Authors:
John Cartlidge
;
Charlotte Szostek
;
Marco De Luca
and
Dave Cliff
Affiliation:
University of Bristol, United Kingdom
Keyword(s):
Software agents, Auctions, Financial markets, Algorithmic trading, High-frequency trading, HFT, Computational finance, Human-agent experiments, OpEx.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Economic Agent Models
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
For many of the world's major financial markets, the proportion of market activity that is due to the actions of "automated trading" software agents is rising: in Europe and the USA, major exchanges are reporting that 30%-75% of all transactions currently involve automated traders. This is a major application area for artificial intelligence and autonomous agents, yet there have been very few controlled laboratory experiments studying the interactions between human and software-agent traders. In this paper we report on results from new human-agent experiments using the OpEx experimental economics system first introduced at ICAART-2011. Experiments explore the extent to which the performance of the traders, and of the market overall, is dependent on the speed at which the agents operate. Surprisingly, we found that slowing down the agents increased the market’s overall ability to settle to a competitive equilibrium, and that slow-agent markets were more efficient.