Crude Oil Price Movement Analysis Through Mining of Historical Price Data Distribution to Determine the Sample Size Over Price and Time Scale

Crude oil markets are always changing rapidly and unpredictably. Predicting the market price movements have been challenging towards countries and companies. There are multiple factors that cause the price of crude oil to be of high volatility. This study focuses on using technical analysis approach to forecast and predict crude oil future price movement. In this thesis, a new approach is proposed to determine the suitable sampling size to be used dynamically. Through mining the distribution of historical price data, the price movement forecasting approach are formulated by using dynamic size of data sampling.