for CVs.
result GINNs produce tight confidence intervals for non-Gaussian QoIs.

The paper calculates moments and conditional risks for skewed elliptical distributions.

problem Estimating moments and tail conditional risks for skewed elliptical distributions.
method Derives explicit expressions for multivariate doubly truncated moments and conditional risks for generalized skew-elliptical distributions.
result Explicit formulas for multivariate doubly truncated moments and conditional risks are derived for various skewed elliptical distributions.

Proposes a method to identify elements in a skewness matrix for multivariate skew-elliptical distributions.

problem Label switching issue in Bayesian estimation of skewness matrix.
method Imposes a positive lower-triangular constraint and uses Bayesian sparse estimation with horseshoe prior.
result Successfully estimates the true structure of skewness dependency.

Study the geometry and dynamics of skew evolutes and involutes, related to bicycle kinematics.

problem Understanding the geometry and dynamics of skew evolutes and involutes.
method Investigate the skew evolute and involute maps, comparing them to bicycle kinematics.
result The skew evolute and involute maps have properties analogous to bicycle kinematics.

Study on simplicity of Lie skew braces, proving new results for compact cases.

problem Simplicity of Lie skew braces, focusing on compact connected cases.
method Reviewing correspondence, investigating ideals and rigidity, proving main result for compact Lie skew braces.
result Compact connected simple Lie skew braces are either trivial or have simple underlying Lie groups.

A skew loop is a closed curve without parallel tangent lines. We prove: The only complete surfaces in euclidean 3-space with a point of positive curvature and no skew loops are the quadrics. In particular, ellipsoids are the only closed surfaces without skew loops. We also prove results about skew loops on cylinders an…

2002-05-21abs ↗pdf ↗

Skewness dispersion predicts future stock market returns, especially in months with monetary policy announcements.

problem Predicting future stock market returns using skewness dispersion.
method Cross-sectional analysis of firm-level realized skewness and stock market returns.
result Skewness dispersion is a significant predictor of future stock market returns, robust to various estimation methods.

A skew brane is an immersed codimension 2 submanifold in affine space, free from pairs of parallel tangent spaces. Using Morse theory, we prove that a skew brane cannot lie on a quadratic hypersurface. We also prove that there are no skew loops on embedded ruled developable discs in 3-space. The paper extends recent wo…

2003-02-21abs ↗pdf ↗

This paper classifies 4D spin manifolds with skew Killing spinors.

problem Classifying 4D Riemannian spin manifolds with skew Killing spinors.
method Analyzing skew Killing spinors with skew-symmetric endomorphisms A, considering both degenerate and non-degenerate cases.
result In the degenerate case, the manifold is locally isometric to R x N with N having a skew Killing spinor.

Complete classification of quaternionic skew-Hermitian symmetric spaces found.

problem Classifying quaternionic skew-Hermitian symmetric spaces.
method Proving the existence of a torsion-free mSO(2n)mSp(1){ m SO}^{*}(2n){ m Sp}(1)-structure and showing that any homogeneous space is symmetric.
result A complete classification of quaternionic skew-Hermitian symmetric spaces for arbitrary n>1n>1.

Following recent work by Ghomi, Solomon and Tabachnikov, we study geometry and topology of skew branes. A skew brane is a codimension 2 submanifold in affine space such that the tangent spaces at any pair of distinct points are not parallel. We prove that if an oriented closed manifold has a non-zero Euler characterist…

2005-04-23abs ↗pdf ↗

A parsimonious model reduces over-parameterization in skewed matrix variate mixtures.

problem Over-parameterization in skewed matrix variate mixtures.
method Parsimonious family of 256 models using bilinear factor analyzers constrained over clusters, with AECM algorithm for estimation.
result Extensive simulations and real-world datasets (MNIST, Olivetti faces) demonstrate the method's effectiveness.

Optimizes option portfolios for skewed-t returns using VaR and variance measures.

problem Optimizing portfolios for skewed-t returns with heavy tails and skewness.
method Uses variance and VaR measures, departing from normal returns, and provides explicit portfolio weights.
result Optimal portfolio weights differ significantly from variance optimal weights due to skewness.

The paper improves asset allocation using a skew-normal distribution in the Black-Litterman model.

problem Improving asset allocation under skewed return distributions.
method Using the Black-Litterman model with hidden truncation skew-normal distribution and Simaan's three-moment risk model.
result Optimal portfolios have less risk and higher skewness compared to classical BL model.

A new clustering method for functional data using skewed distributions.

problem Clustering functional data with skewed distributions.
method Mixtures of functional linear regression models and three skewed multivariate distributions (variance-gamma, skew-t, normal-inverse Gaussian).
result The proposed method funWeightClustSkew performs well on simulated and real data.

The paper characterizes curvature of quaternionic skew-Hermitian manifolds and constructs related geometric structures.

problem Characterizing the curvature of quaternionic skew-Hermitian manifolds.
method Holonomy theory of symplectic connections and bundle constructions.
result Existence and integrability of almost hypercomplex skew-Hermitian structures on Swann bundles.

The paper defines symmetric brackets for skew-symmetric algebroids with totally skew-symmetric torsion.

problem Defining symmetric brackets for skew-symmetric algebroids.
method Using connections with totally skew-symmetric torsion and pseudo-Riemannian metrics.
result Explicit formula for the Levi-Civita connection and symmetric brackets on almost Hermitian manifolds.

A geometry with parallel skew-symmetric torsion is a Riemannian manifold carrying a metric connection with parallel skew-symmetric torsion. Besides the trivial case of the Levi-Civita connection, geometries with non-vanishing parallel skew-symmetric torsion arise naturally in several geometric contexts, e.g. on natural…

2018-06-30abs ↗pdf ↗

Optimal option portfolios under Sharpe Ratio maximization with skew-elliptical t-distributed returns

problem Optimal option portfolios under Sharpe Ratio maximization
method Formulation for explicit portfolio weights
result Different optimal portfolios for Sharpe Ratio and return-to-Value-at-Risk (VaR) ratio

The paper examines differential smoothness in specific algebra types.

problem Differential smoothness in 3D skew polynomial algebras and diffusion algebras.
method Analyzes the properties of 3D skew polynomial algebras and diffusion algebras.
result Provides insights into the differential smoothness of these algebra types.

This paper is devoted to the first systematic investigation of manifolds that are Einstein for a connection with skew symmetric torsion. We derive the Einstein equation from a variational principle and prove that, for parallel torsion, any Einstein manifold with skew torsion has constant scalar curvature; and if it is …

2012-09-26abs ↗pdf ↗

The rough Bergomi model, introduced by Bayer, Friz and Gatheral [Quant. Finance 16(6), 887-904, 2016], is one of the recent rough volatility models that are consistent with the stylised fact of implied volatility surfaces being essentially time-invariant, and are able to capture the term structure of skew observed in e…

2017-08-08abs ↗pdf ↗