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Recent literature has shifted to examining whether exchange rate volatility symmetrically or asymmetrically affects the trade flows. This study aims to extend the existing literature by examining the effects of extremely large to extremely small changes in exchange rate volatility series on the US imports from Brazil, India, Mexico and South Africa.

For examining the effects of extreme changes, multiple threshold nonlinear autoregressive distributed lag (MTNARDL) model is used and the exchange rate volatility series is divided into quintiles and deciles. It helps to examine the effects of each quintile/decile of exchange rate volatility series on the US imports.

Findings indicate that the effects of extremely large changes in the exchange rate volatility series significantly differ from the effects of extremely small changes in the exchange rate volatility series on the US imports.

The findings of this study are very important. These findings help to consider the effect of extreme changes before devising policies related to trade flows.

This study mainly focuses on US imports from Brazil, India, Mexico and South Africa. In addition, this study extends the existing literature by using a novel methodology called MTNARDL model.

The purpose of this paper is of twofold: first, to empirically examine the short-run and long-run impact of macroeconomic variables such as industrial production, foreign direct investment (FDI), trade balance (TB), exchange rate, interest rate (IR) and consumer price index (CPI) on stock prices (SP) of KSE-100 index; and second, to examine whether this relationship changes as a result of the financial crisis.

This study uses an autoregressive distributed lag model by using the full sample period data from 1997Q3 to 2018Q2 and the post-crisis period data from 2008Q3 to 2018Q2. Moreover, it uses variance decomposition analysis to examine the importance of each variable in explaining SP.

The findings of the full sample period indicate that in the long run, TB, exchange rate and IR negatively affect SP whereas CPI and industrial production positively affect SP. However, the post-crisis period data indicate that only CPI positively affects the SP in the long run. Finally, variance decomposition analysis indicates 30 percent variance in SP is explained by its own shock.

The study findings suggest that macroeconomic variables have a significant role and can be considered important for taking investment and/or policy decisions. Especially, Governments and other regulators may need to take measures to increase the TB since it can help to increase the performance of the Pakistani stock market. Furthermore, investors may consider that findings change when the financial crisis has been taken into consideration.

This study uses two additional variables, namely FDI and TB by using the robust technique in the context of emerging countries like Pakistan. Furthermore, it takes into account the impact of the financial crisis on the underlying variables.