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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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48 results for spanning tests

Develops tests for Markowitz stochastic dominance spanning using saddle points.

problem Determining if adding securities or relaxing investment constraints improves investment opportunity sets.
method Derives properties of cdfs, defines Markowitz stochastic dominance spanning, constructs non-parametric tests based on subsampling.
result Rejects market portfolio Markowitz efficiency and finds evidence of outperformance.

This work extends SVM error bounds to weighted SVM and introduces hyperparameter selection methods.

problem Improving SVM performance through effective hyperparameter selection.
method Extending span error bound theory to weighted SVM and introducing hyperparameter selection methods.
result The span rule is the most effective method for weighted SVM hyperparameter selection and provides the best predictor of test error.

We consider the detection of activations over graphs under Gaussian noise, where signals are piece-wise constant over the graph. Despite the wide applicability of such a detection algorithm, there has been little success in the development of computationally feasible methods with proveable theoretical guarantees for ge…

2012-06-05abs ↗pdf ↗

New methods evaluate stock market anomalies for prospect investors.

problem Determining if new securities or investment changes improve prospect investors' opportunities.
method Developed and implemented a new testing procedure for prospect spanning using subsampling and Linear Programming.
result Many well-known anomalies expand prospect investors' opportunity sets, indicating real economic value.

Non-spanning identification of scheduled event risk in option pricing.

problem Separating continuous surface from scheduled jump in option pricing.
method Modeling FOMC decisions, CPI releases, and NFP reports as deterministic-time jumps in risk-neutral option pricing.
result Improves held-out event-spanning pricing with Gaussian and two-component mixture jumps.

New dataset and models detect cryptocurrency bubbles using social media data.

problem Detecting anomalous market behavior in cryptocoins and meme stocks.
method Developed a novel multi-span identification task and sequence-to-sequence hyperbolic models.
result Models effectively detect cryptocoins and meme stocks bubbles in zero-shot settings.

The paper identifies the minimum mean-variance spanning set and its importance in asset evaluation.

problem Estimating the minimum subset of assets that span the efficient frontier.
method Established identification conditions and developed a novel procedure for MSS estimation and inference.
result The MSS estimator accurately covers the true MSS and converges to it at any desired confidence level.

We introduce Universum learning for multiclass problems and propose a novel formulation for multiclass universum SVM (MU-SVM). We also propose an analytic span bound for model selection with almost 2-4x faster computation times than standard resampling techniques. We empirically demonstrate the efficacy of the proposed…

2018-08-23abs ↗pdf ↗

Tests factor models by decomposing market into body and tail legs, revealing inconsistent results.

problem Inconsistency between factor models and market behavior.
method Decomposes market into body and tail legs, testing factor models at daily and monthly frequencies.
result q5 model shows inconsistent results, with negative body and positive tail alphas at all split ratios.

Three methods combine one-class classifiers with MST-CD and N-ary Trees for binary classification.

problem Binary classification with overlapping and imbalanced classes.
method Combining one-class classifiers with MST-CD and N-ary Trees to handle inconsistencies and spurious connections.
result The proposed methods are feasible and comparable to state-of-the-art algorithms.

Paper proposes a method to improve language model performance on unknown distributions.

problem Language models trained on diverse data can perform poorly on unseen distributions.
method Distributionally robust optimization (DRO) to minimize worst-case performance over a mixture of potential test distributions.
result Topic CVaR approach reduces perplexity by 5.5 points compared to standard maximum likelihood.

Study on cryptocurrency market correlations at various time scales.

problem Understanding the hierarchical structure of cryptocurrency market dynamics.
method Analysis of MST and TMFG for 25 liquid cryptocurrencies at different time horizons.
result Cryptocurrency market correlations decrease with finer time scales and show a growing hierarchical structure with coarser scales.

The study finds that factor momentum is significant only at short lags compared to stock momentum.

problem Investigating the relationship between factor momentum and stock momentum.
method Replicated earlier findings and conducted a spanning test controlling for stock momentum and factor exposure.
result Factor momentum is significant only at short lags after controlling for stock momentum and factor exposure.

The Jones polynomial can be expressed in terms of spanning trees of the graph obtained by checkerboard coloring a knot diagram. We show there exists a complex generated by these spanning trees whose homology is the reduced Khovanov homology. The spanning trees provide a filtration on the reduced Khovanov complex and a …

2006-07-20abs ↗pdf ↗

Spanning attack improves black-box attacks with unlabeled data.

problem Query inefficiency in black-box attacks due to high input space dimensionality.
method Proposes spanning attack by constraining adversarial perturbations in a low-dimensional subspace via an auxiliary unlabeled dataset.
result Significantly improves query efficiency of black-box attacks.

We introduce the warping polynomial of an oriented knot diagram. In this paper, we characterize the warping polynomial, and define the span of a knot to be the minimal span of the warping polynomial for all diagrams of the knot. We show that the span of a knot is one if and only if it is non-trivial and alternating, an…

2011-09-27abs ↗pdf ↗

SPAN learns functions over sets invariant to permutations, outperforming existing methods.

problem Learning functions over sets invariant to permutations.
method SPAN architecture that combines neural networks with adversarial permutations.
result SPAN achieves nearly permutation-invariant functions while maintaining accuracy.

This paper improves speech recognition by using raw waveform signals in multi-span CNN acoustic models.

problem Improving speech recognition accuracy using raw waveform signals.
method Proposes a novel multi-span structure for acoustic modelling based on raw waveform signals with multiple CNN input layers.
result Multi-span acoustic models yield a lower word error rate (WER) than traditional FBANK feature-based models.

Study asymptotic expansion of graph Laplacian on discretized surfaces, relating spanning trees and cycle-rooted forests.

problem Asymptotic expansion of graph Laplacian on discretized surfaces.
method Relate spanning trees and cycle-rooted spanning forests to zeta-regularized determinants.
result Explicit formula for limit of cycle-rooted spanning forest probability and topological observables.

New invariants measure how far spanning surfaces are from being compressible.

problem Understanding how essential spanning surfaces are in 3-manifolds.
method Introducing algebraic and geometric essence invariants, proving plumbing respects algebraic essence, and extending results to arbitrary 3-manifolds.
result Plumbing respects the algebraic essence of spanning surfaces, extending Ozawa's theorem.

Method for factor analysis in short panels without assuming sphericity or Gaussianity.

problem Factor analysis in short panels without assuming sphericity or Gaussianity.
method Pseudo maximum likelihood method and asymptotically uniformly most powerful invariant test.
result Systematic risk explains a large part of cross-sectional total variance in bear markets but is not spanned by observed factors.

Nonorientable spanning surfaces of periodic knots can have arbitrarily high first Betti number.

problem Periodic knots do not always have nonorientable spanning surfaces of high genus.
method Examples and calculations of nonorientable spanning surfaces of periodic knots.
result The first Betti number of nonorientable spanning surfaces can be arbitrarily large.

We investigated the network structures of the Japanese stock market through the minimum spanning tree. We defined grouping coefficient to test the validity of conventional grouping by industrial categories, and found a decreasing in trend for the coefficient. This phenomenon supports the increasing external influences …

2007-08-03abs ↗pdf ↗

Researchers use human-in-the-loop to create counterfactually augmented data, improving model performance.

problem Creating ML models less reliant on spurious patterns in NLP datasets.
method A human-in-the-loop process to curate counterfactually augmented data (CAD), prohibiting unnecessary edits.
result Models trained on CAD appear to rely less on semantically irrelevant words and generalize better out of domain.