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Option pricing under path-dependent stock models
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This paper studies how to price and hedge options under stock models given as a path-dependent SDE solution. When the path-dependent SDE coefficients have Fr\'{e}chet derivatives, an option price is differentiable with respect to time and the path, and is given as a solution to the path-dependent PDE. This can be regarded as a path-dependent version of the Feynman-Kac formula. As a byproduct, we obtain the differentiability of path-dependent SDE solutions and the SDE representation of their derivatives. In addition, we provide formulas for Greeks with path-dependent coefficient perturbations. A stock model having coefficients with time integration forms of paths is covered as an example.
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Fourier Neural Operators for Non-Markovian Processes:Approximation Theorems and Experiments
A mirror-padded Fourier neural operator can approximate, with proven error bounds, solution maps of path-dependent SDEs and Lipschitz transformations of fractional Brownian motion.
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