Forecasting Crude Oil Prices Using the Binary RSI (bRSI) Indicator

The crude oil market is one of the most significant sectors in the global economy. Fluctuations in oil prices impact the financial performance of national economies. Crude oil prices are also the basis of many popular financial derivatives on the financial market. Binary-temporal representation state models enable the precise modelling and development of financially efficient decision-support systems in the crude oil market. Existing models are primarily based on the main technical analysis methods: trend and moving average analysis. In this paper, with the aim of enhancing forecasting efficiency, we introduce the concept of determining the widely used RSI indicator for binary-temporal representation and propose a new state model based on its readings. We also present empirical research on the proposed model applied to the oil market, using historical data from the past six years. The results confirm the validity of the approach adopted.