首页> 中文期刊> 《系统科学与复杂性:英文版》 >A Hybrid Approach for Studying the Lead-Lag Relationships Between China's Onshore and Offshore Exchange Rates Considering the Impact of Extreme Events

A Hybrid Approach for Studying the Lead-Lag Relationships Between China's Onshore and Offshore Exchange Rates Considering the Impact of Extreme Events

         

摘要

Understanding the characteristics of the dynamic relationship between the onshore Renminbi (CNY) and the offshore Renminbi (CNH) exchange rates considering the impact of some extreme events is very important and it has wide implications in several areas such as hedging.For better estimating the dynamic relationship between CNY and CNH,the Granger-causality test and Bry-Boschan Business Cycle Dating Algorithm were employed in this paper.Due to the intrinsic complexity of the lead-lag relationships between CNY and CNH,the empirical mode decomposition (EMD) algorithm is used to decompose those time series data into several intrinsic mode function (IMF) components and a residual sequence,from high to low frequency.Based on the frequencies,the IMFs and a residual sequence are combined into three components,identified as short-term composition caused by some market activities,medium-term composition caused by some extreme events and the long-term trend.The empirical results indicate that when it only matters the short-term market activities,CNH always leads CNY;while the medium-term impact caused by those extreme events may alternate the lead-lag relationships between CNY and CNH.

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  • 来源
    《系统科学与复杂性:英文版》 |2018年第3期|734-749|共16页
  • 作者单位

    Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China;

    Center for Forecasting Science,Chinese Academy of Sciences,Beijing 100190,China;

    Department of Management Sciences,City University of Hong Kong,Hong Kong,China;

    School of Finance,Central University of Finance and Economics,Beijing 100081,China;

    China Great Wall Asset Management Corporation,Beijing 100045,China;

    Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China;

    Center for Forecasting Science,Chinese Academy of Sciences,Beijing 100190,China;

    International Business School,Shaanxi Normal University,Xi'an 710119,China;

    Department of Industrial and Manufacturing Systems Engineering,Hong Kong University,Hong Kong,China;

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  • 正文语种 eng
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