1 code implementation • 10 Oct 2021 • Yufei Wu, Mahmoud Mahfouz, Daniele Magazzeni, Manuela Veloso
The success of machine learning models in the financial domain is highly reliant on the quality of the data representation.
no code implementations • 10 Oct 2021 • Yufei Wu, Mahmoud Mahfouz, Daniele Magazzeni, Manuela Veloso
The success of deep learning-based limit order book forecasting models is highly dependent on the quality and the robustness of the input data representation.
no code implementations • 4 Oct 2021 • Mahmoud Mahfouz, Tucker Balch, Manuela Veloso, Danilo Mandic
Continuous double auctions such as the limit order book employed by exchanges are widely used in practice to match buyers and sellers of a variety of financial instruments.
no code implementations • 19 Sep 2021 • Mahmoud Mahfouz, Armineh Nourbakhsh, Sameena Shah
Organizations around the world face an array of risks impacting their operations globally.
no code implementations • 10 Dec 2019 • Svitlana Vyetrenko, David Byrd, Nick Petosa, Mahmoud Mahfouz, Danial Dervovic, Manuela Veloso, Tucker Hybinette Balch
Machine learning (especially reinforcement learning) methods for trading are increasingly reliant on simulation for agent training and testing.
no code implementations • 28 Nov 2019 • Mahmoud Mahfouz, Angelos Filos, Cyrine Chtourou, Joshua Lockhart, Samuel Assefa, Manuela Veloso, Danilo Mandic, Tucker Balch
The dynamics of financial markets are driven by the interactions between participants, as well as the trading mechanisms and regulatory frameworks that govern these interactions.
no code implementations • 14 Mar 2019 • Giuseppe G. Calvi, Ahmad Moniri, Mahmoud Mahfouz, Qibin Zhao, Danilo P. Mandic
This is achieved through a tensor valued approach, based on the proposed Tucker Tensor Layer (TTL), as an alternative to the dense weight-matrices of DNNs.