arXiv q-fin· Munawar Ali, Qi Feng·· 13 hr agoAI Score32
Research on Branching Signature Models
Branched Signature Model
AI summary
The paper proposes a branching signature model that generalizes the classical geometric rough path based on the branching rough path framework, proving its universal approximation theorem, which can approximate high-level signatures through iterative combinations of low-level signature mappings. The model can explicitly extend the original path to a high-dimensional space via the mapping Ψ, implementing it as the classical geometric signature of the extended path, and its effectiveness is verified in two applications: rough volatility calibration and optimal execution.
Source:arXiv q-fin · arxiv.org
Options and VolatilityMachine LearningHigh-Frequency and Market MicrostructurePaper Research#Papers / Research#arXiv#Machine Learning#Volatility#High-Frequency / Market Microstructure