论文标题
基于机器学习的加密货币的监管风险指数
A Machine Learning Based Regulatory Risk Index for Cryptocurrencies
论文作者
论文摘要
加密货币的价值经常对重大政策变化做出积极反应，但现有指数都没有告知与监管变化相关的市场风险。在本文中，我们量化了源自金融科技和加密货币（CCS）的新法规的风险，并分析其对市场动态的影响。具体而言，基于与政策相关的新闻报道频率构建了加密货币调节风险指数（CRRIX）。未标记的新闻数据是从顶级在线CC新闻平台收集的，并使用潜在的Dirichlet分配模型和Hellinger距离进一步分类。我们的结果表明，基于机器的CRRIX成功捕捉了改变政策的主要时刻。 VCRIX，市场波动指数和CRRIX的运动都是同步的，这意味着CRRIX对加密货币市场的所有参与者都可能有帮助。该算法和Python代码可在www.quantlet.de上进行研究。
Cryptocurrencies' values often respond aggressively to major policy changes, but none of the existing indices informs on the market risks associated with regulatory changes. In this paper, we quantify the risks originating from new regulations on FinTech and cryptocurrencies (CCs), and analyse their impact on market dynamics. Specifically, a Cryptocurrency Regulatory Risk IndeX (CRRIX) is constructed based on policy-related news coverage frequency. The unlabeled news data are collected from the top online CC news platforms and further classified using a Latent Dirichlet Allocation model and Hellinger distance. Our results show that the machine-learning-based CRRIX successfully captures major policy-changing moments. The movements for both the VCRIX, a market volatility index, and the CRRIX are synchronous, meaning that the CRRIX could be helpful for all participants in the cryptocurrency market. The algorithms and Python code are available for research purposes on www.quantlet.de.
