no code implementations • 23 Nov 2022 • Zheng Gong, Wojciech Frys, Renzo Tiranti, Carmine Ventre, John O'Hara, Yingbo Bai
In financial terms, an implied volatility surface can be described by its term structure, its skewness and its overall volatility level.
no code implementations • 17 Aug 2022 • Luke Thorburn, Maria Polukarov, Carmine Ventre
Spatial models of preference, in the form of vector embeddings, are learned by many deep learning and multiagent systems, including recommender systems.
no code implementations • 19 Dec 2021 • Yanqing Ma, Carmine Ventre, Maria Polukarov
Its convenience led to an exponentially increasing amount of financial data, which is however hard to use for the prediction of future prices, due to the low signal-to-noise ratio and the non-stationarity of financial time series.
no code implementations • 12 Apr 2021 • Zheng Gong, Carmine Ventre, John O'Hara
The trade off between risks and returns gives rise to multi-criteria optimisation problems that are well understood in finance, efficient frontiers being the tool to navigate their set of optimal solutions.
no code implementations • 16 Sep 2020 • Fan Fang, Carmine Ventre, Lingbo Li, Leslie Kanthan, Fan Wu, Michail Basios
Feature importance aims at measuring how crucial each input feature is for model prediction.
no code implementations • 25 Mar 2020 • Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, Lingbo Li, David Martinez-Regoband, Fan Wu
This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e. g., cryptocurrency trading systems, bubble and extreme conditions, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).
no code implementations • 9 Feb 2020 • Fan Fang, Waichung Chung, Carmine Ventre, Michail Basios, Leslie Kanthan, Lingbo Li, Fan Wu
The cryptocurrency market is amongst the fastest-growing of all the financial markets in the world.