Tracing dynamic linkages and spillover effect between Pakistani and leading foreign stock markets

Abstract

This study traces the degree of integration and volatility spillover effect between the Pakistani and leading foreign stock markets by analyzing the Meteor shower hypothesis. Daily data are used from nine worldly equity markets (KSE 100, NIKKEI 225, HIS, S&P 500, NASDAQ 100, DOW JONES, GADXI, FTSE 350 and DFMGI) for the period of 2005 to 2014. First, we used the whole data set and after that we split data set into two subsets, First subset of data contains the era of global financial crisis of 2008 from 2005 to 2009 and Second subset is after global financial crisis time period from 2010 to 2014 (The global crisis prevailed till end of 2009). By following the Hamao et al. (1990) technique the univariate GARCH type models are employed to explore the dynamic linkages between Pakistani and leading foreign stock markets. The results from whole data set illustrate that there is mixed co‐movements between leading foreign stock markets and Pakistani stock market. The results from both subsets provide an evidence that there is a unidirectional mean and volatility spillover effect from S&P 500, NASDAQ 100, DJI and DFMGI to KSE 100. Also we found bidirectional spillover effect between DFMGI and KSE 100 from both subsets of data. We concluded that there is only one indirect linkage through which may the information transmitted to KSE 100. This linkage is developed due to the co‐movement among KSE 100, DFMGI and NASDAQ 100 in crisis period. This integration between these markets may provide a sign of indirect linkage. It also exhibits the volatility in Pakistan stock market returns is instigated through direct effects as well as indirect effects. Our study brings important conclusions for financial institutions, portfolio managers, market players and academician to diagnose the nature and level of linkages between the financial markets.

Measuring Return and Volatility Spillovers among Sectoral Stocks in Nigeria

“…Of the papers surveyed in this study, just one study have examined volatility transmissions in the Nigerian stock market (see, Kpughur er al,, 2017) however, it adopts aggregate data and examines transmissions between the naira exchange rate and the stock market using approaches different from this study. There are also studies for other regions, worthy of mention is China (see, e.g., Wang and Zhang, 2011;Sharma, 2017;Jebran et al, 2017), BRICS (see, e.g., Ramaprasad and Biljana, 2007;Boubaker and Raza, 2017;Nareshet al, 2018), U.S (see, e.g., Arouri et al, 2011;Ghouse and Khan, 2017;Kinnunen, 2017;Oh, 2017;Bekiros et al, 2016), Europe (see, e.g., Arouri et al, 2011;Chang et al, 2013;Sharma, 2017;Blau, 2017), South America (see, e.g., Vasco and Agudelo, 2014;Gamba-Santamaria et al, 2016)among others. Furthermore, we notice that there are few or no studies on returns and volatility transmission at the sectoral level in Sub Saharan African regions, this is probably due to data inadequacies or constraints.…”

“…In the literature, differing methods have been used to examine returns and volatility transmissions in stock markets. Some of the prominent techniques include; General Autoregressive Conditional Heteroscedasticity (GARCH) models (see, e.g., Ramaprasad and Biljana, 2007;Arouri et al, 2011;Chang et al, 2013;Jebran, et al, 2017;Kpughur et al, 2017;Ghouse and Khan, 2017;Apergis and Gupta, 2017;Boubaker and Raza, 2017), Vector Autoregression (see, e.g., Andrikopoulos et al, 2014;Baoko and Alagidede, 2017;Sharma, 2017;Kinnunen, 2017), Regression analysis (see, e.g., Wang and Zhang, 2011;Vasco and Agudelo, 2014;Fauzi and Wahyudi, 2016;Blau, 2017) to mention a few.…”

“…Particular attention has been paid to presence of transmission mechanism between markets. Many studies report unidirectional volatility spillovers between markets (for example, see; Arouri et al, 2011;Ghouse and Khan, 2017;Kpughur et al, 2017) while some others reported a bidirectional relationship between markets (see, e.g., Du and He, 2015;Majdoub and Sassi, 2016;Jebran et al, 2017;Boubaker and Raza, 2017). On the contrary, some studies report no evidence of significant comovement (see, e.g., Chang et al, 2013;Bekiros et al, 2016;Kinnunen, 2017).…”

Tracing Return and Volatility Spillover Effect between Exchange Rate and Pakistan Stock Exchange Index

“…The issue remains that the inherent mechanism of world of global equity investing can be pretty bewildering which brings multi-fold impacts. Example being the later global financial crisis of 2008, which has gravely impacted the economy and stock markets of Pakistan (Ghouse & Khan, 2017). The situation got further worsen off in 2009, when the KSE 100 stood at 4,929.54 with total capitalization of market was Rs.…”

“…43.19 but it was gone to Rs. 61.4 (Qayyum & Kamal, 2007;Qayyum & Khan 2014;Din et al, 2010;Ghouse & Khan, 2017;Jebran & Iqbal, 2016;Bhat & Shah 2015;Dar et al, 2013;Aslam, 2104;Ali, 2015). On the other hand, many researchers explored causal linkages between these variables in case of Pakistan see for example (Zubair, 2013;Khan & Ali, 2015;Zia & Rahman, 2011).…”