Title: Screening for light crude oil and market comovements
Authors: Faseli, Omid  
Keywords: Data Mining; Pattern Recognition; Correlation Cluster Map; Clustering; Comolvement; Light Crude Oil; WTI; Brent
Issue Date: 12-Dec-2020
Journal: International Journal of Research in Business and Social Science (IJRBS)
Abstract: 
This study aimed to perform a screening for economic interrelationships among market participants from the stock market, global stock indices, and commodities from fossil energy, agricultural, and the metals sector.
Particular focus was put on the comovements of the light crude oil benchmarks West
Texas Intermediate (WTI) and Brent crude oil.
In finance research and the crude oil markets, identifying novel groupings and interactions is a fundamental requirement due to the extended impact of crude oil price fluctuations on economic growth and inflation.
Thus, it is of high interest for investors to identify market players and interactions that appear sensitive to crude oil price volatility triggers.
The price development of 14 stocks, 25 leading global indices, and 13 commodity prices, including WTI and Brent, were analyzed via data mining applying the hierarchical correlation cluster mapping technique.
All price data comprised the period from January 2012 – December 2018 and were based
on daily returns.
The technique identifies and visualizes existing hierarchical clusters and correlation
patterns emphasizing comovements that indicate positively correlated processes.
The method successfully identified clustering patterns and a series of relevant and partly unexpected novel comovements in all investigated economic sectors.
Although additional research is required to reveal the causative factors, the study offers an insight into in-depth market interrelationships.
DOI: 10.20525/ijrbs.v9i7.949
Organisation: E194 - Institut für Information Systems Engineering 
License: CC BY 4.0 CC BY 4.0
Publication Type: Article
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