英文标题：
《Cryptocurrencies, Mainstream Asset Classes and Risk Factors - A Study of
Connectedness》
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作者：
George Milunovich
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最新提交年份：
2018
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英文摘要：
We investigate connectedness within and across two major groups or assets: i) five popular cryptocurrencies, and ii) six major asset classes plus two commonly employed risk factors. Granger-causality tests uncover six direct channels of causality from the elements of the mainstream assets/risk factors group to digital assets. On the other hand there are two statistically significant causal links going in the other direction. In order to provide some perspective on the magnitude of the uncovered linkages we supplement the analysis by estimating networks from forecast error variance decompositions. The estimated connectedness within the groups is relatively large, whereas the linkages across the two groups are small in comparison. Namely, less than 2.2 percent of future uncertainty of any cryptocurrency is sourced from all non-crypto assets combined, while the joint contribution of all digital assets to non-crypto uncertainty does not exceed 1.5 percent.
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中文摘要：
我们调查了两大集团或资产内部和之间的连通性：i）五种流行的加密货币，以及ii）六种主要资产类别加上两种常用的风险因素。格兰杰因果关系检验揭示了从主流资产/风险因素组的要素到数字资产的六个直接因果关系渠道。另一方面，有两个统计上显著的因果关系朝着另一个方向发展。为了对未发现的联系的规模提供一些看法，我们通过预测误差方差分解估计网络来补充分析。组内的估计连通性相对较大，而两组之间的联系相对较校也就是说，任何加密货币的未来不确定性不到2.2%来自所有非加密资产的总和，而所有数字资产对非加密不确定性的共同贡献不超过1.5%。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：General Finance 一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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