{"title":"A Comparison of Cryptocurrency Volatility-benchmarking New and Mature Asset Classes","authors":"Alessio Brini, Jimmie Lenz","doi":"arxiv-2404.04962","DOIUrl":null,"url":null,"abstract":"The paper analyzes the cryptocurrency ecosystem at both the aggregate and\nindividual levels to understand the factors that impact future volatility. The\nstudy uses high-frequency panel data from 2020 to 2022 to examine the\nrelationship between several market volatility drivers, such as daily leverage,\nsigned volatility and jumps. Several known autoregressive model specifications\nare estimated over different market regimes, and results are compared to equity\ndata as a reference benchmark of a more mature asset class. The panel\nestimations show that the positive market returns at the high-frequency level\nincrease price volatility, contrary to what is expected from the classical\nfinancial literature. We attributed this effect to the price dynamics over the\nlast year of the dataset (2022) by repeating the estimation on different time\nspans. Moreover, the positive signed volatility and negative daily leverage\npositively impact the cryptocurrencies' future volatility, unlike what emerges\nfrom the same study on a cross-section of stocks. This result signals a\nstructural difference in a nascent cryptocurrency market that has to mature\nyet. Further individual-level analysis confirms the findings of the panel\nanalysis and highlights that these effects are statistically significant and\ncommonly shared among many components in the selected universe.","PeriodicalId":501139,"journal":{"name":"arXiv - QuantFin - Statistical Finance","volume":"214 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Statistical Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2404.04962","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The paper analyzes the cryptocurrency ecosystem at both the aggregate and
individual levels to understand the factors that impact future volatility. The
study uses high-frequency panel data from 2020 to 2022 to examine the
relationship between several market volatility drivers, such as daily leverage,
signed volatility and jumps. Several known autoregressive model specifications
are estimated over different market regimes, and results are compared to equity
data as a reference benchmark of a more mature asset class. The panel
estimations show that the positive market returns at the high-frequency level
increase price volatility, contrary to what is expected from the classical
financial literature. We attributed this effect to the price dynamics over the
last year of the dataset (2022) by repeating the estimation on different time
spans. Moreover, the positive signed volatility and negative daily leverage
positively impact the cryptocurrencies' future volatility, unlike what emerges
from the same study on a cross-section of stocks. This result signals a
structural difference in a nascent cryptocurrency market that has to mature
yet. Further individual-level analysis confirms the findings of the panel
analysis and highlights that these effects are statistically significant and
commonly shared among many components in the selected universe.