探索比特币价格的决定因素：贝叶斯结构时间序列的应用
Exploring the determinants of Bitcoin's price: an application of Bayesian Structural Time Series
AI总结：
本文通过贝叶斯结构时间序列方法研究比特币价格与内部和外部因素的关系，揭示其混合属性，包括投机、避险和资本外逃功能。
摘要：
目前，比特币的真实属性尚无共识。讨论涵盖其作为投机或避险资产的用途，而其他作者则认为增强的吸引力可能使货币功能无法满足经济理论的要求。本文通过贝叶斯结构时间序列方法探讨比特币市场价格与一组内部和外部因素之间的关联。旨在通过区分多种吸引力来源，并采用提供更灵活分析框架的方法，分解时间序列的每个组成部分，应用变量选择，纳入先前研究的信息，并动态检验解释变量的行为，所有这些都在透明且可操作的设定下完成。结果表明，比特币价格与中性投资者情绪、黄金价格和人民币对美元汇率呈负相关，而与股票市场指数、美元对欧元汇率以及不同国家搜索趋势的变异符号呈正相关。因此，发现比特币具有混合属性，仍似乎同时充当投机、避险和潜在资本外逃工具。
英文摘要：
Currently, there is no consensus on the real properties of Bitcoin. The discussion comprises its use as a speculative or safe haven assets, while other authors argue that the augmented attractiveness could end accomplishing money's functions that economic theory demands. This paper explores the association between Bitcoin's market price and a set of internal and external factors using Bayesian Structural Time Series Approach. I aim to contribute to the discussion by differentiating among several attractiveness sources and employing a method that provides a more flexible analytic framework that decompose each of the components of the time series, apply variable selection, include information on previous studies, and dynamically examine the behavior of the explanatory variables, all in a transparent and tractable setting. The results show that the Bitcoin price is negatively associated with a neutral investor's sentiment, gold's price and Yuan to USD exchange rate, while positively related to stock market index, USD to Euro exchange rate and variated signs among the different countries' search trends. Hence, I find that Bitcoin has mixed properties since still seems to act as a speculative, safe haven and a potential a capital flights instrument.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
