Explaining crude oil prices using fundamental measures

Coleman, Les

doi:10.1016/j.enpol.2011.10.012

Cited by 120 publications

(77 citation statements)

References 21 publications

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“…The Baltic Dry Index which tracks the cost of shipping goods across the oceans is used as an indicator of global industrial production following [Mitchell et al, 2005], [Frale et al, 2008], [Kilian, 2009], Fan and Xu [2011] and [Coleman, 2012] . A criticism of using the BDI is that it is inuenced by fuel costs, and so is an endogenous variable.…”

Section: Testing Frameworkmentioning

confidence: 99%

“…Thus we have a situation where speculators provide insurance to producers by taking the excess long positions not taken by consumers, but only producers have access to all the information regarding oil reserves and supply issues. [Kaufmann, 2011], [Coleman, 2012], [Fan and Xu, 2011] and [Cifarelli and Paladino, 2010] all show that speculation is an important driver of oil prices. As with the equity markets there are limits to arbitrage, namely the size of the positions traders are permitted to take and the size of the margin calls which traders will incur while they wait for their prots to materialize.…”

Section: Introductionmentioning

confidence: 99%

“…Speculation was measured by Coleman [2012] and Bunn and Chen [2013] using the churn ratio, which was the ratio of the number of forwards or futures contracts to physical delivery, this indicated the level of speculation in the oil and electricity markets respectively. A more specic measure was also used, namely the number of non-commercial futures positions from the CFTC.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sentiment in oil markets

Deeney

Cummins

Dowling

et al. 2015

International Review of Financial Analysis

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Section: Testing Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Sentiment in oil markets

Deeney

Cummins

Dowling

et al. 2015

International Review of Financial Analysis

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“…We compare the oil price forecastability of the VRP with alternative predictors that have been used in the existing literature (see Kaufmann (2011) andColeman (2012) among others). Due to data limitations, our analysis investigates the in-sample properties of the predictive regression of the monthly excess returns for the WTI futures.…”

Section: Introductionmentioning

confidence: 99%

A fear index to predict oil futures returns

Chevallier

Sévi

2014

Energy Studies Review

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This paper evaluates the predictability of WTI light sweet crude oil futures by using the variance risk premium, i.e. the difference between model-free measures of implied and realized volatilities. Additional regressors known for their ability to explain crude oil futures prices are also considered, capturing macroeconomic, financial and oil-specific influences. The results indicate that the explanatory power of the (negative) variance risk premium on oil excess returns is particularly strong (up to 25% for the adjusted Rsquared across our regressions). It complements other financial (e.g. default spread) and oil-specific (e.g. US oil stocks) factors highlighted in previous literature.

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“…We compare the oil price forecastability of the VRP with alternative predictors that have been used in the existing literature (see Kaufmann (2011) and Coleman (2012) among others). Due to data limitations, our analysis investigates the in-sample properties of the predictive regression of the monthly excess returns for the WTI futures.…”

mentioning

confidence: 99%