Revisiting the oil price and stock market nexus: A nonlinear Panel ARDL approach

Oil price shocks, economic policy uncertainty and industry stock returns in China: Asymmetric effects with quantile regression

This article examines the nonlinear Granger causality and time-varying influence between crude oil prices and the US dollar (USD) exchange rate using the Hiemstra and Jones (HP) test, the Diks and Panchenko (DP) test and the time-varying parameter structural vector autoregression model. By applying the iterated cumulative sums of squares (ICSS) algorithm and the DCC-GARCH model, the effects of structural breaks in volatility of the two markets are also investigated. The empirical analysis indicates that, first, crude oil prices are the nonlinear Granger-cause of the USD exchange rate, but not vice versa. Second, the USD exchange rate exerts a stronger and more stable negative influence on crude oil prices in the short term, and the influence gradually weakens after 2012. Finally, ignoring structural breaks can increase the negative volatility correlation between the oil and USD exchange rate markets, which is particularly remarkable during the financial crisis.

Interaction between oil and US dollar exchange rate: nonlinear causality, time-varying influence and structural breaks in volatility

Nuclear energy, renewable energy and economic growth in Pakistan: Evidence from non-linear autoregressive distributed lag model

Heterogeneous impacts of wars on global equity markets: Evidence from the invasion of Ukraine

The effects of oil price shocks on the economies of the Gulf Co-operation Council countries: Nonlinear analysis

This article examines the J-curve phenomenon for 16 European transition economies. While previous studies assume a linear relationship between the exchange rate and the trade balance, this paper allows for nonlinearity. Following Bahmani-Oskooee and Fariditavana (2015, 2016), the empirical method used is the nonlinear cointegrating autoregressive distributed lag (NARDL) model of Shin et al. (2013) in which short-run and long-run nonlinearities are introduced via positive (appreciation) and negative (depreciation) partial sum decompositions of the real exchange rate. We argue that the lack of support for the J-curve phenomenon could be due to the linearity assumption. This issue is examined by utilizing the linear and the NARDL models. Using the linear autoregressive distributed lag (ARDL) model, we are unable to find support for the J-curve phenomenon in any case. However, when the NARDL model is used, we are able to find evidence for the J-curve in 12 out of the 16 countries. This suggests that a...

The J-Curve phenomenon in European transition economies: A nonlinear ARDL approach

The effects of oil price shocks on Asian exchange rates: Evidence from quantile regression analysis

This paper examines the effects of oil price shocks on the stock market returns of the Gulf Cooperation Council countries. The empirical method used is quantile regression analysis. In addition, we allow for structural breaks and asymmetry by differentiating between positive and negative oil price changes. Unlike OLS analysis, quantile regression allows the coefficient estimates to vary throughout the distribution of the dependent variable, which provides a complete picture of the relationship between the explanatory variables and the dependent variable. Our results suggest that the coefficient estimates have not been constant throughout the distribution of stock returns; that oil price shocks have asymmetrical effects on stock returns; and that the effects of oil price shocks on stock market returns are affected by stock market conditions. Overall, the results suggest that rising oil prices increase stock returns only when stock markets are bullish (high quantiles) and normal (medium quantiles), and that falling oil prices lower stock returns only when stock markets are bearish (low quantiles) and normal (medium quantiles). This suggests that oil and stock markets are more likely to boom together or crash together.

Oil price shocks and stock market returns of the GCC countries: empirical evidence from quantile regression analysis

We utilize nonlinear models to examine the stationarity of Asian real exchange rates over the period from 1980:10 to 2007:09, using the US, Japan, and China as base countries. We find evidence of nonlinearity in most cases. Contrary to widely-held belief that the behavior of the real exchange rate should exhibit symmetrical adjustment for deviations above and below the equilibrium level, we find strong evidence of asymmetrical adjustment for most cases. Applying unit root tests that account for two types of nonlinearities (smooth transition and nonlinear deterministic trends) reveals evidence of stationarity in all but the Philippines vis-a-vis Japan. Further testing shows that the results are robust to different exchange rate regimes and, in the case of Malaysia, robust to the imposition of capital controls after the 1997 Asian crisis.

Salah A. Nusair

Papers

The effects of oil price shocks on the economies of the Gulf Co-operation Council countries: Nonlinear analysis

The J-Curve phenomenon in European transition economies: A nonlinear ARDL approach

The effects of oil price shocks on Asian exchange rates: Evidence from quantile regression analysis

Oil price shocks and stock market returns of the GCC countries: empirical evidence from quantile regression analysis

Nonlinear adjustment of Asian real exchange rates