Decompose Market Manipulation Strategies: Evidence from On-chain Meme Coin Market

55 Pages Posted: 23 Dec 2025

See all articles by Wenzhi Ding

Wenzhi Ding

Hong Kong Polytechnic University - School of Accounting and Finance

Chen Lin

The University of Hong Kong - Faculty of Business and Economics

Yichen Luo

The University of Hong Kong - Faculty of Business and Economics; University College London - Department of Computer Science

Jiahua Xu

University College London - Department of Computer Science; The DLT Science Foundation; École Polytechnique Fédérale de Lausanne (EPFL); UCL

Date Written: September 10, 2025

Abstract

This study unravels how different market manipulation strategies affect meme coin project performance and participant profits. Using a clean and observable on-chain setting on the meme coin platform Pumpfun, we collect granular on-chain transaction data and off-chain comment data for 6,000 meme coins and analyze the heterogeneous effects of rat (concealed accumulation/front-running), sniper (concealed accumulation/front-running), wash trading (fabricated activity), and comment bots (fabricated sentiment). Creators or snipers profit from concealed low-cost accumulation; attention manipulation, such as wash trading and fake comments, could effectively attract more traders and affect wealth redistribution. Avoiding manipulation and often timing the dump in early-stage projects, outperformers are disproportionately creators/snipers; underperformers are loss-sensitive and learn little from their past trading. Overall, our findings show how inventory concentration and attention fabrication drive participation, timing, and wealth redistribution. These insights inform transparency and anti-manipulation policy in both crypto and traditional financial markets to better protect innocent traders. 

Suggested Citation

Ding, Wenzhi and Lin, Chen and Luo, Yichen and Xu, Jiahua, Decompose Market Manipulation Strategies: Evidence from On-chain Meme Coin Market (September 10, 2025). Available at SSRN: https://ssrn.com/abstract=5953738 or http://dx.doi.org/10.2139/ssrn.5953738

Wenzhi Ding (Contact Author)

Hong Kong Polytechnic University - School of Accounting and Finance ( email )

Hung Hom
Kowloon
Hong Kong

Chen Lin

The University of Hong Kong - Faculty of Business and Economics ( email )

Pokfulam Road
Hong Kong
China

Yichen Luo

The University of Hong Kong - Faculty of Business and Economics ( email )

University College London - Department of Computer Science ( email )

United Kingdom

Jiahua Xu

University College London - Department of Computer Science ( email )

London
United Kingdom

The DLT Science Foundation ( email )

London
United Kingdom

École Polytechnique Fédérale de Lausanne (EPFL) ( email )

Quartier UNIL-Dorigny, Bâtiment Extranef, # 211
40, Bd du Pont-d'Arve
CH-1015 Lausanne, CH-6900
Switzerland

UCL ( email )

UCL Computer Science
Malet Place London WC
London, London
United Kingdom

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