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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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285785113 · May 202619922001200920172026
48 results for sharp exponent

The total duration of drawdowns is shown to provide a moment-free, unbiased, efficient and robust estimator of Sharpe ratios both for Gaussian and heavy-tailed price returns. We then use this quantity to infer an analytic expression of the bias of moment-based Sharpe ratio estimators as a function of the return distrib…

2015-05-06abs ↗pdf ↗

The paper examines stability of the Sobolev inequality in metric spaces with curvature dimension conditions.

problem Investigating stability of the Sobolev inequality in metric spaces with curvature dimension conditions.
method Assuming almost the same optimal constant, the paper shows that the cumulative distribution of almost extremal functions is close to that of an Aubin-Talenti bubble on the round sphere.
result Quantitative stability with sharp exponent for the Sobolev inequality in various curvature and dimension assumptions.

The paper proves Zimmer's conjecture for non-uniform lattices by controlling mass escape and Lyapunov exponents.

problem Proving Zimmer's conjecture for non-uniform lattices in higher-rank semisimple Lie groups.
method Establishes finiteness of low-dimensional actions, introduces novel techniques to control mass escape and Lyapunov exponents.
result Proves Zimmer's conjecture for many non-uniform lattices, improving previous results.

New method stabilizes deep neural networks by setting Lyapunov exponent to zero.

problem Stability issues in deep neural networks with low width.
method Lyapunov initialization method to set Lyapunov exponent to zero.
result Lyapunov exponent governs stability of deep networks; standard methods fail for low width.

Classifies regularity for Lagrangian mean curvature type equations.

problem Classifying regularity for Lagrangian mean curvature type equations.
method Generalized constant rank theorem for Legendre transform, constructed convex solutions, and showed regularity conditions.
result Optimal regularity conditions for Lagrangian mean curvature type equations.

We empirically analyze the most volatile component of the electricity price time series from two North-American wholesale electricity markets. We show that these time series exhibit fluctuations which are not described by a Brownian Motion, as they show multi-scaling, high Hurst exponents and sharp price movements. We …

2015-07-21abs ↗pdf ↗

Study free energy in spherical spin glasses, proving universality dichotomy.

problem Analyzing free energy in spherical spin glass models with different tail exponents.
method Introduced a tail-adapted normalization and used universality dichotomy.
result Sharp universality dichotomy for free energy across different tail exponents.

Optimizes sharp curvature inequality on spheres, proving near-minimizers are close to standard metric.

problem Optimizing total σ2σ_2-curvature on spheres with positive scalar curvature.
method Analyzes metrics conformal to the standard sphere, uses Sobolev norms to measure closeness.
result Near-minimizers of total σ2σ_2-curvature are almost the standard metric (up to Möbius transformations).

Let ββ be a braid on nn strands, with exponent sum ww. Let ΔΔ be the Garside half-twist braid. We prove that the coefficient of vwn+1v^{w-n+1} in the Homfly polynomial of the closure of ββ agrees with (1)n1(-1)^{n-1} times the coefficient of vw+n21v^{w+n^2-1} in the Homfly polynomial of the closure of βΔ2βΔ^2. This coinciden…

2008-03-02abs ↗pdf ↗

Research examines coamenable subgroups in higher rank groups.

problem Investigates coamenable normal subgroups in higher rank groups.
method Analyzes three complementary phenomena in higher rank groups.
result Growth indicators of coamenable subgroups are not preserved but the Riemannian critical exponent remains rigid.

This paper improves traditional Markowitz optimization by considering variance at multiple time scales.

problem Traditional Markowitz optimization limits to a single time scale, ignoring variance across different frequencies.
method Introduces multifrequency optimization allowing specification of target Hurst exponents across multiple time scales.
result Effective risk management strategy that aligns with investor preferences at various time scales.

Study efficient estimation of hidden subspaces in Gaussian Multi-index models.

problem Estimating hidden subspaces in Gaussian Multi-index models with low-dimensional projections.
method Introduced the generative leap exponent and developed an agnostic sequential estimation procedure using spectral U-statistics.
result Achieved optimal sample complexity of $n=Θ(d^{1 \vee \k/2})$ for efficient estimation.

Study on extremizers for Sobolev inequality on curved manifolds.

problem Existence of extremizers for the sharp pp-Sobolev inequality on Riemannian manifolds with nonnegative curvature.
method Nonsmooth concentration compactness methods and Mosco-convergence results for Cheeger energy.
result Almost extremal functions are close to radial Euclidean bubbles and almost zero globally under nonnegative curvature.

In this paper, we study the dynamics of absolute return, trading volume and bid-ask spread after the trading halts using high-frequency data from the Shanghai Stock Exchange. We deal with all three types of trading halts, namely intraday halts, one-day halts and inter-day halts, of 203 stocks in Shanghai Stock Exchange…

2013-09-04abs ↗pdf ↗

We respond to the issues discussed by Farmer and Lillo (FL) related to our proposed approach to understanding the origin of power-law distributions in stock price fluctuations. First, we extend our previous analysis to 1000 US stocks and perform a new estimation of market impact that accounts for splitting of large ord…

2004-03-02abs ↗pdf ↗

Online SGD achieves consistent estimation in high-dimensional non-convex inference tasks.

problem Consistent estimation in high-dimensional non-convex optimization problems.
method Online stochastic gradient descent (SGD) on non-convex losses.
result Nearly sharp thresholds for sample complexity in high-dimensional settings.

