The Lead-Lag Relationship among East Asian Economies: A Wavelet Analysis


  •  Buerhan Saiti    

Abstract

Recently, the issue of market linkages (and price discovery) between stock indices and the lead-lag relationship is a topic of interest to financial economists, financial managers and analysts, especially that involves the East Asian countries. In this study, to investigate the financial market leader in East Asian countries after the US financial crisis, we employ several conventional time-series techniques and a newly introduced method – wavelet analysis - to economics and finance. Daily return data covering the period from 15th September 2008 to 1st March 2016 for five major international stock price indices in East Asia are analyzed. Our findings tend to, more or less, suggest that the Shanghai stock exchange composite index is the only exogenous variable, whereas the remaining variables are endogenous. Such finding implies that the Shanghai stock exchange composite index is the financial market leader whereas the rest of variables are follower, which includes Nikkei 225 (Japan). In order to check the robustness of our results, we also employed wavelet correlation and cross-correlation techniques. Interestingly, based on the results, the leading role of Shanghai Stock Exchange Composite Index is very clear at short scales; whereas, the leading role disappears at the long scales. This study shows that wavelet analysis can provide a valuable alternative to the existing conventional methodologies in identifying lead-lag (causality) relationship between financial/economic variables, since wavelets considered heterogeneous agents who making decisions over different time horizons.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • Issn(Print): 1913-9004
  • Issn(Onlne): 1913-9012
  • Started: 2008
  • Frequency: monthly

Journal Metrics

Google-based Impact Factor (2019): 14.58

h-index (February 2019): 54

i10-index (February 2019): 453

h5-index (February 2019): 26

h5-median(February 2019): 35

( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )

Contact