比特币价格:技术驱动因素、宏观经济基本面与经济主体预期的组态效应

Bitcoin Prices: Configurational Effects of Technological Drivers, Macroeconomic Fundamentals and Economic Agents' Expectation

International Journal of Finance and Economics · 2025
被引 1
ABS 3

中文导读

本研究使用模糊集定性比较分析和必要条件分析,基于2011-2022年月度数据,发现经济主体预期(如商业信心指数)对比特币价格的影响超过传统因素,并识别出九种导致高价的组态和八种导致低价的组态。

Abstract

ABSTRACT This study aims at bridging critical gaps in the existing cryptocurrency research by exploring combinations of technological, macroeconomic and behavioural factors, namely, economic agents' expectations and the size of influence that each of them has on the Bitcoin price movements. In contrast to the existing studies that focused on individual determinants and estimated aggregate effects thereof, in this study, fuzzy‐set qualitative comparative analysis (fsQCA) is applied to determine configurations of drivers to determine the Bitcoin price and used necessary condition analysis (NCA) to quantify the magnitude of the effects using the monthly data between 2011 and 2022. Findings show that economic agents' expectations such as OECD's Business Confidence Index, Consumer Confidence Index and Composite Leading Indicator emerge as influential variables of Bitcoin, surpassing traditional drivers like Gold and Financial Stress Index. Among these, Business Confidence Index and Composite Leading Indicator exhibit a very large effect on Bitcoin prices, and from the technology variable group, Average Block Size exhibits a very large effect on Bitcoin prices. fsQCA indicates that nine distinct configurations contribute to high Bitcoin prices and eight configurations lead to low Bitcoin prices, thus depicting equifinality in Bitcoin price determination. These insights can provide policymakers and investors with a better understanding of the Bitcoin price dynamic by finding out necessary variables and equifinal pathways towards either high or low prices, thus promoting better risk management activities, as well as regulatory approaches to this highly dynamic asset class.

比特币加密货币宏观经济行为金融组态分析