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In this study, we propose a new market simulation method by machine learning model to generate macro dynamics from micro order dynamics. The market simulator ...
In this study, we propose a new market simulation method by machine learning model to generate macro dynamics from micro order dynamics. The market simulator ...
In this study, we propose a new market simulation method by machine learning model to generate macro dynamics from micro order dynamics. The market simulator ...
May 4, 2022 · We propose a synthetic market generator based on Conditional Generative Adversarial Networks (CGANs) trained on real aggregate-level historical data.
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Jun 25, 2024 · We introduce Factor-GAN, a cutting-edge forecasting framework that applies GANs to the realms of stock return prediction and factor investing.
Missing: Simulation | Show results with:Simulation
We propose a new market simulation method by using a deep learning model to generate the macro price dynamics from the micro order dynamics.
Jun 11, 2021 · Practical financial applications of the CorrGAN framework could range from improving trading strategies to risk and portfolio stress testing.
Oct 2, 2024 · High-Frequency Trading (HFT): Multi-agent systems combined with RL and GANs can create bots that adapt quickly to market fluctuations, making ...
This paper describes simulations and analysis of flash crash scenarios in an agent-based modelling framework.
Abstract—Stock market simulations are widely used to create synthetic environments for testing trading strategies before deploying them to real-time markets ...
Missing: Micro- Macro