a r t i c l e i n f o JEL classification: C23 E44 Q43 Keywords: Crude oil shocks Stock market prices Panel data Asymmetric adjustment Granger causality This paper proposes a panel threshold cointegration approach to investigate the relationship between crude oil shocks and stock markets for the OECD and non-OECD panel from January 1995 to December 2009. Nonlinear cointegration is confirmed for ...

In this paper the relationships between crude oil and refined product prices are investigated in a multivariate framework. This allows us to test several (partly competing) assumptions of earlier studies. In particular, we find that the crude oil price is weakly exogenous and that the spread is constant in some but not all relationships. Moreover, the multivariate analysis shows that the link b...

a r t i c l e i n f o We test whether the spot price of crude oil is determined by stochastic rules or exhibits deterministic endog-enous fluctuations. In our analysis, we employ both metric (correlation dimension and Lyapunov exponents) and topological (recurrence plots) diagnostic tools for chaotic dynamics. We find that the underlying system for crude oil spot prices (i) is of high dimension...

This paper investigated the hedging effectiveness of crude palm oil futures market in Malaysia from January 2009 to June 2011 which traded under Bursa Malaysia Derivatives Berhad. Ordinary Least Squared (OLS) method was used to compute Minimum-Variance hedging ratio (MVHR), R-squared and hedging effectiveness by using daily data from settlement price of crude palm oil futures contracts and spot...

This paper examines the effect of the volatility of oil prices on food price in South Africa using monthly data covering the period 2002:01 to 2014:09. Food price is measured by the South African consumer price index for food while oil price is proxied by the Brent crude oil. The study employs the GARCH-in-mean VAR model, which allows the investigation of the effect of a negative and positive s...

This paper proposes an alternative approach based on a genetic algorithm and neural network (GA–NN) for the prediction of the West Texas Intermediate (WTI) crude oil price. Comparative simulation results suggested that the proposed GA–NN approach is better than the baseline algorithms in terms of prediction accuracy and computational efficiency. Mann–Whitney test results indicated that the WTI ...

In this study, a multiscale neural network learning paradigm based on empirical mode decomposition (EMD) is proposed for crude oil price prediction. In this learning paradigm, the original price series are first decomposed into various independent intrinsic mode components (IMCs) with a range of frequency scales. Then the internal correlation structures of different IMCs are explored by neural ...

The popularity of realized measures and various linear models for volatility forecasting has been the focus of attention in the literature addressing energy markets’ price variability over the past decade. However, there are no studies to help practitioners achieve optimal forecasting accuracy by guiding them to a specific estimator and model. This paper contributes to this literature in two wa...

I use daily futures price data to examine the behavior of natural gas and crude oil price volatility in the U.S. since 1990. I test whether there has been a significant trend in volatility, whether there was a short-term increase in volatility during the time of the Enron collapse, and whether natural gas and crude oil price volatilities are interrelated. I also measure the persistence of shock...

ƒ In addition to accurate forecasts of the price of oil, policy-makers are interested in evaluating the risks associated with the baseline forecast to gauge the implications of alternative oil price paths for the economic outlook. A structural model of the global oil market can be used to develop risk scenarios for oil price forecasts, based on hypothetical assumptions about future demand and s...