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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.

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48 results for Signature

The paper revisits expected signatures in semimartingale models, providing new formulae and simplifying complexity.

problem Computing expected signatures in semimartingale models.
method Revisits and provides new formulae for computing expected signatures in a general semimartingale setting.
result Log-transform of expected signatures simplifies complexity, leading to signature cumulants.

A well-known property of the signature of closed oriented 4n-dimensional manifolds is Novikov additivity, which states that if a manifold is split into two manifolds with boundary along an oriented smooth hypersurface, then the signature of the original manifold equals the sum of the signatures of the resulting manifol…

2009-11-19abs ↗pdf ↗

New findings on mesh group-planes validate Signature-inverse Theorem under specific conditions.

problem Invalidity of existing inverse theorems for mesh group-planes.
method Classification of three and five point meshes, analysis of joint invariant signatures.
result Valid conditions for the Signature-inverse Theorem in mesh group-planes.

Introduces flat discrete signatures for financial data analysis.

problem Representing financial data for machine learning without continuous transformation.
method Introduced flat discrete signatures and discrete signatures, generalizing flat discrete signatures.
result Flat discrete signatures can represent quadratic variation relevant in finance.

This is a sequel to the paper "The signature package on Witt spaces, I. Index classes" by the same authors. In the first part we investigated, via a parametrix construction, the regularity properties of the signature operator on a stratified Witt pseudomanifold, proving, in particular, that one can define a K-homology …

2009-11-04abs ↗pdf ↗

The paper examines the consistency of Lasso regression applied to signature analysis of time series data.

problem Consistency of Lasso regression in signature analysis of time series data.
method The paper studies the consistency of Lasso regression applied to signature analysis of time series data, both theoretically and numerically.
result The Lasso regression is consistent both asymptotically and in finite sample for certain types of time series and processes.

Study signatures of torus links and their cores using Neumann's equivariant signatures and Hirzebruch's formula.

problem Computing signatures of torus links and their cores.
method Use Neumann's equivariant signatures and rewrite Hirzebruch's formula for torus links (without cores) in terms of integral points in a parallelogram.
result Rewritten Hirzebruch's formula for torus links with cores using integral points in a parallelogram.

This paper extends the C*-signature to non-Witt spaces using noncommutative geometric methods.

problem Extending the signature to non-Witt spaces with noncommutative geometric methods.
method Noncommutative geometric methods, combinatorial framework, and comparison with analytical signature.
result Constructing the C*-signature on non-Witt spaces.

Paper generalizes path signature using fractional calculus for improved machine learning.

problem Improving path signature for machine learning applications.
method Introduces two new signatures inspired by fractional calculus and machine learning considerations.
result Significant accuracy improvements in handwritten digit recognition.

We present a novel method for extracting cancer signatures by applying statistical risk models (http://ssrn.com/abstract=2732453) from quantitative finance to cancer genome data. Using 1389 whole genome sequenced samples from 14 cancers, we identify an "overall" mode of somatic mutational noise. We give a prescription …

2016-04-29abs ↗pdf ↗

Paper introduces branched signature model for efficient computation and data-driven applications.

problem Efficient computation and data-driven modeling of branched rough paths.
method Develops a universal approximation theorem and constructs an extension map to realize branched signatures.
result Explicit construction of branched signatures via an extension map for efficient computation.

Path signatures improve hedging of exotic derivatives in non-Markovian models.

problem Hedging exotic derivatives under non-Markovian stochastic volatility models.
method Investigates path signatures in deep and shallow learning contexts, comparing neural networks and regression approaches.
result Path signatures outperform LSTM in most cases and yield more accurate results in hedging.

In this note, we lay the groundwork for a new approach to the problem of group-signature classification of group actions on closed Riemann surfaces. This new approach first focuses on analyzing the low level arithmetic conditions on signatures before invoking the more complicated group theory. We provide the complete f…

2018-10-02abs ↗pdf ↗

The study explains why signature methods work in commodity futures term structure classification.

problem Lack of interpretability in signature methods for term structure classification.
method Introducing signature perturbations to explain the success of signature-based classification.
result The volatility of the convenience yield is the major discriminant for commodity markets classification.

For a normal covering over a closed oriented topological manifold we give a proof of the L2-signature theorem with twisted coefficients, using Lipschitz structures and the Lipschitz signature operator introduced by Teleman. We also prove that the L-theory isomorphism conjecture as well as the C^*_max-version of the Bau…

2002-09-13abs ↗pdf ↗

Motivation : Molecular signatures for diagnosis or prognosis estimated from large-scale gene expression data often lack robustness and stability, rendering their biological interpretation challenging. Increasing the signature's interpretability and stability across perturbations of a given dataset and, if possible, acr…

2010-01-18abs ↗pdf ↗

Researchers develop Malliavin calculus for signatures, simplifying option Greeks computation.

problem Lack of tractability and explicit representations in Malliavin calculus.
method Focus on finite linear combinations of time-extended Brownian motion signatures, derive explicit formulas for Malliavin derivative, and compute Greeks for path-dependent options.
result Closed-form expressions for classical operators of Malliavin calculus, providing algebraic formulations.

We provide an introduction to the signature method, focusing on its theoretical properties and machine learning applications. Our presentation is divided into two parts. In the first part, we present the definition and fundamental properties of the signature of a path. The signature is a sequence of numbers associated …

2016-03-11abs ↗pdf ↗

Construct symplectic Lefschetz fibrations with any signature and spin type.

problem Existence of symplectic Lefschetz fibrations with arbitrary signature.
method Develop techniques to construct explicit symplectic Lefschetz fibrations over the 2-sphere with any prescribed signature and spin type.
result Solve a long-standing conjecture on the existence of such fibrations with positive signature.

The paper proves formulas and theorems for sub-signature operators on manifolds with or without boundaries.

problem Formulating and proving theorems for sub-signature operators on manifolds with boundaries.
method Obtained Lichnerowicz type formulas and proved Kastler-Kalau-Walze type theorems for sub-signature operators.
result Proved Kastler-Kalau-Walze type theorems for sub-signature operators on 4D and 6D compact manifolds with or without boundaries.

Paper develops approximation and statistical theory for signature-based path regression.

problem Understanding how fast signatures approximate continuous path functionals.
method Develops \(L^2\) approximation rate for smooth functionals of Itô diffusions and establishes consistency of statistical learning procedures.
result Signature-based methods improve prediction over handcrafted features in various real-data applications.

New criteria ensure uniqueness of curve signatures, robust to metric variations.

problem Ensuring uniqueness of curve signatures in differential geometry.
method Introducing new methods through differential equations and higher order derivatives.
result New criteria for curve signature uniqueness in general settings.

Novel signature approach for pricing and hedging path-dependent options with market frictions.

problem Pricing and hedging path-dependent options with market frictions.
method Signature approach, mean-quadratic variation criterion, non-standard infinite-dimensional Riccati equations, time-augmented signature, non-Markovian stochastic control problem.
result Effective hedging strategies in frictional markets with low-truncated signature approximations.

Average signature measures geodesics in Lie groups.

problem Understanding geometric properties of Lie groups through geodesic paths.
method Introducing average signature A(G)\mathbb A(G) and using it with trace operation to recover geometric properties.
result Average signature can recover geometric properties like dimension, diameter, volume, and scalar curvature.