Market Manipulation of Bitcoin: Evidence from Mining the Mt. Gox Transaction Network
This paper investigates the market manipulation of Bitcoin, and shows the evidence from mining the Mt. Gox transaction network. The technology mainly used in this paper is SVD, which I feel novel and interesting. Although Bitcoin is a decentralized system, with the expansion of trading venues and the growth of mining pools, some centralized institutions may still interfere with the system. So the cryptocurrency market must strengthen the supervision..
Do the rich get richer? An empirical analysis of the Bitcoin transaction network
Present econophysics models are usually employed on presumed random networks of interacting agents due to the lack of real data. However, the transparency of the Bitcoin transaction network enables this system to be hugely valuable for econophysicists wishing to evaluate and refine their models. This paper is a first try on real data through introducing the Bitcoin transaction data to further analyze the preferential attachment phenomenon in practice, which has significant potential for future studies.
Bitcoin: A Peer-to-Peer Electronic Cash System
The paper treats bitcoin as a P2P Electronic Cash System, and put forward a solution to the double-spending problem using a peer-to-peer distributed timestamp server to generate computational proof of the chronological order of transactions. Under the premise that honest nodes collectively control more CPU power than any cooperating group of attacker nodes, This paper implements a secure electronic payment system based on cryptographic proof instead of trust. This has a wide range of applications in Internet commerce.
Peer to Peer
Predicting the Price of Bitcoin Using Machine Learning
This paper introduces a deep learning model based on long short term memory network to analyze the bitcoin price in USD, which trumps the popular time series forecasting models like ARIMA. The results of the experiment is laudable, and has practical reference value to data mining using deep learning in the blockchain field.
Inferring the interplay between network structure and market effects in Bitcoin
This paper used Principal Component Analysis to extract important features of the time variation of Bitcoin transaction network and investigated the relation between those features and the exchange price of bitcoins. The experiment results showed high correspondence between the first singular vector of the graph of long-term bitcoin users and the market price of bitcoins, which are interesting and important for digital assets value estimation.
What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis
This paper studies some potential drivers of Bitcoin prices, ranging from fundamental sources to speculative and technical ones, and further studies the potential influence o Chinese market. The paper examines the evolution of relationships in both time and frequency domains utilizing the continuous wavelets framework, which allows the paper to distinguish between short-term connections and long-term connections.
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Smart Contract (10)
data mining (5)
Transaction Graph (4)
Ponzi scheme (3)
Bitcoin Clustering (2)
Peer to Peer (2)
Generals Byzantine Problem (2)