{"title":"Modelling common bubbles in cryptocurrency prices","authors":"Mauri K. Hall , Joann Jasiak","doi":"10.1016/j.econmod.2024.106782","DOIUrl":null,"url":null,"abstract":"<div><p>Bubbles and spikes in cryptocurrency prices increase considerably the risk on investments in these assets. In the traditional time series literature bubbles are viewed as nonstationary and non-estimable components of a process. In this paper, we adopt a different approach and consider the bubbles as inherent features of a strictly stationary causal-noncausal (mixed) Vector Autoregressive (VAR) process. This approach allows us to model and estimate the common bubbles and spikes in cryptocurrency prices. It also provides us linear combinations of cryptocurrencies that eliminate common bubbles analogously to the cointegrating vectors eliminating common trends in unit root processes. They are used to build cryptocurrency portfolios immune to the risk of common bubbles that ensure stable investment strategies. The mixed VAR model is estimated from the US Dollar prices of Bitcoin, Ethereum, Ripple, and Stellar over the period 2017–2019. We document the common bubbles and illustrate the behaviour of bubble-free portfolios.</p></div>","PeriodicalId":48419,"journal":{"name":"Economic Modelling","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S026499932400138X/pdfft?md5=cb3d51d2119ee4fdfe8cd7a1ef4a90e3&pid=1-s2.0-S026499932400138X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Modelling","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S026499932400138X","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Bubbles and spikes in cryptocurrency prices increase considerably the risk on investments in these assets. In the traditional time series literature bubbles are viewed as nonstationary and non-estimable components of a process. In this paper, we adopt a different approach and consider the bubbles as inherent features of a strictly stationary causal-noncausal (mixed) Vector Autoregressive (VAR) process. This approach allows us to model and estimate the common bubbles and spikes in cryptocurrency prices. It also provides us linear combinations of cryptocurrencies that eliminate common bubbles analogously to the cointegrating vectors eliminating common trends in unit root processes. They are used to build cryptocurrency portfolios immune to the risk of common bubbles that ensure stable investment strategies. The mixed VAR model is estimated from the US Dollar prices of Bitcoin, Ethereum, Ripple, and Stellar over the period 2017–2019. We document the common bubbles and illustrate the behaviour of bubble-free portfolios.
加密货币价格的泡沫和飙升大大增加了这些资产的投资风险。在传统的时间序列文献中,泡沫被视为一个过程中的非稳态和不可估计的组成部分。在本文中,我们采用了一种不同的方法,将泡沫视为严格静止的因果-非因果(混合)向量自回归(VAR)过程的固有特征。通过这种方法,我们可以对加密货币价格中常见的泡沫和尖峰进行建模和估算。它还为我们提供了加密货币的线性组合,这些组合可以消除常见的泡沫,类似于单位根过程中消除常见趋势的协整向量。它们可用于构建不受常见泡沫风险影响的加密货币投资组合,以确保投资策略的稳定性。混合 VAR 模型是根据 2017-2019 年期间比特币、以太坊、瑞波币和恒星币的美元价格估算的。我们记录了常见的泡沫,并说明了无泡沫投资组合的行为。
期刊介绍:
Economic Modelling fills a major gap in the economics literature, providing a single source of both theoretical and applied papers on economic modelling. The journal prime objective is to provide an international review of the state-of-the-art in economic modelling. Economic Modelling publishes the complete versions of many large-scale models of industrially advanced economies which have been developed for policy analysis. Examples are the Bank of England Model and the US Federal Reserve Board Model which had hitherto been unpublished. As individual models are revised and updated, the journal publishes subsequent papers dealing with these revisions, so keeping its readers as up to date as possible.