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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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1223 · Jun 202619922001200920172026
20 results for prefactor

The paper uses machine learning to compute rare event probabilities in stochastic systems.

problem Characterizing rare events in stochastic dynamical systems with weak noise.
method Developed a neural network framework for computing quasipotential, most probable paths, and prefactors.
result Demonstrated higher effectiveness and accuracy of the algorithm in calculating mean exit times.

This study generalizes an econophysics model to account for trader heterogeneity, finding robust power-law exponents but sensitive prefactors.

problem The original Lillo-Mike-Farmer model assumed homogeneity in traders' order-splitting strategies, which this study generalizes.
method The study proposes a generalised Lillo-Mike-Farmer model and solves it exactly without heuristic assumptions.
result The power-law exponent in the order-sign ACF is robust for arbitrary heterogeneous intensity distributions, but the prefactor is sensitive to heterogeneity.

The conformal Laplacian's algebraic structure is explored in 2D, revealing a central charge.

problem Exploring the algebraic structure of the conformal Laplacian in 2D.
method Using prefactorization algebras and Green functions.
result In 2D, the conformal Laplacian's algebraic structure is revealed through a central charge.

Paper derives closed-form solutions for CEV model using semiclassical approximation.

problem Analyzing the constant elasticity variance (CEV) option pricing model.
method Utilizes semiclassical (WKB) approximation and Van Vleck-Morette determinant.
result Derives an exponential factor not previously considered in the kernel.

Sharp large deviations and Gibbs conditioning for portfolio credit risk models.

problem Analyzing the risk of default in financial portfolios with dependent factors.
method Sharp large deviation estimates and conditional Bahadur-Rao estimates for threshold models with diverging latent factors.
result Conditioned on a large exceedance event, default indicators become asymptotically i.i.d., and loss-given-default is exponentially tilted.

We confirm the square-root law of market impact on Apple Inc. using a large dataset.

problem Testing the square-root law of market impact on a single U.S. large-cap equity.
method Using a full market-by-order feed, we reconstruct metaorders and calibrate impact using the square-root formula.
result The square-root law is confirmed with a prefactor of 0.34, consistent with worldwide data.

This work studies the smooth 1-Wasserstein distance and its limit distribution in high dimensions.

problem Addressing the curse of dimensionality in empirical approximation.
method Conducts a statistical study including limit distribution, bootstrap consistency, and concentration inequalities.
result Derives a nondegenerate limit distribution for empirical SWD, contrasting with classic W1W_1.

Derives continuum model from discrete ε\varepsilon-graphs with connectivity functional.

problem Modeling diffusion in networks with varying connectivity.
method Energy-based continuum limit derivation, neural-network reconstruction of connectivity.
result Error between discrete and continuum energies is O(ε)O(\varepsilon), valid even with fluctuations.

Paper improves SDR estimation speed and conditions.

problem Improving sufficient dimension reduction for multi-index models.
method Estimating expected smoothed gradient outer product.
result Achieves fast parametric convergence rate of Cdn1/2C_d \cdot n^{-1/2}.

Analyzes tunneling effects for Schrödinger operators on vector bundles.

problem Tunneling effects in quantum systems with multiple potential wells.
method Quasimodes and WKB analysis near potential wells, interaction matrix for coupling between wells.
result Polynomial prefactor for exponentially small eigenvalue splitting determined by dimension of minimal geodesics.

We characterize the communication complexity of the following distributed estimation problem. Alice and Bob observe infinitely many iid copies of ρρ-correlated unit-variance (Gaussian or ±1\pm1 binary) random variables, with unknown ρ[1,1]ρ\in[-1,1]. By interactively exchanging kk bits, Bob wants to produce an estimate $…

2019-01-25abs ↗pdf ↗

Nonparametric Thompson Sampling achieves optimal regret for risk-averse bandits with sub-Gaussian rewards.

problem Optimizing risk-averse bandit problems with sub-Gaussian rewards.
method Anchor-free nonparametric Thompson Sampling algorithm ρextNPTSSGρ ext{-}NPTS_{\mathrm{SG}}.
result Achieves regret matching the instance-dependent lower bound to leading order in logn\log n.

One-pass SGD dynamics in overparameterized quadratic networks show slow escape from poor solutions.

problem Slow escape from poor generalization solutions in overparameterized neural networks.
method Analysis of one-pass SGD dynamics using ordinary differential equations for overlap matrices.
result Overparameterization only modestly accelerates escape from poor solutions.

This paper contains a phenomenological description of the whole U.S. forward rate curve (FRC), based on an data in the period 1990-1996. We find that the average FRC (measured from the spot rate) grows as the square-root of the maturity, with a prefactor which is comparable to the spot rate volatility. This suggests th…

1997-12-15abs ↗pdf ↗

Quantitative analysis of order-splitting behavior in Japanese stock market.

problem Understanding and quantifying the order-splitting behavior of traders in the Japanese stock market.
method Analysis of a large dataset of trading accounts over nine years, clustering traders into order-splitting and random traders, and applying statistical methods to analyze metaorder length and sign correlation.
result The metaorder length distribution follows power laws with exponent α, and the sign correlation exponent γ is approximately α-1, supporting the LMF model.