Abstract—Volatile crude oil prices have been drawing a lot of attention lately since it plays a significant role in the world economy. The recent severe price movement has immensely impacted the economy of countries that rely heavily on the production of crude oil and natural gas. While businesses have been struggling in making financial decision to hedge their risk against possible future price fluctuation, governmental bodies and policy makers often caught in the midst of severe volatility. Hence, this paper presents a historical price data distribution analysis by using dynamic data sampling base on the characteristic of the price data distribution. Experiment was conducted on the historical price data of crude oil futures for the period of thirty years. The outcome of the experiment indicates a promising performance demonstrating the relevancy of the proposed approach.
Index Terms—Data mining, data analysis, knowledge discovery, time series analysis, statistical analysis.
The authors are with Swinburne University of Technology Sarawak, Jalan Simpang Tiga, 93350 Kuching, Sarawak, Malaysia (e-mail: khsim@swinburne.edu.my).
[PDF]
Cite: Kwan-Hua Sim, Isaac Goh, and Kwan-Yong Sim, "Analysing Price Movements of Crude Oil Futures by Mining of Dynamic Sample Size through Price Distribution of the Historical Data," International Journal of Modeling and Optimization vol. 5, no. 6, pp. 393-397, 2015.