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用于研究比特币交易的基于智能体人工市场

文章 arXiv papers · 作者: Luisanna Cocco et al.
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总结

本文介绍一个用于研究比特币交易的人工加密货币市场。模型包含两类不同的交易者：随机交易者和图表交易者。他们根据各自策略以及持有的比特币或法币余额提交买卖订单。比特币供应量会随时间增长，增速与真实市场相关，但模型本身没有表示挖矿过程。

作者报告称，该模拟再现了比特币绝对收益率的若干统计特征：自相关性和累积分布。这提供了一种探索简单交易者类型间的互动如何形成某些观测市场模式的方法。该模型被视为进一步分析的起点，而非对加密货币市场的完整描述；其简化的智能体类型和未建模的挖矿过程，限制了模型行为向真实交易条件推广的程度。

核心观点

  • 人工市场包含随机交易者和交易比特币的图表交易者。
  • 智能体根据自身策略以及可用的加密货币或法币资源下单。
  • 比特币供应量随时间增长，但模拟未明确建模挖矿过程。
  • 模型再现了据报告的绝对收益率特征，包括自相关性及其累积分布。
  • 其结构经过简化，因此适合作为研究起点，而非完整的市场描述。

标签

加密资产统计学市场微观结构
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# Using an Artificial Financial Market for studying a Cryptocurrency Market


# Using an Artificial Financial Market for studying a Cryptocurrency Market









This paper presents an agent-based artificial cryptocurrency market in which heterogeneous agents buy or sell cryptocurrencies, in particular Bitcoins. In this market, there are two typologies of agents, Random Traders and Chartists, which interact with each other by trading Bitcoins. Each agent is initially endowed with a finite amount of crypto and/or fiat cash and issues buy and sell orders, according to her strategy and resources. The number of Bitcoins increases over time with a rate proportional to the real one, even if the mining process is not explicitly modelled. The model proposed is able to reproduce some of the real statistical properties of the price absolute returns observed in the Bitcoin real market. In particular, it is able to reproduce the autocorrelation of the absolute returns, and their cumulative distribution function. The simulator has been implemented using object-oriented technology, and could be considered a valid starting point to study and analyse the cryptocurrency market and its future evolutions.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。