Narayan Paresh Kumar
Monash Business School, Monash University, Melbourne, Australia.
Financ Res Lett. 2022 Mar;45:102181. doi: 10.1016/j.frl.2021.102181. Epub 2021 May 30.
Using a dynamic VAR model fitted to hourly data, we evaluate the evolution of spillover shocks from exchange rates returns of EURO, Yen, CAD and GBP. We find that over the COVID-19 sample: (a) total exchange rate shock spillovers explain around 37.7% of the forecast error variance in the exchange rate market compared to only 26.1% in the pre-COVID-19 period; and (b) exchange rate own shocks explain between 56% to 75% of own exchange rate movements. These results hold in multiple robustness tests. The implication is that exchange rates predict most of their own changes. We confirm this through an economic significance test where we show that the shock spillovers predict exchange rate returns and these predicted exchange rates can be useful in extracting buy and sell trading signals.
使用一个拟合每小时数据的动态向量自回归（VAR）模型，我们评估了欧元、日元、加元和英镑汇率回报的溢出冲击的演变。我们发现，在新冠疫情期间样本中：（a）汇率冲击总溢出解释了汇率市场约37.7%的预测误差方差，而在新冠疫情前时期仅为26.1%；（b）汇率自身冲击解释了自身汇率变动的56%至75%。这些结果在多个稳健性检验中都成立。这意味着汇率预测了其大部分自身变化。我们通过一项经济显著性检验证实了这一点，在该检验中我们表明冲击溢出预测了汇率回报，并且这些预测汇率可用于提取买卖交易信号。
