Asymmetric Volatility Transmission in Cryptocurrency Markets: The Role of Market Capitalization and Exogenous Shocks
Description
This dataset was collected to examine whether volatility transmission in digital asset markets is asymmetric, with large-cap cryptocurrencies exerting a stronger influence on small-cap cryptocurrencies than the reverse, and whether negative market events generate larger and more persistent effects than positive ones. The data include daily U.S.-dollar closing prices for Bitcoin, Ethereum, Binance Coin, LBRY Credits, Energi, and Utrust over the period 1 September 2018 to 1 March 2023, from which daily log-returns are constructed. For the event-study analysis, the package also includes the Royalton CRIX Crypto Index and a list of eleven major cryptocurrency-related events, such as Black Thursday, the Terra-Luna collapse, and the FTX collapse. The data show that volatility spillovers run mainly from large-cap to small-cap assets, that negative events produce stronger and more persistent abnormal returns than positive ones, and that conditional correlations increase over time, especially during stress periods. These findings indicate growing market integration and systemic risk within cryptocurrency markets. The dataset can therefore be used to study contagion, volatility spillovers, event effects, and hedging strategies in digital asset markets.
Files
Steps to reproduce
All information necessary to understand how the data were gathered and how the research can be reproduced is provided in the accompanying README file. The README specifies that this replication package relates to the paper Asymmetric Volatility Transmission in Cryptocurrency Markets: The Role of Market Capitalization and Exogenous Shocks by Mariana Santos, Carmela Iorio, and Bruno Damásio, submitted to Economic Modelling (Manuscript ID: ECMODE-D-25-03011). The replication package contains all data and code required to replicate every table and figure in the paper. All data are publicly available from Yahoo Finance (https://finance.yahoo.com). The raw CSV files downloaded from Yahoo Finance are included in this package to ensure exact reproducibility. The analysis is conducted entirely in R. The package includes raw daily price data downloaded from Yahoo Finance, and a single self-contained R script that produces all results reported in the manuscript. In this way, the README serves as the main reference document for data provenance, software requirements, and replication procedures, allowing an independent researcher to understand the construction of the dataset and replicate the study in full.