Oil price dynamics (2002–2006)

Askari, Hossein; Krichene, Noureddine

doi:10.1016/j.eneco.2007.12.004

Cited by 129 publications

(82 citation statements)

References 40 publications

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“…Macroeconomic factors have been considered by Hamilton (1983), Bernanke et al (1997), Hamilton (2003) and Barsky and Lutz (2004). How supply and demand imbalances, along with the movements in the business cycle, impact on oil prices has been investigated in depth (Kilian, 2006, 2007, Askari and Krichene, 2008, Kilian, 2008, Kaufmann, 2011. Heath (2016) provides a contemporary study on the macroeconomic factors that drive oil prices, showing that measures of real economic activity forecast oil futures prices and, most notably, that real economy shocks have a resulting impact on oil prices.…”

Section: Introductionmentioning

confidence: 99%

Oil market modelling: A comparative analysis of fundamental and latent factor approaches

Cummins

Dowling

Kearney

2016

International Review of Financial Analysis

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We formally compare fundamental factor and latent factor approaches to oil price modelling. Fundamental modelling has a long history in seeking to understand oil price movements, while latent factor modelling has a more recent and limited history, but has gained popularity in other financial markets. The two approaches, though competing, have not formally been compared as to effectiveness. For a range of short-medium-and long-dated WTI oil futures we test a recently proposed five-factor fundamental model and a Principal Component Analysis latent factor model. Our findings demonstrate that there is no discernible difference between the two techniques in a dynamic setting. We conclude that this infers some advantages in adopting the latent factor approach due to the difficulty in determining a well specified fundamental model.

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Section: Introductionmentioning

confidence: 99%

Oil market modelling: A comparative analysis of fundamental and latent factor approaches

Cummins

Dowling

Kearney

2016

International Review of Financial Analysis

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“…This literature started in the aftermath of Middle East geopolitical factors that coincided with OPEC's increasing market power in the 1970s, but later studies uncovered asymmetries and other subtleties, both in terms of oil price responses to potential geopolitical and market factors, and in terms of real economic responses to oil price fluctuations, which often take the form of jumps, c.f. Askari and Krichene (2008).…”

Section: Model Of Demand For Military Spendingmentioning

confidence: 99%

Winter is Coming: Controlled Conflicts and the Oil-Price Geopolitical-Risk Premium

El‐Gamal

2016

SSRN Journal

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“…Fuzzy K-NN Classifier is the most popular choice for classification applications because it gives information about the certainty of the classification decision and it is simple [31][32][33][34][35]. Fuzzy K-Nearest Neighbor Classifier (FKNN) is an improved algorithm of the standard K-Nearest Neighbor (KNN) algorithm.…”

Section: Fuzzy K-nearest Neighbor (Fknn)mentioning

confidence: 99%

Quality Assurance for Economy Classification based on Data Mining Techniques

Rawas¹,

Mahmoud²

2017

Bus Eco J

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Researchers in the quality assurance field used traditional techniques for increasing the organization income and take the most suitable decisions. Today they focus and search for a new intelligent techniques in order to enhance the quality of their decisions. This paper based on applying the most robust trend in computer science field which is data mining in the quality assurance field. The cases study which is discussed in this paper based on detecting and predicting the developed and developing countries based on the indicators. This paper uses three different artificial intelligent techniques namely; Artificial Neural Network (ANN), k-Nearest Neighbor (KNN), and Fuzzy k-Nearest Neighbor (FKNN). The main target of this paper is to merge between the last intelligent techniques applied in the computer science with the quality assurance approaches. The experimental result shows that proposed approaches in this paper achieved the highest accuracy score than the other comparative studies as indicates in the experimental result section.

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Oil price dynamics (2002–2006)

Cited by 129 publications

References 40 publications

Oil market modelling: A comparative analysis of fundamental and latent factor approaches

Oil market modelling: A comparative analysis of fundamental and latent factor approaches

Winter is Coming: Controlled Conflicts and the Oil-Price Geopolitical-Risk Premium

Quality Assurance for Economy Classification based on Data Mining Techniques

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