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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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7 results for “deep-signature”

Deep Signature FBSDE Algorithmcs.LG

Deep signature/log-signature FBSDE algorithm improves accuracy and training time.

problem Solving FBSDEs with state and path dependent features.

method Incorporates deep signature/log-signature transformation into RNN model.

result Improves accuracy and training time compared to existing methods.

FBSDE deep signature log-signature RNN accuracy

2021-08-24abs ↗pdf ↗

Deep Signature Algorithm for Multi-dimensional Path-Dependent Optionsq-fin.CP

Deep signature algorithm for pricing path-dependent options.

problem Pricing path-dependent options with complex payoff functions.

method Extended backward scheme for state-dependent FBSDEs with reflections, incorporating signature layer for path-dependent FBSDEs.

result Convergence analysis of the algorithm with explicit dependence on truncation order and neural network approximation errors.

path-dependent options deep signature algorithm FBSDEs numerical pricing convergence analysis

2022-11-21abs ↗pdf ↗

Pricing American options under rough volatility using deep-signatures and signature-kernelsq-fin.MF

New methods price American options in rough volatility models.

problem Pricing American options under rough volatility.

method Integrating deep-signature and signature-kernel learning into optimal stopping problem solutions.

result Performance comparison in rough Heston and rough Bergomi models.

American options rough volatility deep-signature signature-kernel optimal stopping

2025-01-12abs ↗pdf ↗

Option pricing under non-Markovian stochastic volatility models: A deep signature approachq-fin.MF

The paper develops a deep signature approach for option pricing under non-Markovian stochastic volatility models.

problem Pricing options under non-Markovian stochastic volatility models is challenging due to the dependence on historical paths.

method Reformulate the asset dynamics as a rough stochastic differential equation and represent rough paths via signatures. Apply standard analytical tools to solve the transformed equation.

result The deep signature approach provides a theoretically grounded and computationally efficient framework for option pricing.

option pricing stochastic volatility non-Markovian models deep signatures rough paths

2025-08-21abs ↗pdf ↗

Deep Signature Transformscs.LG

The signature is an infinite graded sequence of statistics known to characterise a stream of data up to a negligible equivalence class. It is a transform which has previously been treated as a fixed feature transformation, on top of which a model may be built. We propose a novel approach which combines the advantages o…

2019-05-21abs ↗pdf ↗

Valuation of variable annuities under the Volterra mortality and rough Heston modelsq-fin.CP

The paper values variable annuities using complex stochastic models and deep learning.

problem Valuation of variable annuities with early surrender options under non-Markovian models.

method Developed a deep signature Least Squares Monte Carlo approach to handle path-dependent continuation values.

result Fair fees increase with Hurst parameters of stock volatility and mortality force.

variable annuities non-Markovian models deep learning signature methods stochastic processes

2026-04-01abs ↗pdf ↗

SigMA: Path Signatures and Multi-head Attention for Learning Parameters in fBm-driven SDEscs.LG

SigMA uses signatures and attention to estimate parameters in fBm-driven SDEs.

problem Estimating parameters in SDEs driven by fBm is challenging due to non-Markovian and semimartingale issues.

method SigMA integrates path signatures with multi-head self-attention, using convolutional and MLP layers.

result SigMA outperforms other methods in accuracy, robustness, and model compactness.

path signatures fractional Brownian motion SDEs multi-head attention parameter estimation

2025-12-17abs ↗pdf ↗