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Cointegration and stock market interdependence: Evidence from South Africa, India and the USA
Author(s) -
T. Mohanasundaram,
K. Parthasarathy
Publication year - 2015
Publication title -
suid-afrikaanse tydskrif vir ekonomiese en bestuurswetenskappe/south african journal of economic and management sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 17
eISSN - 2222-3436
pISSN - 1015-8812
DOI - 10.4102/sajems.v18i4.1029
Subject(s) - cointegration , granger causality , stock market , stock market index , econometrics , economics , vector autoregression , stock (firearms) , composite index , index (typography) , financial economics , johansen test , multivariate statistics , normality , error correction model , statistics , geography , mathematics , composite indicator , context (archaeology) , archaeology , world wide web , computer science
The purpose of this study is to explore the nature of the association and the possible existence of a shortrun and long-run relationship between the stock-market indices of South Africa, India and the USA. The idea behind this combination is to know how the stock markets of these three prominent countries are related to each other. The study employs monthly data from the stock indices, namely JALSH (South Africa), NIFTY (India) and NASDAQ (USA) composite from April 2004 to March 2014. After testing for the normality of the data distribution and the stationarity of the time series data, this paper discovered a strong correlation between the stock market indices of South Africa, India and the USA. The correlation among the stock markets is high, particularly between South Africa and India. In addition, the paper attempts to discover the presence of any predictive ability among these markets by applying the Granger causality test. The result indicates that the NASDAQ index has no predictive ability as far as the JALSH and NIFTY indices are concerned. However, the JALSH index has a predictive ability on the NIFTY index. After testing the Granger cause relationship, the existence of a long-run and short-run relationship is tested. The long-run relationships among the stock market indices are analysed, following the Johansen and Juselius multivariate cointegration approach. The result suggests the absence of a long-run relationship among the three stock market indices. Short-run relationship is investigated with the Vector Autoregression (VAR) model, and the outcome obtained shows that both the USA and the South African stock markets are predicted only by their own past lags. However, the Indian stock market is seen to be a function of its own past lags and the past lags of the South African stock index

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