Bitcoins are traded on various exchange platforms and, therefore, prices may differ across trading venues. We aim to investigate return connectedness across eight of the major exchanges of Bitcoin, both from a static and a dynamic viewpoint. To this end, we employ an extension of the order‐invariant forecast error variance decomposition proposed by Diebold and Yilmaz (2012) to a generalized vector error correction framework. Our results suggest that there is strong connectedness among the exchanges, as expected, although some of them behave dissimilarly. We identify Bitfinex and Coinbase as leading exchanges during the considered period, while Kraken as a follower exchange. We also obtain that connectedness across exchanges is strongly dynamic, as it evolves over time.

中文翻译：

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矢量错误校正模型可测量比特币交易市场的连通性

比特币在各种交换平台上进行交易，因此，各个交易场所的价格可能有所不同。我们的目标是从静态和动态的角度研究整个八个主要比特币交易所的收益联系。为此，我们将Diebold和Yilmaz（2012）提出的阶不变预测误差方差分解扩展为广义矢量误差校正框架。我们的结果表明，正如预期的那样，交易所之间有很强的联系性，尽管其中一些交易所的行为有所不同。在确定的时期内，我们将Bitfinex和Coinbase确定为主要交易所，而将Kraken确定为跟随者交易所。我们还发现，随着时间的推移，跨交易所的联系具有很强的动态性。