Uncertainty and realized jumps in the pound-dollar exchange rate: evidence from over one century of data

IF 0.7 4区 经济学 Q3 ECONOMICS
Konstantinos Gkillas, Rangan Gupta, Dimitrios Vortelinos
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引用次数: 0

Abstract

Abstract We study the importance of economic uncertainty so as to predict realized jumps (hereafter jumps) in the pound-dollar exchange rate. The empirical analysis covers the time period from February 1900 to May 2018 on a monthly basis, incorporating several market states, including various booms and crashes. First, we apply a standard linear Granger causality test in order to identify causal effects from economic uncertainty to jumps. We show that the standard linear Granger causality test fails to capture such casual effects. Providing the misspecification of the linear model, we next make use of a nonparametric causality-in-quantiles test. This test allows us to take into account the substantial evidence of nonlinearity along with the structural breaks between economic uncertainty and jumps. In applying this data-driven robust procedure, we find strong evidence of uncertainty causing jumps of the dollar-pound exchange rate. These results are robust over the entire conditional distribution of jumps, exhibiting the strongest impact at the lowest conditional quantiles considered. In addition, our results are generally found to be robust to alternative measures of uncertainty, jumps generated at a daily frequency based on shorter samples of intraday data, and across three other dollar-based exchange rates.
英镑兑美元汇率的不确定性和已实现的跳跃:来自一个多世纪数据的证据
摘要:本文研究经济不确定性的重要性,以预测英镑兑美元汇率的已实现跳跃(以下简称跳跃)。该实证分析涵盖了从1900年2月到2018年5月的时间段,包括几个市场状态,包括各种繁荣和崩溃。首先,我们应用标准的线性格兰杰因果检验,以确定经济不确定性对跳跃的因果影响。我们表明,标准的线性格兰杰因果检验未能捕捉到这种偶然效应。提供线性模型的错误说明,我们接下来使用非参数分位数因果关系检验。这个测试允许我们考虑非线性的实质性证据以及经济不确定性和跳跃之间的结构性断裂。在应用这一数据驱动的稳健程序时,我们发现了强有力的证据,证明不确定性导致美元英镑汇率跳升。这些结果在跳跃的整个条件分布上是稳健的,在考虑的最低条件分位数上表现出最强的影响。此外,我们的结果通常被发现对于不确定性的替代度量是稳健的,基于较短的日内数据样本以每日频率产生的跳跃,以及其他三种基于美元的汇率。
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
34
期刊介绍: Studies in Nonlinear Dynamics & Econometrics (SNDE) recognizes that advances in statistics and dynamical systems theory may increase our understanding of economic and financial markets. The journal seeks both theoretical and applied papers that characterize and motivate nonlinear phenomena. Researchers are required to assist replication of empirical results by providing copies of data and programs online. Algorithms and rapid communications are also published.
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