Division of Physics and Applied Physics, Nanyang Technological University, Singapore, Singapore.
Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore, Singapore.
PLoS One. 2021 Jan 12;16(1):e0242600. doi: 10.1371/journal.pone.0242600. eCollection 2021.
Human behavior as they engaged in financial activities is intimately connected to the observed market dynamics. Despite many existing theories and studies on the fundamental motivations of the behavior of humans in financial systems, there is still limited empirical deduction of the behavioral compositions of the financial agents from a detailed market analysis. Blockchain technology has provided an avenue for the latter investigation with its voluminous data and its transparency of financial transactions. It has enabled us to perform empirical inference on the behavioral patterns of users in the market, which we explore in the bitcoin and ethereum cryptocurrency markets. In our study, we first determine various properties of the bitcoin and ethereum users by a temporal complex network analysis. After which, we develop methodology by combining k-means clustering and Support Vector Machines to derive behavioral types of users in the two cryptocurrency markets. Interestingly, we found four distinct strategies that are common in both markets: optimists, pessimists, positive traders and negative traders. The composition of user behavior is remarkably different between the bitcoin and ethereum market during periods of local price fluctuations and large systemic events. We observe that bitcoin (ethereum) users tend to take a short-term (long-term) view of the market during the local events. For the large systemic events, ethereum (bitcoin) users are found to consistently display a greater sense of pessimism (optimism) towards the future of the market.
人类在从事金融活动时的行为与所观察到的市场动态密切相关。尽管现有许多关于金融体系中人类行为基本动机的理论和研究，但从详细的市场分析中推导出金融参与者的行为构成仍然有限。区块链技术通过其庞大的数据量和金融交易的透明度为后者的研究提供了途径。它使我们能够对市场中用户的行为模式进行实证推断，我们在比特币和以太坊加密货币市场中对此进行了探索。在我们的研究中，我们首先通过时间复杂网络分析确定了比特币和以太坊用户的各种属性。之后，我们通过结合 k-means 聚类和支持向量机的方法，推导出了这两个加密货币市场中用户的行为类型。有趣的是，我们发现了在两个市场中都很常见的四种不同策略：乐观主义者、悲观主义者、积极交易者和消极交易者。在局部价格波动和大型系统性事件期间，用户行为在比特币和以太坊市场之间的构成差异非常明显。我们观察到，在局部事件期间，比特币（以太坊）用户倾向于对市场持有短期（长期）观点。对于大型系统性事件，以太坊（比特币）用户对市场的未来表现出持续的悲观（乐观）情绪。
