Oil price shocks and industry stock returns

Rehman

Economic Research-Ekonomska Istraživanja

et al. 2016

This study analyses risk-return trade-off and behaviour of various volatility dynamics including: volatility, its persistence, mean reversion and speed of mean reversion along with asymmetry and leverage effect on the Pakistani stock market by employing aggregate (aggregate market level) and disaggregate (sectoral level) monthly data for the period from 1998 to 2012. Three generalised autoregressive conditional heteroscedasticity models were applied: GARCH (1,1) for various volatility dynamics; EGARCH for asymmetric and leverage effect and GARCH-M for pricing of risk. The outcomes of the study are as follows: first, the volatility shocks are quite persistent but with varying degrees across the sectors. Both the ARCH effect (short-term effect) and GARCH effect (long-term effect) play their role in generating conditional future stock returns volatility. Further, overall the volatility process is mean reverting; however, the speed of mean reversion varies across the sectors. Secondly, the current study finds little evidence of asymmetry and leverage effect at both aggregate and disaggregates data. Thirdly, the pricing of risk (positive risk premium) is also evident, particularly at the disaggregate data in the Pakistani stock market. Finally, this research study sets the implications for both the policy makers and investors.

Section: Introductionmentioning

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Pricing of risk and volatility dynamics on an emerging stock market: evidence from both aggregate and disaggregate data

Rehman

Economic Research-Ekonomska Istraživanja

et al. 2016

Should crude oil price volatility receive more attention than the price of crude oil? An empirical investigation via a large‐scale out‐of‐sample forecast evaluation of US macroeconomic data

Nonejad¹

2020

Journal of Forecasting

Apart from the percentage change in the price of crude oil, there is a growing tradition of using various nonlinear transformations of the price of crude oil to forecast real gross domestic product growth rates, equity returns, inflation and other macroeconomic variables. This study attempts to quantify the additional potential predictive power afforded by crude oil price volatility relative to widely used crude oil price-based variables for more than 300 US macroeconomic time series at the monthly and the quarterly sampling frequency. We observe that regressions employing crude oil price realized volatility and crude oil price realized semivolatilities tend to afford a more consistent pattern of out-of-sample prediction gains relative to competitors using well-known crude oil price measures and the autoregressive benchmark at the quarterly and monthly sampling frequency. While it is somewhat harder to find evidence of finite-sample predictive gains relative to the benchmark, the evidence is stronger with respect to population-level predictability 1 quarter (1 month) ahead for the model with crude oil price realized semivolatilities across the considered data and models. Furthermore, point (density) forecasts employing crude oil price realized volatility tend to be more accurate than corresponding forecasts produced under the crude oil price-based predictive regressions in a horse race.

Journal of Futures Markets

Impact of international energy prices on China's industries

Wong

Zhang

2020

This study examines how returns and volatility of future contracts for Brent crude oil (Brent), West Texas Intermediate crude oil (WTI), Henry Hub natural gas, and Newcastle thermal coal impacts industries in China. Using the firm‐level data of 3,750 stock listings across both Shanghai and Shenzhen stock exchanges, segregated into 138 subindustries under the Global Industry Classification Standard, this study finds evidence that crude oil futures have the most significant influence. Further analysis suggests that stock returns of oil‐related companies are more closely align to Brent and WTI's futures returns following China's key oil pricing reform on March 27, 2013. Overall, Chinese industries are also more exposed to global crude oil futures volatility after this event.