Modelling Dynamic Conditional Correlations in WTI Oil Forward and Futures Returns

This paper estimates the dynamic conditional correlations in the returns on WTI oil one-month forward prices, and one-, three-, six-, and twelve-month futures prices, using recently developed multivariate conditional volatility models. The dynamic correlations enable a determination of whether the forward and various futures returns are substitutes or complements, which are crucial for deciding whether or not to hedge against unforeseen circumstances. The models are estimated using daily data on WTI oil forward and futures prices, and their associated returns, from 3 January 1985 to 16 January 2004. At the univariate level, the estimates are statistically significant, with the occasional asymmetric effect in which negative shocks have a greater impact on volatility than positive shocks. In all cases, both the short- and long-run persistence of shocks are statistically significant. Among the five returns, there are ten conditional correlations, with the highest estimate of constant conditional correlation being 0.975 between the volatilities of the three-month and six-month futures returns, and the lowest being 0.656 between the volatilities of the forward and twelve-month futures returns. The dynamic conditional correlations can vary dramatically, being negative in four of ten cases and being close to zero in another five cases. Only in the case of the dynamic volatilities of the three-month and six-month futures returns is the range of variation relatively narrow, namely (0.832, 0.996). Thus, in general, the dynamic volatilities in the returns in the WTI oil forward and future prices can be either independent or interdependent over time

Modeling UK Natural Gas Prices When Gas Prices Periodically Decouple from the Oil Price

When natural gas prices are subject to periodic decoupling from oil prices, for instance due to peak-load pricing, conventional linear models of price dynamics such as the Vector Error Correction Model (VECM) can lead to erroneous inferences about cointegration relationships, price adjustments and relative values. We propose the use of regime-switching models to address these issues. Our regime switching model uses price data to infer whether pricing is oil-driven (integrated) or gas-specific (decoupled). We find that UK natural gas (ICE) and oil (Brent) are cointegrated for the majority of the sample considered (1997-2014). Gas prices tend to decouple during fall and early winter, when they increase relative to oil consistent with heating demand for natural gas creating gas-specific pricing. Using the model to infer relative values when evidence favors integrated markets, we find that the industry 10-1 rule-of-thumb holds, meaning that the value of one barrel of oil is 10 times the value of one MMbtu of natural gas

Trends, Persistence, and Volatility in Energy Markets

This paper makes a threefold contribution to the underlying dynamic properties and causal effects of energy prices. Firstly, the paper makes a study of the underlying trends to help identify the time series path of nonrenewable energy resources, which can have far reaching consequences for economists and policy makers alike. The analysis is extended to also determine the persistence of oil price shocks. Secondly, the study examines the causal relation between oil prices and the macroeconomy allowing for nonlinear models that have been recently advocated in the literature. Finally, this study describes the relation between oil prices and agricultural commodities. From a policy perspective, these interrelationships of agricultural and oil prices warrant careful consideration in the context of the recent energy crisis, which may very well continue in the future

Efficiency Of Foreign Exchange Markets: A Developing Country Perspective

This study tests weak and semi-strong form efficiency of the foreign exchange market in Sri Lanka during the recent float using six bilateral exchange rates. Weak-form efficiency is examined using unit root tests while semi-strong form efficiency is tested using cointegration, Granger causality tests and variance decomposition analysis. Results indicate that the Sri Lankan foreign exchange market is consistent with the weak-form of the efficient market hypothesis (EMH). However, the results provide evidence against the semi-strong version of the EMH. These results have important implications for government policy makers and participants in the foreign exchange market of Sri Lank