Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling

25 July 2023

Papers citing "Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling"

9 / 9 papers shown

Title
Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions Phillip Murray Ben Wood Hans Buehler Magnus Wiese Mikko S. Pakkanen 61 20 0 15 Jul 2022
Policy Gradient Stock GAN for Realistic Discrete Order Data Generation in Financial Markets Masanori Hirano Hiroki Sakaji Kiyoshi Izumi GAN 61 6 0 28 Apr 2022
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 273 30,123 0 01 Mar 2022
Theoretically Motivated Data Augmentation and Regularization for Portfolio Construction Liu Ziyin Kentaro Minami Kentaro Imajo 41 4 0 08 Jun 2021
Generating Realistic Stock Market Order Streams Junyi Li Xintong Wang Yaoyang Lin Arunesh Sinha Michael P. Wellman GAN AIFin 59 81 0 07 Jun 2020
Quant GANs: Deep Generation of Financial Time Series Magnus Wiese R. Knobloch R. Korn Peter Kretschmer GAN AI4TS AIFin 68 277 0 15 Jul 2019
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 304 12,063 0 19 Jun 2017
Improved Techniques for Training GANs Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen GAN 480 9,048 0 10 Jun 2016
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,049 0 20 Dec 2014