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.
Highlights
No one can deny that the recent US financial crisis was one of the most unpredicted economic events in the recent history, the severity with which it melted markets and economies around the world
This paper investigates the dynamic causal linkages in the daily returns amongst five major international stock price indices in East Asia, namely, Nikkei 225 (Japan), Kospi (Korea), Shanghai Stock Exchange Composite Index (China), Taiwan Stock Exchange Index (TAIEX) and Hang Seng Index (Hong Kong) from 15th September 2008 to 1st March 2016
We tried to investigate the economic leader in East Asian countries after the collapse of Lehman Brothers based on several conventional time-series techniques and a newly introduced method – wavelet analysis - to economics and finance
Summary
No one can deny that the recent US financial crisis was one of the most unpredicted economic events in the recent history, the severity with which it melted markets and economies around the world. In such a context, we investigate the stock indices causality among the East Asian economies through conventional techniques such as long run structural modelling, vector error correction and variance decomposition and as well as a novel approach known as wavelet analysis. We investigate the stock indices causality among the East Asian economies through conventional techniques such as long run structural modelling, vector error correction and variance decomposition and as well as a novel approach known as wavelet analysis This analysis is a very helpful technique since it represents a refinement in terms of analysis in both time and frequency domains (Rua and Nunes, 2009). A pioneer study by Ramsey and Lampart (1998a, b) to investigate the relationship between several macroeconomic variables by employing wavelets
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