在NFT市场的周期性,艾略特波和分数
1University of Illinois Chicago, Chicago, USA. westland@uic.edu.
Scientific reports
|February 23, 2024
概括
非可变代币 (NFT) 的价格是由特定资产的粉丝社区和加密货币的影响驱动的,而不是传统的市场模式. 粉丝定期交易,以及比特币和以太币的运动,解释了NFT价格动态.
科学领域:
- 数字资产数字资产
- 区块链技术 区块链技术
- 市场分析市场分析
背景情况:
- 非可替代代币 (NFT) 通过独特的基于区块链的数字资产为创作者提供新的收入来源.
- 由于其日益增长的经济意义,了解NFT市场行为至关重要.
研究的目的:
- 调查NFT市场的低效率和周期性行为.
- 分析加密货币对NFT价格的影响.
- 确定NFT价格系列的可预测性.
主要方法:
- 使用周期性行为提取模型分析NFT价格系列.
- 在加密货币和NFT市场中对自动循环的调查.
- 在NFT和加密货币 (比特币,以太币) 价格变动之间的相关性分析.
主要成果:
- 线性模型对NFT价格系列无效;周期性模型提供更好的解释和预测.
- NFT价格行为与基础资产和粉丝社区的定期交易密切相关.
- 在24-48小时内发现比特币/以太币价格变动与NFT价格/数量之间存在显著的相关性.
结论:
- NFT市场的功能更像是社交媒体平台,而不是传统交易所.
- 传统的经济计量模型无法预测NFT价格;由粉丝驱动的活动和加密影响是关键.
- 碎形模型在解释一些NFT价格行为时显示出有限的,不稳定的一致性.
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