Deep learning of transition probability densities for stochastic asset models with applications in option pricing
Year of publication: |
2025
|
---|---|
Authors: | Su, Haozhe ; Tretyakov, M. V. ; Newton, David P. |
Published in: |
Management science : journal of the Institute for Operations Research and the Management Sciences. - Hanover, Md. : INFORMS, ISSN 1526-5501, ZDB-ID 2023019-9. - Vol. 71.2025, 4, p. 2922-2952
|
Subject: | deep learning | neural networks | option pricing | parametric PDEs | transition probability density | Optionspreistheorie | Option pricing theory | Neuronale Netze | Neural networks | Stochastischer Prozess | Stochastic process | Lernprozess | Learning process | Wahrscheinlichkeitsrechnung | Probability theory | Statistische Verteilung | Statistical distribution | Optionsgeschäft | Option trading |
-
An unsupervised deep learning approach to solving partial integro-differential equations
Fu, Weilong, (2022)
-
A new improvement scheme for approximation methods of probability density functions
Takahashi, Akihiko, (2016)
-
Nonparametric predictive inference for European option pricing based on the binomial tree model
He, Ting, (2019)
- More ...
-
Option pricing via QUAD : from Black-Scholes-Merton to Heston with jumps
Su, Haozhe, (2016)
-
Application of option pricing theory to R&D
Newton, David P., (1992)
-
Market conventions vs. actuarial yields : implications for bond swapping
Newton, David P., (1992)
- More ...