  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.
