11 citations · 28 across the 15 of their papers we have counts for
5 papers · 1 filter
Exploring Coevolutionary Dynamics of Competitive Arms-Races Between Infinitely Diverse Heterogenous Adaptive Automated Trader-Agents
Nik Alexandrov, Dave Cliff, Charlie Figuero
We report on a series of experiments in which we study the coevolutionary "arms-race" dynamics among groups of agents that engage in adaptive automated trading in an accurate model…
Methods Matter: A Trading Agent with No Intelligence Routinely Outperforms AI-Based Traders
Dave Cliff, Michael Rollins
There's a long tradition of research using computational intelligence (methods from artificial intelligence (AI) and machine learning (ML)), to automatically discover, implement, a…
Using Stock Prices as Ground Truth in Sentiment Analysis to Generate Profitable Trading Signals
Ellie Birbeck, Dave Cliff
The increasing availability of "big" (large volume) social media data has motivated a great deal of research in applying sentiment analysis to predict the movement of prices within…
Deep Learning can Replicate Adaptive Traders in a Limit-Order-Book Financial Market
Arthur le Calvez, Dave Cliff
We report successful results from using deep learning neural networks (DLNNs) to learn, purely by observation, the behavior of profitable traders in an electronic market closely mo…
BSE: A Minimal Simulation of a Limit-Order-Book Stock Exchange
Dave Cliff
This paper describes the design, implementation, and successful use of the Bristol Stock Exchange (BSE), a novel minimal simulation of a centralised financial market, based on a Li…