Abstract
Wash trade refers to the activities of traders who utilise deliberately designed collusive transactions to increase the trading volumes for creating active market impression. Wash trade can be damaging to the proper functioning and integrity of capital markets. Existing work focuses on collusive clique detections based on certain assumptions of trading behaviours. Effective approaches for analysing and detecting wash trade in a real-life market have yet to be developed. This paper proposes a new analysis approach for abstracting the basic structures of wash trade based on the network topology theory and a novel approach for detecting wash trade activities. The evaluation experiments conducted on four NASDAQ stocks suggest that wash trade actions can be effectively identified based on the proposed algorithm.
| Original language | English |
|---|---|
| Title of host publication | Unknown Host Publication |
| Publisher | IEEE |
| Pages | 85-91 |
| Number of pages | 7 |
| Publication status | Published (in print/issue) - 27 Mar 2014 |
| Event | IEEE Computational Intelligence for Financial Engineering and Economics - Canary Wharf, London Duration: 27 Mar 2014 → … |
Conference
| Conference | IEEE Computational Intelligence for Financial Engineering and Economics |
|---|---|
| Period | 27/03/14 → … |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
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