Optimal estimates for spectral projection norms on compact manifolds.

problem Estimating norms of spectral projection operators on compact manifolds.
method Analyzing spectral windows with logarithmic growth and applying curvature constraints.
result Optimal estimates for L2(M)oLq(M)L^2(M) o L^q(M) norms are derived, saturating on flat or negatively curved manifolds.

Study on finite entropy and energy in Kähler geometry.

problem Finite entropy and energy measures in Kähler geometry.
method Refined Moser-Trudinger inequalities for quasi-plurisubharmonic functions.
result Quasi-plurisubharmonic potentials with finite entropy belong to the finite energy class Enn1{\mathcal E}^{\frac{n}{n-1}}.

Optimal learning rates decay to zero in easy tasks and maintain a warmup phase in hard tasks.

problem Optimizing learning rates under functional scaling laws for model training.
method Deriving optimal learning-rate schedules based on exponents ss and ββ.
result Sharp phase transition between easy and hard tasks, with different decay behaviors.

In this paper, we prove that if a metric measure space satisfies the volume doubling condition and the Gagliardo-Nirenberg inequality with the same exponent nn (n2)(n\geq 2), then it has exactly the nn-dimensional volume growth. Besides, two interesting applications have also been given. The one is that we show that if…

2015-11-15abs ↗pdf ↗

The study of random positive 3-strand braids reveals patterns in the roots of their Alexander polynomials.

problem Investigating the roots of Alexander polynomials of random positive 3-strand braids.
method Experimental data analysis, conjectures refinement, and proof of results using tools like the signature function of links and Lyapunov exponent of the Burau representation.
result Generically, at least 69% of the roots of Alexander polynomials are on the unit circle, with a large root-free region near the origin.

Anosov subgroups' deformations affect limit cones and growth indicators continuously.

problem Understanding continuous changes in Anosov subgroups' effects on limit cones and growth indicators.
method Continuous variation of limit cones and growth indicators under deformations of Anosov subgroups, with convexity assumptions.
result Limit cones and growth indicators vary continuously under deformations of Anosov subgroups.

Study semilinear equations on weighted manifolds to prove rigidity.

problem Prove rigidity of weighted manifolds via classification of semilinear equations.
method Classify positive solutions at the Sobolev-critical exponent, proving rigidity and weight triviality.
result Existence of positive solutions implies rigidity and weight triviality under certain curvature conditions.

Recent empirical studies suggest that the volatilities associated with financial time series exhibit short-range correlations. This entails that the volatility process is very rough and its autocorrelation exhibits sharp decay at the origin. Another classic stylistic feature often assumed for the volatility is that it …

2017-06-29abs ↗pdf ↗

Study shows computational and statistical gaps in Gaussian Single-Index Models.

problem Statistical and computational trade-offs in high-dimensional regression problems.
method Analysis of SQ and LDP frameworks, partial-trace algorithm.
result Computational algorithms require significantly more samples than information-theoretic limits.

Sharp inequality for eigenvalues of convex bodies, proving ellipsoid uniqueness.

problem Eigenvalue bounds for convex bodies and ellipsoid uniqueness.
method Established a sharp upper-bound for eigenvalues of a specific operator.
result Equality holds only for ellipsoids, complementing conjectural lower-bound.

Let (M,g) be a smooth compact Riemannian manifold without boundary of dimension n>=6. We prove that {align*} \|u\|_{L^{2^*}(M,g)}^2 \le K^2\int_M\{|\nabla_g u|^2+c(n)R_gu^2\}dv_g +A\|u\|_{L^{2n/(n+2)}(M,g)}^2, {align*} for all u\in H^1(M), where 2^*=2n/(n-2), c(n)=(n-2)/[4(n-1)], R_g is the scalar curvature, $K^{-1}=\i…

2002-01-24abs ↗pdf ↗

Kurdyka-Lojasiewicz (KL) exponent plays an important role in estimating the convergence rate of many contemporary first-order methods. In particular, a KL exponent of 12\frac12 for a suitable potential function is related to local linear convergence. Nevertheless, KL exponent is in general extremely hard to estimate. I…

2019-02-10abs ↗pdf ↗

Study detects a specific type of link using annular Khovanov homology.

problem Detecting a specific type of three-strand weaving link.
method Combines braid detection with rigidity theorem to determine (σ1σ21)N(σ_1σ_2^{-1})^N up to conjugacy.
result Annular Khovanov homology detects the underlying unoriented annular link KNK_N.

In this paper, we show how the sampling properties of the Hurst exponent methods of estimation change with the presence of heavy tails. We run extensive Monte Carlo simulations to find out how rescaled range analysis (R/S), multifractal detrended fluctuation analysis (MF-DFA), detrending moving average (DMA) and genera…

2012-01-23abs ↗pdf ↗

Study of deep neural networks using finite-time Lyapunov exponents.

problem Understanding the geometric structures in input space formed by deep neural networks.
method Analogy with dynamical systems, computing finite-time Lyapunov exponents.
result Ridges of large positive exponents divide input space into regions associated with different classes.

The study proves a gap theorem for CAT(0) spaces with a constant below 1/(6√π).

problem Proving isoperimetric inequalities in non-positive curvature spaces.
method Introduced minimal tetrahedra to prove a linear inequality.
result Established a gap theorem for CAT(0) spaces with a constant below 1/(6√π).

New similarity measure for covariate shift improves nonparametric regression rates.

problem Improving nonparametric regression under covariate shift.
method Introducing a new similarity measure based on probability ratios.
result Shows a sharper rate of convergence compared to transfer exponent.