Market Manipulation of Bitcoin: Evidence from Mining the Mt. Gox Transaction Network
Weili Chen, Jun Wu, Zibin Zheng, Chuan Chen, and Yuren Zhou

TL;DR
This paper analyzes the Mt. Gox Bitcoin transaction network to detect market manipulation patterns, revealing significant manipulation and emphasizing the need for better supervision in cryptocurrency markets.
Contribution
It introduces a novel network analysis approach combining graph analysis and SVD to identify manipulation patterns in cryptocurrency exchange data.
Findings
Detected strong correlation between certain account behaviors and price fluctuations.
Identified specific market manipulation patterns in Mt. Gox transactions.
Provided evidence of serious market manipulation in the Mt. Gox exchange.
Abstract
The cryptocurrency market is a very huge market without effective supervision. It is of great importance for investors and regulators to recognize whether there are market manipulation and its manipulation patterns. This paper proposes an approach to mine the transaction networks of exchanges for answering this question.By taking the leaked transaction history of Mt. Gox Bitcoin exchange as a sample,we first divide the accounts into three categories according to its characteristic and then construct the transaction history into three graphs. Many observations and findings are obtained via analyzing the constructed graphs. To evaluate the influence of the accounts' transaction behavior on the Bitcoin exchange price,the graphs are reconstructed into series and reshaped as matrices. By using singular value decomposition (SVD) on the matrices, we identify many base networks which have a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBlockchain Technology Applications and Security · Complex Systems and Time Series Analysis · Data Stream Mining Techniques
