Determinants of the crude oil futures curve: Inventory, consumption and volatility

Nikitopoulos, Christina Sklibosios; Squires, Matthew; Thorp, Susan; Yeung, Danny

doi:10.1016/j.jbankfin.2017.07.006

Cited by 33 publications

(26 citation statements)

References 41 publications

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“…These findings are consistent with the theory of storage, in that the adjusted basis is wider and has higher variation when the inventory is low. Therefore, our results are in line with the main predictions of the theory of storage and consistent with the recent literature (see, e.g., Almansour, 2016; Byun, 2017; Nikitopoulos et al, 2017). However, our Fama and French indirect tests, reported in the previous section, do not support this for crude oil.…”

Section: Resultssupporting

confidence: 94%

“…Following Fama and French (1987), we construct the interest‐adjusted basis, which has been widely applied in the literature (see, e.g., Gao & Wang, 2005; Geman & Ohana, 2009; Nikitopoulos et al, 2017) and has the financial interpretation of the cost of carry. This variable is defined as the difference between the second and the first nearby futures contracts and is adjusted for a risk‐free interest rate, as follows:

{italiciab}_{italictT} = \frac{F (t, 2) - F (t, 1) (1 + r (t, T))}{F (t, 1)},

where

{iab}_{tT}

is the 2‐month interest‐adjusted basis (adjusted basis henceforth); and F ( t , 1) and F ( t , 2) are the first and the second nearby futures prices.…”

Section: Methodsmentioning

confidence: 99%

“…Gorton et al (2013) find a negative and nonlinear relationship between inventories and convenience yield and conclude that the basis reflects the state of inventories. By separating the positive and negative bases, Nikitopoulos et al (2017) find that positive bases do not cause adjustments in the U.S. crude oil and petroleum inventory, as the theory of storage predicts. They also show that, in addition to the indirect transmission of consumption shocks through inventories, there are other direct effects of petroleum consumption on future bases.…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

The theory of storage in the crude oil futures market, the role of financial conditions

Ahmadi

Behmiri

Manera

2020

Journal of Futures Markets

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This study examines the impacts of inventory and financial instability on the basis of the crude oil market. The results show that, first, the basis rises with inventory, and this effect is higher during low inventory regimes. This validates the theory of storage in the crude oil market. Second, the basis rises with financial instability, and this effect is higher during turbulent regimes. These results warn the oil market participants that, to make decisions based on the basis variation, traditionally known as a signal of scarcity or abundance, the underlying cause of the variation has to be considered.

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Section: Resultssupporting

confidence: 94%

{italiciab}_{italictT} = \frac{F (t, 2) - F (t, 1) (1 + r (t, T))}{F (t, 1)},

where

{iab}_{tT}

is the 2‐month interest‐adjusted basis (adjusted basis henceforth); and F ( t , 1) and F ( t , 2) are the first and the second nearby futures prices.…”

Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

The theory of storage in the crude oil futures market, the role of financial conditions

Ahmadi

Behmiri

Manera

2020

Journal of Futures Markets

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“…He came to an interesting finding that the analysed geopolitical events had a positive impacts on oil prices before the year 2000, however, their impact has diminished afterwards. Pierru, et al (2018) investigated the impacts of OPEC's policies on the oil price volatility and Nikitopoulos, et al (2017) investigated the impacts of oil inventories and consumption on the oil price volatility.…”

Section: Literature Reviewmentioning

confidence: 99%

Seasonal patterns in oil prices and their implications for investors

Árendáš

Tkacova

Bukoven

2018

Journal of International Studies

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This paper focuses on the investigation of oil price seasonal patterns and their exploitability in the investment process. As oil is one of the most important and most traded commodities, a successful investment strategy exploiting seasonal patterns in oil price behaviour may be useful for many retail as well as institutional investors. The results show that during the 1983-2017 period, the Brent and WTI oil prices tended to record abnormally positive returns during the months of March, April and August and abnormally negative returns -during the months of October and November. The analysis also shows that simple investment strategies based on switching between the oil market and money market investments, that are utilizing the oil price seasonal patterns, can outperform in the long term.

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“…However, studies forecasting futures prices are scarce. According to Sklibosios Nikitopoulos et al (2017), futures prices depend on the value of deferred use. For example, decreasing futures prices show that the value of immediate use (consumption) or the yield to holders of physical inventory is reducing.…”

Section: Introductionmentioning

confidence: 99%

Can We Forecast Daily Oil Futures Prices? Experimental Evidence from Convolutional Neural Networks

Luo

Cai

Tanaka

et al. 2019

JRFM

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This paper proposes a novel approach, based on convolutional neural network (CNN) models, that forecasts the short-term crude oil futures prices with good performance. In our study, we confirm that artificial intelligence (AI)-based deep-learning approaches can provide more accurate forecasts of short-term oil prices than those of the benchmark Naive Forecast (NF) model. We also provide strong evidence that CNN models with matrix inputs are better at short-term prediction than neural network (NN) models with single-vector input, which indicates that strengthening the dependence of inputs and providing more useful information can improve short-term forecasting performance.

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Determinants of the crude oil futures curve: Inventory, consumption and volatility

Cited by 33 publications

References 41 publications

The theory of storage in the crude oil futures market, the role of financial conditions

The theory of storage in the crude oil futures market, the role of financial conditions

Seasonal patterns in oil prices and their implications for investors

Can We Forecast Daily Oil Futures Prices? Experimental Evidence from Convolutional Neural Networks

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