11 citations · 28 across the 15 of their papers we have counts for
5 papers · 1 filter
Market Impact in Trader-Agents: Adding Multi-Level Order-Flow Imbalance-Sensitivity to Automated Trading Systems
Zhen Zhang, Dave Cliff
Financial markets populated by human traders often exhibit "market impact", where the traders' quote-prices move in the direction of anticipated change, before any transaction has…
Exploring Narrative Economics: An Agent-Based-Modeling Platform that Integrates Automated Traders with Opinion Dynamics
Kenneth Lomas, Dave Cliff
In seeking to explain aspects of real-world economies that defy easy understanding when analysed via conventional means, Nobel Laureate Robert Shiller has since 2017 introduced and…
Automated Creation of a High-Performing Algorithmic Trader via Deep Learning on Level-2 Limit Order Book Data
Aaron Wray, Matthew Meades, Dave Cliff
We present results demonstrating that an appropriately configured deep learning neural network (DLNN) can automatically learn to be a high-performing algorithmic trading system, op…
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…
Which Trading Agent is Best? Using a Threaded Parallel Simulation of a Financial Market Changes the Pecking-Order
Michael Rollins, Dave Cliff
This paper presents novel results generated from a new simulation model of a contemporary financial market, that cast serious doubt on the previously widely accepted view of the re…