3 citations · 3 across the 4 of their papers we have counts for
4 papers
KANHedge: Efficient Hedging of High-Dimensional Options Using Kolmogorov-Arnold Network-Based BSDE Solver
Rushikesh Handal, Masanori Hirano
High-dimensional option pricing and hedging present significant challenges in quantitative finance, where traditional PDE-based methods struggle with the curse of dimensionality. T…
Enhancing Financial Domain Adaptation of Language Models via Model Augmentation
Kota Tanabe, Masanori Hirano, Kazuki Matoya +3
The domain adaptation of language models, including large language models (LLMs), has become increasingly important as the use of such models continues to expand. This study demons…
KANOP: A Data-Efficient Option Pricing Model using Kolmogorov-Arnold Networks
Rushikesh Handal, Kazuki Matoya, Yunzhuo Wang +1
Inspired by the recently proposed Kolmogorov-Arnold Networks (KANs), we introduce the KAN-based Option Pricing (KANOP) model to value American-style options, building on the conven…
Experimental Analysis of Deep Hedging Using Artificial Market Simulations for Underlying Asset Simulators
Masanori Hirano
Derivative hedging and pricing are important and continuously studied topics in financial markets. Recently, deep hedging has been proposed as a promising approach that uses deep l…